{"id":1327,"date":"2026-09-17T17:03:04","date_gmt":"2026-09-17T08:03:04","guid":{"rendered":"https:\/\/localmodelwatch.tsuchitsuchi.com\/model-qwen-qwen3-8-27b-en\/"},"modified":"2026-09-19T06:50:53","modified_gmt":"2026-09-18T21:50:53","slug":"model-qwen-qwen3-8-27b-en","status":"publish","type":"page","link":"https:\/\/localmodelwatch.tsuchitsuchi.com\/en\/model-qwen-qwen3-8-27b-en\/","title":{"rendered":"Qwen\/Qwen3.8-27B: Models, Variants and Hardware Requirements"},"content":{"rendered":"

Everything Local Model Watch has published about the Qwen\/Qwen3.8-27B<\/strong> family: 6 article(s) covