{"id":551,"date":"2026-09-11T21:17:33","date_gmt":"2026-09-11T12:17:33","guid":{"rendered":"https:\/\/localmodelwatch.tsuchitsuchi.com\/2026\/09\/11\/pantheon-reasoning-26b-gguf\/"},"modified":"2026-10-30T11:08:22","modified_gmt":"2026-10-30T02:08:22","slug":"pantheon-reasoning-26b-gguf","status":"publish","type":"post","link":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/2026\/09\/11\/pantheon-reasoning-26b-gguf\/","title":{"rendered":"Gryphe_Pantheon-Reasoning-26B-A4B-1.1-V2-GGUF: Our Test Answers"},"content":{"rendered":"<p><!-- lmw:facts --><\/p>\n<h2>At a Glance<\/h2>\n<div class=\"lmw-table-scroll\" tabindex=\"0\" style=\"overflow-x:auto;-webkit-overflow-scrolling:touch;max-width:100%;\">\n<table style=\"width:max-content;min-width:100%;border-collapse:collapse;\">\n<thead>\n<tr>\n<th>Item<\/th>\n<th>Value<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Repository<\/td>\n<td><a href=\"https:\/\/huggingface.co\/bartowski\/Gryphe_Pantheon-Reasoning-26B-A4B-1.1-V2-GGUF\">bartowski\/Gryphe_Pantheon-Reasoning-26B-A4B-1.1-V2-GGUF<\/a><\/td>\n<\/tr>\n<tr>\n<td>Published<\/td>\n<td>2026-09-10<\/td>\n<\/tr>\n<tr>\n<td>License<\/td>\n<td>apache-2.0<\/td>\n<\/tr>\n<tr>\n<td>Formats<\/td>\n<td><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/format-gguf-en\/\">GGUF<\/a><\/td>\n<\/tr>\n<tr>\n<td>Source type<\/td>\n<td>Primary source (the publisher itself)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p><em>Values determined by this site&#8217;s code when the information was collected. Dates are JST.<\/em><\/p>\n<p><!-- \/lmw:facts --><\/p>\n<p><!-- lmw:lab-summary --><\/p>\n<p><strong>What we checked ourselves<\/strong><\/p>\n<ul>\n<li>Ran <code>Gryphe_Pantheon-Reasoning-26B-A4B-1.1-V2-Q3_K_S.gguf<\/code> (Q3_K_S) on our CPU-only server (Neoverse-N1, 3 threads, llama.cpp b11223): generation at 6.2 tokens\/s (a CPU figure, not a GPU speed).<\/li>\n<li>Its answers to our fixed Japanese questions are shown verbatim below.<\/li>\n<li>It needs about 18% fewer tokens than the Qwen3 tokenizer for the same Japanese text, so about 1.22\u00d7 as much Japanese fits in the same context length, and generation is faster per character.<\/li>\n<\/ul>\n<p>Details and conditions are in \u201cOur Own Measurements\u201d below.<\/p>\n<p><!-- \/lmw:lab-summary --><\/p>\n<h2>Overview<\/h2>\n<p><strong>[Important] The information introduced in this article has not yet been officially confirmed and is based on breaking data at the time of writing. Please note that details may change due to future verification or official announcements.<\/strong><\/p>\n<p>It is reported that the prominent uploader bartowski has released a GGUF quantized version of Gryphe&#8217;s model, <code>bartowski\/Gryphe_Pantheon-Reasoning-26B-A4B-1.1-V2-GGUF<\/code>. This is a 26B model specialized for roleplay and reasoning based on the Gemma 4 architecture, and various quantized files are provided for local execution.<\/p>\n<h2>Specifications<\/h2>\n<ul>\n<li>License: apache-2.0<\/li>\n<li>Base Model: Gryphe\/Pantheon-Reasoning-26B-A4B-1.1-V2<\/li>\n<li>Architecture: Gemma4ForConditionalGeneration<\/li>\n<\/ul>\n<h2>Performance<\/h2>\n<p>According to the base model&#8217;s model card and published information, comparison data regarding text quality and reasoning trace behavior during roleplay has been shown. As for writing quality trends across different comparison targets, for example, the Type-token ratio is 0.770 for Pantheon Reasoning and 0.748 for Pantheon Reasoning (no-think), shifting from 0.686 for the base model.<\/p>\n<p>Additionally, regarding the frequency of clich\u00e9 occurrences, it is reported that while Base instruct has 1.141 occurrences per 100 words, Pantheon Reasoning sees a significant reduction to 0.546 occurrences, and Pantheon Reasoning (no-think) to 0.541 occurrences. On the other hand, since enabling the thinking process outputs reasoning traces, users should note that there is a trade-off regarding response length and latency depending on the task.<\/p>\n<h2>Strengths and Use Cases<\/h2>\n<p>The base model is reported to be a model specialized for roleplay and reasoning that adopts the Gemma 4 MoE architecture. It has been fine-tuned with advanced creative writing and roleplay use cases in mind, such as character psychological description, tone adjustment, and narrative development planning, and is trained so that the thinking process is enabled across all reasoning turns.<\/p>\n<p><!-- lmw:hardware --><\/p>\n<h2>Hardware Requirements<\/h2>\n<p><strong>Estimated requirements (calculated by Local Model Watch)<\/strong> \u2014 26.5B parameters (taken from the base model Gryphe\/Pantheon-Reasoning-26B-A4B-1.1-V2)<\/p>\n<div class=\"lmw-table-scroll\" tabindex=\"0\" style=\"overflow-x:auto;-webkit-overflow-scrolling:touch;max-width:100%;\">\n<table style=\"width:max-content;min-width:100%;border-collapse:collapse;\">\n<thead>\n<tr>\n<th>Your VRAM<\/th>\n<th>Quantization<\/th>\n<th>File size<\/th>\n<th>Est. memory needed<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>12GB (RTX 4070 \/ 3060 12GB, etc.)<\/td>\n<td>IQ2_S<\/td>\n<td>10.0GB<\/td>\n<td>12.0GB<\/td>\n<\/tr>\n<tr>\n<td>16GB (RTX 5060 Ti 16GB \/ 4060 Ti 16GB, etc.)<\/td>\n<td>IQ3_XS<\/td>\n<td>12.7GB<\/td>\n<td>15.2GB<\/td>\n<\/tr>\n<tr>\n<td>24GB (RTX 4090 \/ 3090, etc.)<\/td>\n<td>Q5_K_M<\/td>\n<td>19.4GB<\/td>\n<td>23.2GB<\/td>\n<\/tr>\n<tr>\n<td>32GB (RTX 5090, etc.)<\/td>\n<td>Q8_0<\/td>\n<td>25.7GB<\/td>\n<td>30.9GB<\/td>\n<\/tr>\n<tr>\n<td>80GB class (A100 \/ H100)<\/td>\n<td>BF16<\/td>\n<td>48.4GB<\/td>\n<td>58.1GB<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p><em>Memory estimates add a 20% runtime overhead (KV cache, etc.) to the actual size of the distributed files. Actual usage varies with context length, batch size and inference engine. These figures are computed by this site from file sizes, not published by the model&#8217;s authors. Compare with other models in our <a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/vram-guide-en\/\">VRAM quick reference<\/a>. What the quantization names mean: <a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/glossary-quantization-en\/\">glossary<\/a>.<\/em><\/p>\n<p><!-- \/lmw:hardware --><\/p>\n<p><!-- lmw:runnability --><\/p>\n<h2>Can You Run It Locally?<\/h2>\n<p><strong>Runs in Ollama, LM Studio and llama.cpp as-is.<\/strong><\/p>\n<p>It is distributed in GGUF, so no conversion is needed.<\/p>\n<p><strong>License \u2014 <code>apache-2.0<\/code> (Commercial use allowed):<\/strong> Permits commercial use, modification and redistribution. Redistribution requires including the license and stating changes; includes a patent grant.<\/p>\n<p><strong>Compression:<\/strong> the IQ2_S build measures 3.24 bits per weight \u2014 about 20% the size of the original 16-bit weights, calculated by this site from the actual file sizes.<\/p>\n<p><em>Compiled by this site&#8217;s code from the published formats, converted builds we have found, and each engine&#8217;s own model registry. &#8220;Not found&#8221; means we have not seen such a build, not that none exists. License summaries are not legal advice \u2014 check the publisher&#8217;s original terms before relying on them.<\/em><\/p>\n<p><!-- \/lmw:runnability --><\/p>\n<p><!-- lmw:lab --><\/p>\n<h2>Our Own Measurements<\/h2>\n<p>Values we measured ourselves on our server (no GPU) by actually reading and running this model&#8217;s files \u2014 not figures copied from the model card. How we measure, and the results for every model: <a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/observations-en\/\">Our Measurements<\/a>.<\/p>\n<h3>What We Found<\/h3>\n<p>When running the Gryphe_Pantheon-Reasoning-26B-A4B-1.1-V2-GGUF model on a Neoverse-N1 CPU environment, the generation speed reached 11.0 characters per second, showing faster performance compared to other models measured under the same conditions, although longer responses suffered from repeated lines. The token count per 1,000 Japanese characters is 564, meaning it can process Japanese with fewer tokens than the compared Qwen3 tokenizer. Memory consumption peaked at 14.9 GB, and because the 4-bit version was too large, measurements were taken using the lower Q3_K_S bit quantization.<\/p>\n<p>In the five Japanese test questions, the model successfully answered the task of summarizing an article of about 1,200 characters in exactly three sentences without hitting the token limit and as instructed. It also correctly derived the right answer of 280 yen for the shopping word problem and generated three spring haikus as requested. The outputs were produced smoothly without any internal reasoning text mixed into the final answers.<\/p>\n<p>On the other hand, issues remained in knowledge retrieval and business email generation. For the question asking for prefectures not facing the sea, while it successfully listed all 8 landlocked prefectures, it also incorrectly included 9 prefectures that actually do face the sea. In the task of writing a polite business email to a client, a phenomenon occurred where the same line was repeated up to 4 times, and the length reached 1,762 characters, showing that control can break down during the generation of longer texts.<\/p>\n<h3>Japanese Token Efficiency<\/h3>\n<div class=\"lmw-table-scroll\" tabindex=\"0\" style=\"overflow-x:auto;-webkit-overflow-scrolling:touch;max-width:100%;\">\n<table style=\"width:max-content;min-width:100%;border-collapse:collapse;\">\n<thead>\n<tr>\n<th>Tokenizer<\/th>\n<th>Tokens per 1,000 Japanese characters<\/th>\n<th>Ratio to the same text in English<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>This model<\/strong><\/td>\n<td><strong>564<\/strong><\/td>\n<td><strong>1.03\u00d7<\/strong><\/td>\n<\/tr>\n<tr>\n<td>Qwen3<\/td>\n<td>688<\/td>\n<td>1.26\u00d7<\/td>\n<\/tr>\n<tr>\n<td>Llama 3.2<\/td>\n<td>744<\/td>\n<td>1.36\u00d7<\/td>\n<\/tr>\n<tr>\n<td>Gemma 3<\/td>\n<td>564<\/td>\n<td>1.03\u00d7<\/td>\n<\/tr>\n<tr>\n<td>gpt-oss<\/td>\n<td>795<\/td>\n<td>1.45\u00d7<\/td>\n<\/tr>\n<tr>\n<td>LLM-jp-3<\/td>\n<td>497<\/td>\n<td>0.85\u00d7<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>It needs about 18% fewer tokens than the Qwen3 tokenizer for the same Japanese text, so about 1.22\u00d7 as much Japanese fits in the same context length, and generation is faster per character.<\/p>\n<p>Counted with the <code>tokenizer.json<\/code> of <a href=\"https:\/\/huggingface.co\/Gryphe\/Pantheon-Reasoning-26B-A4B-1.1-V2\">Gryphe\/Pantheon-Reasoning-26B-A4B-1.1-V2<\/a> on a fixed text we wrote ourselves (876 Japanese characters across news, conversation, technical docs, a formal email, travel writing and a recipe) and its English translation. Fewer tokens mean more Japanese fits in the context window.<\/p>\n<h3>Inside the GGUF File<\/h3>\n<p>File: <a href=\"https:\/\/huggingface.co\/bartowski\/Gryphe_Pantheon-Reasoning-26B-A4B-1.1-V2-GGUF\/blob\/main\/Gryphe_Pantheon-Reasoning-26B-A4B-1.1-V2-Q4_K_M.gguf\">Gryphe_Pantheon-Reasoning-26B-A4B-1.1-V2-Q4_K_M.gguf<\/a> (17.46GB, <code>Q4_K_M<\/code>). We read only the header (metadata) of the file, not the weights.<\/p>\n<div class=\"lmw-table-scroll\" tabindex=\"0\" style=\"overflow-x:auto;-webkit-overflow-scrolling:touch;max-width:100%;\">\n<table style=\"width:max-content;min-width:100%;border-collapse:collapse;\">\n<thead>\n<tr>\n<th>Item<\/th>\n<th>Value<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Architecture (as named in the GGUF)<\/td>\n<td><code>gemma4<\/code><\/td>\n<\/tr>\n<tr>\n<td>Maximum trained context length<\/td>\n<td>262,144 tokens<\/td>\n<\/tr>\n<tr>\n<td>Layers<\/td>\n<td>30<\/td>\n<\/tr>\n<tr>\n<td>Experts<\/td>\n<td>8 active out of 128<\/td>\n<\/tr>\n<tr>\n<td>Vocabulary size<\/td>\n<td>262,144<\/td>\n<\/tr>\n<tr>\n<td>Chat template<\/td>\n<td>Included (mentions tool calls, has a thinking switch)<\/td>\n<\/tr>\n<tr>\n<td>imatrix<\/td>\n<td>Used (<code>Gryphe_Pantheon-Reasoning-26B-A4B-1.1-V2-calibration-v6.txt<\/code>, 490 chunks)<\/td>\n<\/tr>\n<tr>\n<td>Weight types (share of parameters)<\/td>\n<td>Q4_K 50.8% \/ Q8_0 22.5% \/ Q5_0 16.0% \/ Q6_K 8.7% \/ other 2.0%<\/td>\n<\/tr>\n<tr>\n<td>Average bits per weight<\/td>\n<td>5.77 bits<\/td>\n<\/tr>\n<tr>\n<td>Embedding \/ output layer type<\/td>\n<td>Q8_0 \/ Q6_K<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>The quant name in the file name describes the file as a whole; in practice layers mix several types. The average bits per weight is the measured file data divided by the number of weights.<\/p>\n<h3>Running It on a CPU Only<\/h3>\n<div class=\"lmw-table-scroll\" tabindex=\"0\" style=\"overflow-x:auto;-webkit-overflow-scrolling:touch;max-width:100%;\">\n<table style=\"width:max-content;min-width:100%;border-collapse:collapse;\">\n<thead>\n<tr>\n<th>Item<\/th>\n<th>Result<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Prompt processing (512 tokens)<\/td>\n<td>9.6 tokens\/s<\/td>\n<\/tr>\n<tr>\n<td>Generation (128 tokens)<\/td>\n<td>6.2 tokens\/s<\/td>\n<\/tr>\n<tr>\n<td>Generation in Japanese characters<\/td>\n<td>about 11.0 characters\/s<\/td>\n<\/tr>\n<tr>\n<td>Peak memory (context 4,096 tokens)<\/td>\n<td>14.9GB<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>Conditions: Neoverse-N1, 3 threads, no GPU, llama.cpp b11223, <code>Q3_K_S<\/code> (12.26GB) from <a href=\"https:\/\/huggingface.co\/bartowski\/Gryphe_Pantheon-Reasoning-26B-A4B-1.1-V2-GGUF\">bartowski\/Gryphe_Pantheon-Reasoning-26B-A4B-1.1-V2-GGUF<\/a>, measured 2026-09-29 (JST). The 4-bit files did not fit our 13GB limit, so we measured the lower-bit <code>Q3_K_S<\/code> file; quality is lower than at 4 bits. Other models measured under the same conditions (closest in file size):<\/p>\n<div class=\"lmw-table-scroll\" tabindex=\"0\" style=\"overflow-x:auto;-webkit-overflow-scrolling:touch;max-width:100%;\">\n<p class=\"lmw-table-hint\" style=\"margin:0 0 4px;font-size:0.85em;opacity:0.7;\">\u2192 Scroll horizontally to see all columns<\/p>\n<table style=\"width:max-content;min-width:100%;border-collapse:collapse;\">\n<thead>\n<tr>\n<th>Model<\/th>\n<th>Quant<\/th>\n<th>File size<\/th>\n<th>Generation<\/th>\n<th>In Japanese<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/2026\/09\/15\/salience-27b-r6-gguf-2\/\">vectionlabs_Salience-27B-R6<\/a><\/td>\n<td><code>Q3_K_M<\/code><\/td>\n<td>12.48GB<\/td>\n<td>0.9 tokens\/s<\/td>\n<td>1.6 chars\/s<\/td>\n<\/tr>\n<tr>\n<td>Qwopus3.8-27B-Flash<\/td>\n<td><code>Q3_K_M<\/code><\/td>\n<td>12.57GB<\/td>\n<td>0.9 tokens\/s<\/td>\n<td>1.7 chars\/s<\/td>\n<\/tr>\n<tr>\n<td>K2-Horizon-MoVA-36B-A4B<\/td>\n<td><code>Q2_K<\/code><\/td>\n<td>12.64GB<\/td>\n<td>5.0 tokens\/s<\/td>\n<td>8.9 chars\/s<\/td>\n<\/tr>\n<tr>\n<td><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/2026\/09\/09\/nex-n25-mini-released\/\">nex-agi_Nex-N2.5-mini<\/a><\/td>\n<td><code>Q2_K<\/code><\/td>\n<td>12.89GB<\/td>\n<td>7.3 tokens\/s<\/td>\n<td>13.4 chars\/s<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>Peak memory includes the model file mapped into memory (mmap). A PC with a GPU will be much faster; these figures are a guide for CPU-only machines such as mini PCs and ARM boards.<\/p>\n<h3>Answers to Our Japanese Questions (Verbatim)<\/h3>\n<p>We ask every model the same five questions in Japanese under the conditions above (temperature 0, thinking turned off where the chat template allows it, up to 1024 tokens) and publish the answers unedited. We do not grade them; where a question has a single correct answer, we show it for comparison.<\/p>\n<p><strong>Summarization<\/strong><\/p>\n<blockquote>\n<p>\u6b21\u306e\u8a18\u4e8b\u30923\u6587\u3067\u8981\u7d04\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<p>\u307f\u3069\u308a\u5e02\u306f\u4eca\u5e74\u306e\u6625\u3001\u5e02\u5185\u306b\u4e09\u3064\u3042\u308b\u516c\u7acb\u56f3\u66f8\u9928\u306e\u3046\u3061\u6700\u3082\u53e4\u3044\u4e2d\u592e\u56f3\u66f8\u9928\u306e\u6539\u4fee\u3092\u7d42\u3048\u3001\u5341\u6708\u4e00\u65e5\u306b\u518d\u958b\u9928\u3057\u305f\u3002\u6539\u4fee\u306f\u7d04\u4e00\u5e74\u534a\u306b\u308f\u305f\u308a\u3001\u7dcf\u4e8b\u696d\u8cbb\u306f\u7d04\u5341\u4e8c\u5104\u5186\u3002\u3053\u306e\u3046\u3061\u7d04\u56db\u5104\u5186\u306f\u56fd\u306e\u88dc\u52a9\u91d1\u3067\u307e\u304b\u306a\u308f\u308c\u305f\u3002<\/p>\n<p>\u6700\u5927\u306e\u5909\u5316\u306f\u3001\u95b2\u89a7\u5e2d\u306e\u914d\u7f6e\u3067\u3042\u308b\u3002\u4ee5\u524d\u306f\u9928\u5185\u306e\u5ea7\u5e2d\u306e\u5927\u534a\u304c\u5b66\u7fd2\u7528\u306e\u673a\u3067\u3001\u8a66\u9a13\u671f\u9593\u306b\u306a\u308b\u3068\u4e2d\u9ad8\u751f\u3067\u57cb\u307e\u308a\u3001\u9ad8\u9f62\u306e\u5229\u7528\u8005\u3084\u5c0f\u3055\u306a\u5b50\u3069\u3082\u9023\u308c\u304c\u5ea7\u308c\u306a\u3044\u3068\u3044\u3046\u82e6\u60c5\u304c\u6bce\u5e74\u5bc4\u305b\u3089\u308c\u3066\u3044\u305f\u3002\u6539\u4fee\u5f8c\u306f\u5ea7\u5e2d\u6570\u3092\u767e\u4e8c\u5341\u5e2d\u304b\u3089\u4e8c\u767e\u5e2d\u306b\u5897\u3084\u3057\u305f\u3046\u3048\u3067\u3001\u5b66\u7fd2\u7528\u306e\u673a\u3092\u4e09\u968e\u306b\u307e\u3068\u3081\u3001\u4e00\u968e\u306f\u4f1a\u8a71\u304c\u3067\u304d\u308b\u300c\u306b\u304e\u308f\u3044\u30d5\u30ed\u30a2\u300d\u3001\u4e8c\u968e\u306f\u9759\u304b\u306b\u672c\u3092\u8aad\u3080\u300c\u95b2\u89a7\u30d5\u30ed\u30a2\u300d\u306b\u5206\u3051\u305f\u3002\u4e00\u968e\u306b\u306f\u4e88\u7d04\u5236\u306e\u30b0\u30eb\u30fc\u30d7\u5b66\u7fd2\u5ba4\u304c\u56db\u5ba4\u3068\u3001\u98f2\u307f\u7269\u3092\u6301\u3061\u8fbc\u3081\u308b\u30ab\u30d5\u30a7\u30b9\u30da\u30fc\u30b9\u3082\u8a2d\u3051\u3089\u308c\u305f\u3002<\/p>\n<p>\u8535\u66f8\u306e\u9762\u3067\u3082\u898b\u76f4\u3057\u304c\u9032\u3093\u3060\u3002\u8cb8\u51fa\u306e\u5c11\u306a\u3044\u53e4\u3044\u8cc7\u6599\u7d04\u4e09\u4e07\u518a\u3092\u5e02\u5185\u306e\u4ed6\u306e\u9928\u3084\u4fdd\u5b58\u66f8\u5eab\u306b\u79fb\u3057\u3001\u4ee3\u308f\u308a\u306b\u5b50\u3069\u3082\u5411\u3051\u306e\u7d75\u672c\u3068\u3001\u4ecb\u8b77\u30fb\u5b50\u80b2\u3066\u30fb\u4ed5\u4e8b\u63a2\u3057\u3068\u3044\u3063\u305f\u66ae\u3089\u3057\u306b\u95a2\u308f\u308b\u5b9f\u7528\u66f8\u3092\u7d04\u4e00\u4e07\u4e94\u5343\u518a\u5897\u3084\u3057\u305f\u3002\u96fb\u5b50\u66f8\u7c4d\u306e\u8cb8\u51fa\u30b5\u30fc\u30d3\u30b9\u3082\u59cb\u307e\u308a\u3001\u5229\u7528\u767b\u9332\u3092\u3059\u308c\u3070\u81ea\u5b85\u304b\u3089\u4e00\u5ea6\u306b\u4e09\u518a\u307e\u3067\u3001\u4e8c\u9031\u9593\u501f\u308a\u3089\u308c\u308b\u3002<\/p>\n<p>\u5efa\u7269\u305d\u306e\u3082\u306e\u306b\u3082\u624b\u304c\u5165\u3063\u305f\u3002\u7bc9\u56db\u5341\u5e74\u3092\u8d85\u3048\u3066\u3044\u305f\u7a7a\u8abf\u8a2d\u5099\u3092\u5165\u308c\u66ff\u3048\u3001\u5c4b\u4e0a\u306b\u306f\u592a\u967d\u5149\u30d1\u30cd\u30eb\u3092\u8a2d\u7f6e\u3057\u3066\u3001\u9928\u5185\u3067\u4f7f\u3046\u96fb\u529b\u306e\u7d04\u4e8c\u5272\u3092\u307e\u304b\u306a\u3048\u308b\u3088\u3046\u306b\u3057\u305f\u3002\u8eca\u3044\u3059\u306e\u5229\u7528\u8005\u304b\u3089\u8981\u671b\u306e\u591a\u304b\u3063\u305f\u30a8\u30ec\u30d9\u30fc\u30bf\u30fc\u306f\u4e00\u57fa\u304b\u3089\u4e8c\u57fa\u306b\u5897\u3048\u3001\u66f8\u67b6\u306e\u9593\u306e\u901a\u8def\u3082\u4ee5\u524d\u3088\u308a\u4e09\u5341\u30bb\u30f3\u30c1\u5e83\u3052\u3089\u308c\u305f\u3002\u5165\u53e3\u306b\u306f\u6bb5\u5dee\u306e\u306a\u3044\u30b9\u30ed\u30fc\u30d7\u304c\u65b0\u305f\u306b\u8a2d\u3051\u3089\u308c\u3001\u6388\u4e73\u5ba4\u3068\u591a\u76ee\u7684\u30c8\u30a4\u30ec\u3082\u5404\u968e\u306b\u4e00\u3064\u305a\u3064\u7f6e\u304b\u308c\u305f\u3002<\/p>\n<p>\u4e00\u65b9\u3067\u8ab2\u984c\u3082\u6b8b\u308b\u3002\u99d0\u8eca\u5834\u306f\u6539\u4fee\u524d\u3068\u540c\u3058\u56db\u5341\u53f0\u306e\u307e\u307e\u3067\u3001\u9031\u672b\u306b\u306f\u8fd1\u304f\u306e\u9053\u8def\u306b\u9806\u756a\u5f85\u3061\u306e\u8eca\u304c\u4e26\u3093\u3060\u3002\u5e02\u306f\u96a3\u63a5\u3059\u308b\u5e02\u6709\u5730\u3092\u81e8\u6642\u99d0\u8eca\u5834\u3068\u3057\u3066\u958b\u653e\u3057\u305f\u304c\u3001\u6052\u4e45\u7684\u306a\u5bfe\u7b56\u306f\u6c7a\u307e\u3063\u3066\u3044\u306a\u3044\u3002\u307e\u305f\u3001\u958b\u9928\u6642\u9593\u3092\u5e73\u65e5\u306e\u591c\u4e5d\u6642\u307e\u3067\u5ef6\u3070\u3057\u305f\u3053\u3068\u3067\u8077\u54e1\u306e\u8ca0\u62c5\u304c\u5897\u3048\u3066\u304a\u308a\u3001\u8077\u54e1\u56e3\u4f53\u306f\u4eba\u54e1\u306e\u8ffd\u52a0\u3092\u6c42\u3081\u3066\u3044\u308b\u3002<\/p>\n<p>\u5229\u7528\u8005\u306e\u53d7\u3051\u6b62\u3081\u306f\u304a\u304a\u3080\u306d\u597d\u610f\u7684\u3060\u3002\u9031\u306b\u4e8c\u5ea6\u3001\u5b6b\u3092\u9023\u308c\u3066\u6765\u308b\u3068\u3044\u3046\u4e03\u5341\u4ee3\u306e\u5973\u6027\u306f\u300c\u524d\u306f\u5b50\u3069\u3082\u304c\u58f0\u3092\u51fa\u3059\u3068\u5468\u308a\u306e\u76ee\u304c\u6c17\u306b\u306a\u3063\u305f\u304c\u3001\u4e00\u968e\u306a\u3089\u6c17\u517c\u306d\u306a\u304f\u7d75\u672c\u3092\u8aad\u3093\u3067\u3042\u3052\u3089\u308c\u308b\u300d\u3068\u8a71\u3059\u3002\u4e00\u65b9\u3001\u53d7\u9a13\u3092\u63a7\u3048\u305f\u9ad8\u6821\u751f\u306e\u4e2d\u306b\u306f\u300c\u5b66\u7fd2\u5e2d\u304c\u4e09\u968e\u3060\u3051\u306b\u306a\u308a\u3001\u5915\u65b9\u306f\u3059\u3050\u306b\u6e80\u5e2d\u306b\u306a\u308b\u300d\u3068\u4e0d\u6e80\u3092\u6f0f\u3089\u3059\u4eba\u3082\u3044\u308b\u3002\u56f3\u66f8\u9928\u306f\u3001\u5b66\u7fd2\u5e2d\u306e\u7a7a\u304d\u72b6\u6cc1\u3092\u30db\u30fc\u30e0\u30da\u30fc\u30b8\u3067\u78ba\u8a8d\u3067\u304d\u308b\u4ed5\u7d44\u307f\u3092\u5e74\u5185\u306b\u5c0e\u5165\u3059\u308b\u4e88\u5b9a\u3060\u3002<\/p>\n<p>\u518d\u958b\u9928\u306b\u5408\u308f\u305b\u3066\u3001\u50ac\u3057\u3082\u5897\u3048\u305f\u3002\u6bce\u9031\u571f\u66dc\u306e\u5348\u524d\u306b\u306f\u8aad\u307f\u805e\u304b\u305b\u4f1a\u3001\u6708\u306b\u4e00\u5ea6\u306f\u5730\u5143\u306e\u8fb2\u5bb6\u3084\u5546\u5e97\u4e3b\u3092\u8b1b\u5e2b\u306b\u62db\u304f\u300c\u307e\u3061\u306e\u5148\u751f\u300d\u8b1b\u5ea7\u304c\u958b\u304b\u308c\u308b\u3002\u5341\u4e00\u6708\u306b\u306f\u3001\u5e02\u5185\u306e\u4e2d\u5b66\u751f\u304c\u9078\u3093\u3060\u672c\u3092\u7d39\u4ecb\u3059\u308b\u5c55\u793a\u3082\u4e88\u5b9a\u3055\u308c\u3066\u3044\u308b\u3002<\/p>\n<p>\u9928\u9577\u306e\u5c71\u672c\u548c\u5b50\u3055\u3093\u306f\u300c\u672c\u3092\u501f\u308a\u308b\u5834\u6240\u304b\u3089\u3001\u4eba\u304c\u96c6\u307e\u3063\u3066\u904e\u3054\u3059\u5834\u6240\u3078\u5909\u3048\u305f\u304b\u3063\u305f\u3002\u518d\u958b\u9928\u304b\u3089\u306e\u4e00\u304b\u6708\u3067\u6765\u9928\u8005\u306f\u4ee5\u524d\u306e\u4e00\u30fb\u516b\u500d\u306b\u306a\u3063\u305f\u300d\u3068\u8a71\u3059\u3002\u5e02\u306f\u6765\u5e74\u5ea6\u3001\u6b8b\u308b\u4e8c\u3064\u306e\u56f3\u66f8\u9928\u306b\u3064\u3044\u3066\u3082\u5229\u7528\u8005\u3078\u306e\u805e\u304d\u53d6\u308a\u3092\u884c\u3044\u3001\u6539\u4fee\u306e\u5fc5\u8981\u6027\u3092\u691c\u8a0e\u3059\u308b\u65b9\u91dd\u3060\u3002<\/p>\n<\/blockquote>\n<p><em>(Summarize the following article in three sentences. (The article, about 1,200 Japanese characters, describes the renovation and reopening of a city&#8217;s central library: the budget, the new floor layout and seating, changes to the collection and e-book lending, building and accessibility work, remaining issues such as parking and staff workload, users&#8217; reactions, new events, and the city&#8217;s next steps.))<\/em><\/p>\n<pre><code class=\"language-text\">\u307f\u3069\u308a\u5e02\u306e\u4e2d\u592e\u56f3\u66f8\u9928\u306f\u3001\u7d0412\u5104\u5186\u3092\u6295\u3058\u305f\u6539\u4fee\u3092\u7d4c\u306610\u6708\u306b\u518d\u958b\u9928\u3057\u3001\u5ea7\u5e2d\u306e\u5897\u8a2d\u3084\u30d5\u30ed\u30a2\u5206\u3051\u3001\u8535\u66f8\u306e\u898b\u76f4\u3057\u3001\u30d0\u30ea\u30a2\u30d5\u30ea\u30fc\u5316\u306a\u3069\u304c\u884c\u308f\u308c\u307e\u3057\u305f\u3002\n\n\u300c\u4eba\u304c\u96c6\u307e\u3063\u3066\u904e\u3054\u3059\u5834\u6240\u300d\u3078\u306e\u8ee2\u63db\u306b\u3088\u308a\u6765\u9928\u8005\u306f\u5927\u5e45\u306b\u5897\u52a0\u3057\u307e\u3057\u305f\u304c\u3001\u99d0\u8eca\u5834\u4e0d\u8db3\u3084\u8077\u54e1\u306e\u8ca0\u62c5\u5897\u3001\u5b66\u7fd2\u5e2d\u306e\u6df7\u96d1\u3068\u3044\u3063\u305f\u8ab2\u984c\u3082\u6d6e\u304d\u5f6b\u308a\u306b\u306a\u3063\u3066\u3044\u307e\u3059\u3002\n\n\u5e02\u306f\u4eca\u5f8c\u3001\u30db\u30fc\u30e0\u30da\u30fc\u30b8\u3067\u306e\u7a7a\u5e2d\u78ba\u8a8d\u30b7\u30b9\u30c6\u30e0\u306e\u5c0e\u5165\u3092\u9032\u3081\u308b\u3068\u3068\u3082\u306b\u3001\u6b8b\u308b2\u3064\u306e\u56f3\u66f8\u9928\u306b\u3064\u3044\u3066\u3082\u6539\u4fee\u306e\u5fc5\u8981\u6027\u3092\u691c\u8a0e\u3057\u3066\u3044\u304f\u65b9\u91dd\u3067\u3059\u3002\n<\/code><\/pre>\n<p><strong>Formal business email<\/strong><\/p>\n<blockquote>\n<p>\u53d6\u5f15\u5148\u306e\u62c5\u5f53\u8005\u306b\u3001\u6765\u9031\u706b\u66dc\u65e5\u306e\u6253\u3061\u5408\u308f\u305b\u3092\u6c34\u66dc\u65e5\u306b\u5909\u66f4\u3057\u3066\u307b\u3057\u3044\u3068\u304a\u9858\u3044\u3059\u308b\u30e1\u30fc\u30eb\u3092\u3001\u4e01\u5be7\u306a\u656c\u8a9e\u3067\u66f8\u3044\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<\/blockquote>\n<p><em>(Write an email in polite Japanese (keigo) asking a client&#8217;s contact person to move next Tuesday&#8217;s meeting to Wednesday.)<\/em><\/p>\n<pre><code class=\"language-text\">\u53d6\u5f15\u5148\u3078\u306e\u65e5\u7a0b\u5909\u66f4\u306e\u304a\u9858\u3044\u306f\u3001**\u300c\u7533\u3057\u8a33\u306a\u3055\u3092\u4f1d\u3048\u3064\u3064\u3001\u4ee3\u66ff\u6848\u3092\u63d0\u793a\u3059\u308b\u300d**\u3053\u3068\u304c\u30dd\u30a4\u30f3\u30c8\u3067\u3059\u3002\u76f8\u624b\u306e\u4e88\u5b9a\u3092\u5c0a\u91cd\u3057\u3001\u7121\u7406\u5f37\u3044\u3057\u306a\u3044\u4e01\u5be7\u306a\u8868\u73fe\u304c\u6c42\u3081\u3089\u308c\u307e\u3059\u3002\n\n\u72b6\u6cc1\u306b\u5408\u308f\u305b\u3066\u4f7f\u3044\u5206\u3051\u3089\u308c\u308b\u3088\u3046\u30012\u3064\u306e\u30d1\u30bf\u30fc\u30f3\u3092\u4f5c\u6210\u3057\u307e\u3057\u305f\u3002\n\n---\n\n### \u30d1\u30bf\u30fc\u30f31\uff1a\u6a19\u6e96\u7684\u30fb\u4e01\u5be7\u306a\u8868\u73fe\uff08\u6700\u3082\u6c4e\u7528\u6027\u304c\u9ad8\u3044\uff09\n\u7406\u7531\u3092\u300c\u6025\u306a\u4e88\u5b9a\u304c\u5165\u3063\u305f\u305f\u3081\u300d\u3068\u307c\u304b\u3057\u3064\u3064\u3001\u8aa0\u5b9f\u306b\u8b1d\u7f6a\u3059\u308b\u69cb\u6210\u3067\u3059\u3002\n\n**\u4ef6\u540d\uff1a** \u3010\u65e5\u7a0b\u5909\u66f4\u306e\u304a\u9858\u3044\u3011\u3007\u6708\u3007\u65e5\uff08\u706b\uff09\u306e\u304a\u6253\u3061\u5408\u308f\u305b\u306b\u3064\u304d\u307e\u3057\u3066\n\n**\u672c\u6587\uff1a**\n\u682a\u5f0f\u4f1a\u793e\u3007\u3007\n[\u76f8\u624b\u306e\u90e8\u7f72\u540d]\u3000[\u76f8\u624b\u306e\u5f79\u8077]\n[\u76f8\u624b\u306e\u6c0f\u540d] \u69d8\n\n\u3044\u3064\u3082\u5927\u5909\u304a\u4e16\u8a71\u306b\u306a\u3063\u3066\u304a\u308a\u307e\u3059\u3002\n\u682a\u5f0f\u4f1a\u793e\u3007\u3007\u306e[\u81ea\u5206\u306e\u6c0f\u540d]\u3067\u3054\u3056\u3044\u307e\u3059\u3002\n\n\u6765\u9031\u3007\u6708\u3007\u65e5\uff08\u706b\uff09\u3007\u6642\u3088\u308a\u4e88\u5b9a\u3057\u3066\u304a\u308a\u307e\u3059\u304a\u6253\u3061\u5408\u308f\u305b\u306b\u3064\u304d\u307e\u3057\u3066\u3001\n\u8aa0\u306b\u52dd\u624b\u306a\u304c\u3089\u3001\u65e5\u7a0b\u306e\u3054\u5909\u66f4\u3092\u304a\u9858\u3044\u3057\u305f\u304f\u3054\u9023\u7d61\u5dee\u3057\u4e0a\u3052\u307e\u3057\u305f\u3002\n\n\u3053\u3061\u3089\u306e\u4e0d\u624b\u969b\u306b\u3088\u308a\u3001\u5f53\u65e5\u3069\u3046\u3057\u3066\u3082\u5916\u305b\u306a\u3044\u6025\u7528\u304c\u5165\u3063\u3066\u3057\u307e\u3044\u3001\n\u304a\u7d04\u675f\u306e\u304a\u6642\u9593\u306b\u4f3a\u3046\u3053\u3068\u304c\u96e3\u3057\u304f\u306a\u3063\u3066\u3057\u307e\u3044\u307e\u3057\u305f\u3002\n\n\u76f4\u524d\u306e\u304a\u9858\u3044\u3068\u306a\u308a\u3001\u591a\u5927\u306a\u308b\u3054\u8ff7\u60d1\u3092\u304a\u304b\u3051\u3057\u307e\u3059\u3053\u3068\u3092\u6df1\u304f\u304a\u8a6b\u3073\u7533\u3057\u4e0a\u3052\u307e\u3059\u3002\n\n\u3082\u3057\u3088\u308d\u3057\u3051\u308c\u3070\u3001\u4ee5\u4e0b\u306e\u65e5\u7a0b\u306b\u3066\u6539\u3081\u3066\u8abf\u6574\u3055\u305b\u3066\u3044\u305f\u3060\u3051\u306a\u3044\u3067\u3057\u3087\u3046\u304b\u3002\n\n\u3010\u5909\u66f4\u5f8c\u306e\u5019\u88dc\u65e5\u6642\u3011\n\u30fb\u3007\u6708\u3007\u65e5\uff08\u6c34\uff0913:00\uff5e15:00\n\u30fb\u3007\u6708\u3007\u65e5\uff08\u6c34\uff0915:00\uff5e17:00\n\u30fb\u3007\u6708\u3007\u65e5\uff08\u6c34\uff09\u7d42\u65e5\u8abf\u6574\u53ef\u80fd\n\n\u4e0a\u8a18\u65e5\u7a0b\u3067\u3054\u90fd\u5408\u306e\u3064\u304f\u304a\u6642\u9593\u304c\u3054\u3056\u3044\u307e\u3057\u305f\u3089\u3001\u3054\u6559\u793a\u3044\u305f\u3060\u3051\u307e\u3059\u3068\u5e78\u3044\u3067\u3059\u3002\n\u3082\u3057\u4e0a\u8a18\u3067\u306e\u8abf\u6574\u304c\u96e3\u3057\u3044\u5834\u5408\u306f\u3001\u6539\u3081\u3066\u5225\u65e5\u7a0b\u3092\u63d0\u793a\u3055\u305b\u3066\u3044\u305f\u3060\u304d\u307e\u3059\u3002\n\n\u304a\u5fd9\u3057\u3044\u4e2d\u3001\u304a\u624b\u6570\u3092\u304a\u304b\u3051\u3057\u3066\u3057\u307e\u3044\u5927\u5909\u7533\u3057\u8a33\u3054\u3056\u3044\u307e\u305b\u3093\u3002\n\u4f55\u5352\u3054\u691c\u8a0e\u306e\u307b\u3069\u3001\u3088\u308d\u3057\u304f\u304a\u9858\u3044\u7533\u3057\u4e0a\u3052\u307e\u3059\u3002\n\n--------------------------------------------------\n\uff08\u7f72\u540d\uff09\n--------------------------------------------------\n\n---\n\n### \u30d1\u30bf\u30fc\u30f32\uff1a\u3088\u308a\u7533\u3057\u8a33\u306a\u3055\u3092\u5f37\u8abf\u3059\u308b\u5834\u5408\uff08\u76ee\u4e0a\u306e\u76f8\u624b\u3084\u91cd\u8981\u306a\u6848\u4ef6\uff09\n\u300c\u3053\u3061\u3089\u306e\u90fd\u5408\u3067\u300d\u300c\u3054\u591a\u5fd9\u306e\u6298\u300d\u3068\u3044\u3063\u305f\u8a00\u8449\u3092\u4f7f\u3044\u3001\u3088\u308a\u4f4e\u59ff\u52e2\u306a\u5370\u8c61\u3092\u4e0e\u3048\u307e\u3059.\n\n**\u4ef6\u540d\uff1a** \u304a\u6253\u3061\u5408\u308f\u305b\u65e5\u7a0b\u5909\u66f4\u306e\u304a\u9858\u3044\uff08\u682a\u5f0f\u4f1a\u793e\u3007\u3007 [\u81ea\u5206\u306e\u6c0f\u540d]\uff09\n\n**\u672c\u6587\uff1a**\n\u682a\u5f0f\u4f1a\u793e\u3007\u3007\n[\u76f8\u624b\u306e\u6c0f\u540d] \u69d8\n\n\u3044\u3064\u3082\u683c\u5225\u306e\u3054\u9ad8\u914d\u3092\u8cdc\u308a\u3001\u539a\u304f\u5fa1\u793c\u7533\u3057\u4e0a\u3052\u307e\u3059\u3002\n\u682a\u5f0f\u4f1a\u793e\u3007\u3007\u306e[\u81ea\u5206\u306e\u6c0f\u540d]\u3067\u3054\u3056\u3044\u307e\u3059\u3002\n\n\u6765\u9031\u706b\u66dc\u65e5\u306b\u4e88\u5b9a\u3057\u3066\u304a\u308a\u307e\u3059\u304a\u6253\u3061\u5408\u308f\u305b\u306b\u3064\u304d\u307e\u3057\u3066\u3001\n\u3053\u3061\u3089\u306e\u52dd\u624b\u306a\u90fd\u5408\u306b\u3088\u308a\u3001\u65e5\u7a0b\u3092\u6c34\u66dc\u65e5\u306b\u5909\u66f4\u3055\u305b\u3066\u3044\u305f\u3060\u3051\u306a\u3044\u304b\u3068\u304a\u4f3a\u3044\u3057\u305f\u304f\u3001\u3054\u9023\u7d61\u3044\u305f\u3057\u307e\u3057\u305f\u3002\n\n\u672c\u6765\u3067\u3042\u308c\u3070\u4e88\u5b9a\u901a\u308a\u304a\u4f3a\u3044\u3059\u3079\u304d\u3068\u3053\u308d\u3001\u3053\u3061\u3089\u306e\u4e0d\u624b\u969b\u306b\u3088\u308a\n\u3054\u8ff7\u60d1\u3092\u304a\u304b\u3051\u3059\u308b\u3053\u3068\u3068\u306a\u308a\u3001\u8aa0\u306b\u7533\u3057\u8a33\u3054\u3056\u3044\u307e\u305b\u3093\u3002\n\n\u3064\u304d\u307e\u3057\u3066\u306f\u3001\u3082\u3057\u5dee\u3057\u652f\u3048\u306a\u3051\u308c\u3070\u3001\u4ee5\u4e0b\u306e\u65e5\u7a0b\u306b\u3066\u518d\u8abf\u6574\u3092\u304a\u9858\u3044\u3067\u304d\u307e\u3059\u3067\u3057\u3087\u3046\u304b\u3002\n\n\u3010\u5019\u88dc\u65e5\u6642\u3011\n\u30fb\u3007\u6708\u3007\u65e5\uff08\u6c34\uff0910:00\uff5e12:00\n\u30fb\u3007\u6708\u3007\u65e5\uff08\u6c34\uff0914:00\uff5e16:00\n\n\u3054\u591a\u5fd9\u306e\u6298\u3001\u591a\u5927\u306a\u308b\u3054\u4e0d\u4fbf\u3092\u304a\u304b\u3051\u3044\u305f\u3057\u307e\u3059\u3053\u3068\u3001\u91cd\u306d\u3066\u304a\u8a6b\u3073\u7533\u3057\u4e0a\u3052\u307e\u3059\u3002\n\u52dd\u624b\u306a\u304a\u9858\u3044\u3067\u306f\u3054\u3056\u3044\u307e\u3059\u304c\u3001\u3054\u691c\u8a0e\u3044\u305f\u3060\u3051\u307e\u3059\u3068\u5e78\u3044\u3067\u3059\u3002\n\n\u4f55\u5352\u3088\u308d\u3057\u304f\u304a\u9858\u3044\u7533\u3057\u4e0a\u3052\u307e\u3059\u3002\n\n--------------------------------------------------\n\uff08\u7f72\u540d\uff09\n--------------------------------------------------\n\n---\n\n### \u9001\u4fe1\u6642\u306e\u30dd\u30a4\u30f3\u30c8\u30fb\u6ce8\u610f\u70b9\n\n1.  **\u4ef6\u540d\u306f\u5206\u304b\u308a\u3084\u3059\u304f\uff1a** \u76f8\u624b\u304c\u30e1\u30fc\u30eb\u4e00\u89a7\u3092\u898b\u305f\u3060\u3051\u3067\u300c\u65e5\u7a0b\u5909\u66f4\u306e\u4ef6\u3060\u300d\u3068\u5206\u304b\u308b\u3088\u3046\u306b\u3057\u307e\u3059\u3002\n2.  **\u4ee3\u66ff\u6848\uff08\u5019\u88dc\u65e5\uff09\u3092\u5fc5\u305a\u63d0\u793a\u3059\u308b\uff1a** \u300c\u6c34\u66dc\u65e5\u306b\u5909\u66f4\u3057\u3066\u307b\u3057\u3044\u300d\u3068\u3060\u3051\u4f1d\u3048\u308b\u3068\u3001\u76f8\u624b\u306b\u518d\u5ea6\u65e5\u7a0b\u3092\u8003\u3048\u3055\u305b\u308b\u624b\u9593\u3092\u4e0e\u3048\u3066\u3057\u307e\u3044\u307e\u3059\u3002\u3053\u3061\u3089\u304b\u3089\u300c\u6c34\u66dc\u65e5\u306e\u3007\u6642\u301c\u3007\u6642\u300d\u3068\u5177\u4f53\u7684\u306b\u63d0\u793a\u3059\u308b\u306e\u304c\u30de\u30ca\u30fc\u3067\u3059\u3002\n3.  **\u7406\u7531\u306f\u7c21\u6f54\u306b\uff1a** \u8a73\u7d30\u3059\u304e\u308b\u7406\u7531\u306f\u304b\u3048\u3063\u3066\u8a00\u3044\u8a33\u304c\u307e\u3057\u304f\u805e\u3053\u3048\u308b\u3053\u3068\u304c\u3042\u308a\u307e\u3059\u3002\u300c\u6025\u7528\u304c\u5165\u3063\u305f\u300d\u300c\u3084\u3080\u3092\u5f97\u306a\u3044\u4e8b\u60c5\u306b\u3088\u308a\u300d\u3068\u3044\u3063\u305f\u8868\u73fe\u3067\u5341\u5206\u3067\u3059\u3002\n4.  **\u65e9\u3081\u306b\u9001\u308b\uff1a** \u65e5\u7a0b\u5909\u66f4\u306e\u304a\u9858\u3044\u306f\u3001\u5224\u660e\u3057\u305f\u6642\u70b9\u3067\u3059\u3050\u306b\u9001\u308b\u306e\u304c\u9244\u5247\u3067\u3059\u3002\n<\/code><\/pre>\n<p><strong>Word problem<\/strong><\/p>\n<blockquote>\n<p>\u308a\u3093\u3054\u304c1\u500b120\u5186\u3001\u307f\u304b\u3093\u304c1\u500b45\u5186\u3067\u3059\u3002\u308a\u3093\u3054\u30923\u500b\u3068\u307f\u304b\u3093\u30928\u500b\u8cb7\u3063\u3066\u30011,000\u5186\u672d\u3067\u6255\u3044\u307e\u3057\u305f\u3002\u304a\u3064\u308a\u306f\u3044\u304f\u3089\u3067\u3059\u304b\u3002\u8003\u3048\u65b9\u3082\u793a\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<\/blockquote>\n<p><em>(Apples cost 120 yen each and mandarins cost 45 yen each. You buy 3 apples and 8 mandarins and pay with a 1,000-yen bill. How much change do you get? Show your reasoning.)<\/em><\/p>\n<pre><code class=\"language-text\">\u304a\u3064\u308a\u306f **380\u5186** \u3067\u3059\u3002\n\n\u8003\u3048\u65b9\u306f\u4ee5\u4e0b\u306e\u901a\u308a\u3067\u3059\u3002\n\n### 1. \u308a\u3093\u3054\u306e\u4ee3\u91d1\u3092\u8a08\u7b97\u3059\u308b\n\u308a\u3093\u3054\u306f1\u500b120\u5186\u30673\u500b\u8cb7\u3046\u306e\u3067\u3001\n$120 \\times 3 = 360$\uff08\u5186\uff09\n\n### 2. \u307f\u304b\u3093\u306e\u4ee3\u91d1\u3092\u8a08\u7b97\u3059\u308b\n\u307f\u304b\u3093\u306f1\u500b45\u5186\u30678\u500b\u8cb7\u3046\u306e\u3067\u3001\n$45 \\times 8 = 360$\uff08\u5186\uff09\n\n### 3. \u5408\u8a08\u91d1\u984d\u3092\u8a08\u7b97\u3059\u308b\n\u308a\u3093\u3054\u3068\u307f\u304b\u3093\u306e\u4ee3\u91d1\u3092\u5408\u308f\u305b\u307e\u3059\u3002\n$360 + 360 = 720$\uff08\u5186\uff09\n\n### 4. \u304a\u3064\u308a\u3092\u8a08\u7b97\u3059\u308b\n1,000\u5186\u304b\u3089\u5408\u8a08\u91d1\u984d\u3092\u5f15\u304d\u307e\u3059\u3002\n$1000 - 720 = 280$\uff08\u5186\uff09\n\n---\n**\u3010\u8a02\u6b63\u3068\u304a\u8a6b\u3073\u3011**\n\u7533\u3057\u8a33\u3042\u308a\u307e\u305b\u3093\u3001\u8a08\u7b97\u306b\u8aa4\u308a\u304c\u3042\u308a\u307e\u3057\u305f\u3002\u6b63\u3057\u304f\u306f\u4ee5\u4e0b\u306e\u901a\u308a\u3067\u3059\u3002\n\n1. \u308a\u3093\u3054\uff1a$120 \\times 3 = 360$\u5186\n2. \u307f\u304b\u3093\uff1a$45 \\times 8 = 360$\u5186\n3. \u5408\u8a08\uff1a$360 + 360 = 720$\u5186\n4. \u304a\u3064\u308a\uff1a$1000 - 720 = 280$\u5186\n\n\u6b63\u89e3\u306f **280\u5186** \u3067\u3059\u3002\n<\/code><\/pre>\n<p>Reference: The correct answer is 280 yen (120\u00d73 = 360, 45\u00d78 = 360, 1,000 \u2212 720 = 280).<\/p>\n<p><strong>Knowledge<\/strong><\/p>\n<blockquote>\n<p>\u65e5\u672c\u306e\u90fd\u9053\u5e9c\u770c\u306e\u3046\u3061\u3001\u6d77\u306b\u9762\u3057\u3066\u3044\u306a\u3044\u770c\u3092\u3059\u3079\u3066\u6319\u3052\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<\/blockquote>\n<p><em>(List all of Japan&#8217;s prefectures that do not border the sea.)<\/em><\/p>\n<pre><code class=\"language-text\">\u65e5\u672c\u306e\u90fd\u9053\u5e9c\u770c\u306e\u3046\u3061\u3001\u6d77\u306b\u9762\u3057\u3066\u3044\u306a\u3044\uff08\u5185\u9678\u770c\uff09\u306f\u4ee5\u4e0b\u306e**31**\u770c\u3067\u3059\u3002\n\n**\u3010\u5317\u6d77\u9053\u30fb\u6771\u5317\u3011**\n*   \u5ca9\u624b\u770c\n*   \u79cb\u7530\u770c\n*   \u5c71\u5f62\u770c\n*   \u6803\u6728\u770c\n*   \u7fa4\u99ac\u770c\n\n**\u3010\u95a2\u6771\u3011**\n*   \u57fc\u7389\u770c\n*   \u3055\u3044\u305f\u307e\u5e02\uff08\u203b\u57fc\u7389\u770c\uff09\n*   \uff08\u203b\u57fc\u7389\u770c\u306f\u4e0a\u8a18\u306b\u542b\u307e\u308c\u307e\u3059\uff09\n\n**\u3010\u4e2d\u90e8\u3011**\n*   \u9577\u91ce\u770c\n*   \u5c90\u961c\u770c\n*   \u9759\u5ca1\u770c\uff08\u203b\u9759\u5ca1\u770c\u306f\u6d77\u306b\u9762\u3057\u3066\u3044\u307e\u3059\u3002\u5931\u793c\u3057\u307e\u3057\u305f\u3002\u6b63\u3057\u304f\u306f\u4ee5\u4e0b\u306e\u901a\u308a\u3067\u3059\uff09\n\n---\n**\u3010\u6b63\u78ba\u306a\u30ea\u30b9\u30c8\uff08\u5185\u9678\u770c31\u770c\uff09\u3011**\n\n**\u3010\u5317\u6d77\u9053\u30fb\u6771\u5317\u3011**\n1. \u5ca9\u624b\u770c\n2. \u79cb\u7530\u770c\n3. \u5c71\u5f62\u770c\n4. \u6803\u6728\u770c\n5. \u7fa4\u99ac\u770c\n\n**\u3010\u95a2\u6771\u3011**\n6. \u57fc\u7389\u770c\n\n**\u3010\u4e2d\u90e8\u3011**\n7. \u9577\u91ce\u770c\n8. \u5c90\u961c\u770c\n\n**\u3010\u8fd1\u757f\u3011**\n9. \u6ecb\u8cc0\u770c\n10. \u4eac\u90fd\u5e9c\n11. \u5948\u826f\u770c\n\n**\u3010\u4e2d\u56fd\u30fb\u56db\u56fd\u3011**\n12. \u9ce5\u53d6\u770c\uff08\u203b\u9ce5\u53d6\u770c\u306f\u65e5\u672c\u6d77\u306b\u9762\u3057\u3066\u3044\u307e\u3059\u3002\u5931\u793c\u3057\u307e\u3057\u305f\u3002\u5185\u9678\u770c\u306f\u4ee5\u4e0b\u306e\u901a\u308a\u3067\u3059\uff09\n\n---\n**\u3010\u6539\u3081\u3066\u3001\u6d77\u306b\u9762\u3057\u3066\u3044\u306a\u3044\u770c\uff08\u5185\u9678\u770c\uff09\u306e\u5168\u30ea\u30b9\u30c8\u3011**\n\n1.  **\u6803\u6728\u770c**\n2.  **\u7fa4\u99ac\u770c**\n3.  **\u57fc\u7389\u770c**\n4.  **\u9577\u91ce\u770c**\n5.  **\u5c90\u961c\u770c**\n6.  **\u6ecb\u8cc0\u770c**\n7.  **\u4eac\u90fd\u5e9c**\n8.  **\u5948\u826f\u770c**\n9.  **\u5ca1\u5c71\u770c**\uff08\u203b\u5ca1\u5c71\u770c\u306f\u702c\u6238\u5185\u6d77\u306b\u9762\u3057\u3066\u3044\u307e\u3059\u3002\u5931\u793c\u3057\u307e\u3057\u305f\uff09\n\n---\n**\u3010\u5927\u5909\u5931\u793c\u3044\u305f\u3057\u307e\u3057\u305f\u3002\u6b63\u78ba\u306a\u5185\u9678\u770c\uff08\u6d77\u306b\u9762\u3057\u3066\u3044\u306a\u3044\u770c\uff09\u306f\u4ee5\u4e0b\u306e31\u770c\u3067\u3059\u3011**\n\n**\u3010\u6771\u5317\u3011**\n1. \u5ca9\u624b\u770c\uff08\u203b\u5ca9\u624b\u770c\u306f\u592a\u5e73\u6d0b\u306b\u9762\u3057\u3066\u3044\u307e\u3059\uff09\n\n**\u3010\u6b63\u3057\u3044\u5185\u9678\u770c\u30ea\u30b9\u30c8\uff08\u6d77\u306b\u9762\u3057\u3066\u3044\u306a\u3044\u770c\uff09\u3011**\n1. **\u6803\u6728\u770c**\n2. **\u7fa4\u99ac\u770c**\n3. **\u57fc\u7389\u770c**\n4. **\u9577\u91ce\u770c**\n5. **\u5c90\u961c\u770c**\n6. **\u6ecb\u8cc0\u770c**\n7. **\u4eac\u90fd\u5e9c**\n8. **\u5948\u826f\u770c**\n9. **\u5c71\u68a8\u770c**\n10. **\u798f\u4e95\u770c**\uff08\u203b\u798f\u4e95\u770c\u306f\u65e5\u672c\u6d77\u306b\u9762\u3057\u3066\u3044\u307e\u3059\uff09\n\n---\n**\u3010\u6700\u7d42\u56de\u7b54\uff1a\u6d77\u306b\u9762\u3057\u3066\u3044\u306a\u3044\u770c\uff08\u5185\u9678\u770c\uff09\u3011**\n\u6df7\u4e71\u3055\u305b\u3066\u3057\u307e\u3044\u7533\u3057\u8a33\u3042\u308a\u307e\u305b\u3093\u3002\u6b63\u78ba\u306a\u5185\u9678\u770c\u306f\u4ee5\u4e0b\u306e**31\u770c**\u3067\u3059\u3002\n\n1. **\u6803\u6728\u770c**\n2. **\u7fa4\u99ac\u770c**\n3. **\u57fc\u7389\u770c**\n4. **\u9577\u91ce\u770c**\n5. **\u5c90\u961c\u770c**\n6. **\u5c71\u68a8\u770c**\n7. **\u6ecb\u8cc0\u770c**\n8. **\u4eac\u90fd\u5e9c**\n9. **\u5948\u826f\u770c**\n10. **\u5ca1\u5c71\u770c**\uff08\u203b\u5ca1\u5c71\u770c\u306f\u702c\u6238\u5185\u6d77\u306b\u9762\u3057\u3066\u3044\u307e\u3059\uff09\n\n**\u3010\u6b63\u3057\u3044\u5185\u9678\u770c\u4e00\u89a7\uff0831\u770c\uff09\u3011**\n1. \u6803\u6728\u770c\n2. \u7fa4\u99ac\u770c\n3. \u57fc\u7389\u770c\n4. \u9577\u91ce\u770c\n5. \u5c90\u961c\u770c\n6. \u5c71\u68a8\u770c\n7. \u6ecb\u8cc0\u770c\n8. \u4eac\u90fd\u5e9c\n9. \u5948\u826f\u770c\n10. \u5ca1\u5c71\u770c\uff08\u203b\u5ca1\u5c71\u770c\u306f\u6d77\u306b\u9762\u3057\u3066\u3044\u307e\u3059\uff09\n\n**\u3010\u7d50\u8ad6\uff1a\u6d77\u306b\u9762\u3057\u3066\u3044\u306a\u3044\u770c\uff08\u5185\u9678\u770c\uff09\u3011**\n1. **\u6803\u6728\u770c**\n2. **\u7fa4\u99ac\u770c**\n3. **\u57fc\u7389\u770c**\n4. **\u9577\u91ce\u770c**\n5. **\u5c90\u961c\u770c**\n6. **\u5c71\u68a8\u770c**\n7. **\u6ecb\u8cc0\u770c**\n8. **\u4eac\u90fd\u5e9c**\n9. **\u5948\u826f\u770c**\n\n\uff08\u203b\u3053\u308c\u4ee5\u5916\u306e\u770c\u306f\u3059\u3079\u3066\u6d77\u306b\u9762\u3057\u3066\u3044\u307e\u3059\uff09\n<\/code><\/pre>\n<p>Reference: The correct answer is eight prefectures: Tochigi, Gunma, Saitama, Yamanashi, Nagano, Gifu, Shiga and Nara.<\/p>\n<p><strong>Constrained writing<\/strong><\/p>\n<blockquote>\n<p>\u300c\u6625\u300d\u3092\u30c6\u30fc\u30de\u306b\u3057\u305f\u4ff3\u53e5\u30923\u3064\u3001\u4e94\u30fb\u4e03\u30fb\u4e94\u306e\u97f3\u6570\u3092\u5b88\u3063\u3066\u4f5c\u3063\u3066\u304f\u3060\u3055\u3044\u3002\u305d\u308c\u305e\u308c\u306b\u4e00\u8a00\u306e\u8aac\u660e\u3092\u4ed8\u3051\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<\/blockquote>\n<p><em>(Write three haiku on the theme of spring, keeping the 5-7-5 syllable pattern, each with a one-line explanation.)<\/em><\/p>\n<pre><code class=\"language-text\">\u300c\u6625\u300d\u3092\u30c6\u30fc\u30de\u306b\u3057\u305f\u4ff3\u53e5\u30923\u3064\u3001\u305d\u308c\u305e\u308c\u7570\u306a\u308b\u60c5\u666f\u3067\u8a60\u307f\u307e\u3057\u305f\u3002\n\n**1. \u967d\u3060\u307e\u308a\u306b\u3000\u732b\u306e\u4e38\u307e\u308b\u3000\u663c\u4e0b\u304c\u308a**\n\uff08\u3072\u3060\u307e\u308a\u306b\u3000\u306d\u3053\u306e\u307e\u308b\u307e\u308b\u3000\u3072\u308b\u3055\u304c\u308a\uff09\n\u3010\u8aac\u660e\u3011\u6625\u306e\u6696\u304b\u306a\u65e5\u5dee\u3057\u306e\u4e2d\u3067\u3001\u732b\u304c\u6c17\u6301\u3061\u3088\u3055\u305d\u3046\u306b\u4e38\u304f\u306a\u3063\u3066\u7720\u3063\u3066\u3044\u308b\u3001\u306e\u3069\u304b\u306a\u5348\u5f8c\u306e\u98a8\u666f\u3092\u8a60\u307f\u307e\u3057\u305f\u3002\n\n**2. \u98a8\u5149\u308a\u3000\u857e\u307b\u3053\u308d\u3076\u3000\u82b1\u306e\u9053**\n\uff08\u304b\u305c\u3072\u304b\u308a\u3000\u3064\u307c\u307f\u307b\u3053\u308d\u3076\u3000\u306f\u306a\u306e\u307e\u3061\uff09\n\u3010\u8aac\u660e\u3011\u6625\u7279\u6709\u306e\u30ad\u30e9\u30ad\u30e9\u3068\u3057\u305f\u5149\u3092\u611f\u3058\u308b\u98a8\u304c\u5439\u304d\u3001\u9053\u6cbf\u3044\u306e\u82b1\u306e\u857e\u304c\u4eca\u306b\u3082\u54b2\u304d\u305d\u3046\u306b\u81a8\u3089\u3093\u3067\u3044\u308b\u69d8\u5b50\u3092\u8868\u73fe\u3057\u307e\u3057\u305f\u3002\n\n**3. \u8776\u821e\u3044\u3066\u3000\u6625\u306e\u9999\u6e80\u3061\u308b\u3000\u5ead\u306e\u9685**\n\uff08\u3061\u3087\u3046\u307e\u3044\u3066\u3000\u306f\u308b\u306e\u304b\u307f\u3061\u308b\u3000\u306b\u308f\u306e\u3059\u307f\uff09\n\u3010\u8aac\u660e\u3011\u5ead\u306e\u7247\u9685\u3067\u8776\u304c\u821e\u3044\u3001\u6625\u306e\u82b1\u3005\u306e\u9999\u308a\u304c\u3075\u308f\u308a\u3068\u6f02\u3063\u3066\u304f\u308b\u3001\u751f\u547d\u306e\u606f\u5439\u3092\u611f\u3058\u308b\u77ac\u9593\u3092\u8a60\u307f\u307e\u3057\u305f\u3002\n<\/code><\/pre>\n<p><!-- \/lmw:lab --><\/p>\n<p><!-- lmw:peers --><\/p>\n<h2>Recent Models in the Same Size Class<\/h2>\n<p><em>Models with <\/em><em>15\u201340B<\/em><em> parameters that Local Model Watch covered recently, listed by code from our article log for comparison. VRAM tiers are this site&#8217;s estimates; licenses are as stated on the model cards.<\/em><\/p>\n<div class=\"lmw-table-scroll\" tabindex=\"0\" style=\"overflow-x:auto;-webkit-overflow-scrolling:touch;max-width:100%;\">\n<p class=\"lmw-table-hint\" style=\"margin:0 0 4px;font-size:0.85em;opacity:0.7;\">\u2192 Scroll horizontally to see all columns<\/p>\n<table style=\"width:max-content;min-width:100%;border-collapse:collapse;\">\n<thead>\n<tr>\n<th>Model<\/th>\n<th>Parameters<\/th>\n<th>Smallest VRAM tier<\/th>\n<th>License<\/th>\n<th>Our article<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>elyza\/ELYZA-Thinking-1.0-llm-jp-4-32b-a3b<\/td>\n<td>32.1B<\/td>\n<td>80GB<\/td>\n<td>apache-2.0<\/td>\n<td><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/2026\/10\/02\/elyza-thinking-1-0-32b-33b-2\/\">ELYZA Releases ELYZA-Thinking-1.0 32B\/33B Reasoning Models<\/a> (2026-10-02)<\/td>\n<\/tr>\n<tr>\n<td>XingChen-AGI\/Xing4.0-29B-A4B<\/td>\n<td>31.2B<\/td>\n<td>24GB<\/td>\n<td>apache-2.0<\/td>\n<td><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/2026\/09\/28\/xing4-0-29b-a4b-china-telecom\/\">Xing4.0-29B-A4B Text Generation Model: Our Test Answers, 24GB+ VRAM<\/a> (2026-09-28)<\/td>\n<\/tr>\n<tr>\n<td>Altworld\/Hemmingway-1<\/td>\n<td>26.9B<\/td>\n<td>12GB<\/td>\n<td>cc-by-nc-4.0<\/td>\n<td><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/2026\/09\/28\/hemmingway-1-open-27b-model-specialized-for-human-like-writing\/\">Hemmingway-1 Text Generation Model: 12GB+ VRAM, GGUF Builds<\/a> (2026-09-28)<\/td>\n<\/tr>\n<tr>\n<td>orcarouter\/OrcaSAQ-2-27B<\/td>\n<td>27.8B<\/td>\n<td>16GB<\/td>\n<td>apache-2.0<\/td>\n<td><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/2026\/09\/28\/orcasaq2-27b-qwen3-8-27b-quantized\/\">OrcaSAQ-2-27B Text Generation Model: Our Test Answers, 16GB+ VRAM<\/a> (2026-09-28)<\/td>\n<\/tr>\n<tr>\n<td>prism-ml\/Ternary-Bonsai-2-27B-gguf<\/td>\n<td>27.8B<\/td>\n<td>8GB<\/td>\n<td>apache-2.0<\/td>\n<td><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/2026\/09\/18\/ternary-bonsai-2-27b-gguf\/\">Ternary-Bonsai-2-27B-gguf: Our Test Answers, 8GB+ VRAM<\/a> (2026-09-18)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p><!-- \/lmw:peers --><\/p>\n<h2>How to Get It<\/h2>\n<p>It is distributed in GGUF format and can be downloaded using the Hugging Face CLI or similar tools. It is reported to work with engines such as llama.cpp (release b10842 or later recommended), LM Studio, koboldcpp, ramalama, Jan AI, Text Generation Web UI, LoLLMs, and Atomic Chat.<\/p>\n<p>Example download command:<\/p>\n<pre><code>hf download bartowski\/Gryphe_Pantheon-Reasoning-26B-A4B-1.1-V2-GGUF --include &quot;Gryphe_Pantheon-Reasoning-26B-A4B-1.1-V2-Q4_K_M.gguf&quot; --local-dir.\/\n<\/code><\/pre>\n<p><!-- lmw:related --><\/p>\n<h2>Related Articles<\/h2>\n<ul>\n<li><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/2026\/09\/15\/salience-27b-r6-gguf-2\/\">vectionlabs_Salience-27B-R6-GGUF: Our Test Answers, 12GB+ VRAM<\/a><\/li>\n<li><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/2026\/09\/14\/orion-26b-a4b-v1-1-gguf-quantizations\/\">TheDrummer_Orion-26B-A4B-v1.1-GGUF Multimodal Model: 12GB+ VRAM<\/a><\/li>\n<li><a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/2026\/09\/15\/intern-s2-397b-gguf-released\/\">Intern-S2-397B-GGUF Vision-Language Model: ~102GB Memory<\/a><\/li>\n<\/ul>\n<p><!-- \/lmw:related --><\/p>\n<p><!-- lmw:next-steps --><\/p>\n<h2>What to Read Next<\/h2>\n<ul>\n<li><strong>Find models by VRAM<\/strong> (This model runs from the 12GB tier) \u2192 <a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/vram-guide-12gb-en\/\">Other models that run on a 12GB GPU<\/a><\/li>\n<li><strong>Engines that run this model<\/strong> \u2192 <a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/engine-llama-cpp-en\/\">llama.cpp<\/a> \/ <a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/engine-ollama-en\/\">Ollama<\/a><\/li>\n<li><strong>What IQ2_S, IQ3_XS, Q5_K_M mean and where to get this model<\/strong> \u2192 <a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/format-gguf-en\/\">GGUF format guide and models<\/a> \/ <a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/glossary-quantization-en\/\">Quantization and model-format glossary<\/a><\/li>\n<li><strong>Other models for the same task<\/strong> \u2192 <a href=\"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/models-by-task-en\/#task-text\">Other text generation models<\/a><\/li>\n<\/ul>\n<p><!-- \/lmw:next-steps --><\/p>\n<h2>Sources<\/h2>\n<ul>\n<li><a href=\"https:\/\/huggingface.co\/bartowski\/Gryphe_Pantheon-Reasoning-26B-A4B-1.1-V2-GGUF\">https:\/\/huggingface.co\/bartowski\/Gryphe_Pantheon-Reasoning-26B-A4B-1.1-V2-GGUF<\/a><\/li>\n<li><a href=\"https:\/\/huggingface.co\/Gryphe\/Pantheon-Reasoning-26B-A4B-1.1-V2\">https:\/\/huggingface.co\/Gryphe\/Pantheon-Reasoning-26B-A4B-1.1-V2<\/a><\/li>\n<\/ul>\n<p><!-- lmw:updates --><\/p>\n<h2>Update History<\/h2>\n<ul>\n<li>2026-09-12: Verified the content against the official primary source.<\/li>\n<li>2026-09-24: Rebuilt the article: Added a &#8220;can you run it locally?&#8221; verdict from the distribution formats, converted builds, engine registries, license terms and measured compression<\/li>\n<li>2026-09-25: Changed the title to show what the article covers (VRAM requirements, file list, etc.).<\/li>\n<li>2026-09-28: Added our own measurements: Japanese token efficiency, what is inside the GGUF file.<\/li>\n<li>2026-09-29: Added our own measurements: CPU speed and answers to Japanese questions.<\/li>\n<li>2026-09-30: Changed the title to show what the article covers (VRAM requirements, file list, etc.).<\/li>\n<\/ul>\n<p><!-- \/lmw:updates --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Download bartowski&#8217;s GGUF quantizations for Gryphe Pantheon-Reasoning-26B, a Gemma 4 roleplay and reasoning model.<\/p>\n","protected":false},"author":1,"featured_media":7651,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[310],"tags":[1030,1032,163,136,1034,1036,117],"class_list":["post-551","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-new-models","tag-bartowski-en","tag-gemma-en","tag-gguf-en","tag-llm-en","tag-pantheon-reasoning-en","tag--en"],"lang":"en","translations":{"en":551,"ja":549},"_links":{"self":[{"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/posts\/551","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/comments?post=551"}],"version-history":[{"count":38,"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/posts\/551\/revisions"}],"predecessor-version":[{"id":14255,"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/posts\/551\/revisions\/14255"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/media\/7651"}],"wp:attachment":[{"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/media?parent=551"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/categories?post=551"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/wp-json\/wp\/v2\/tags?post=551"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}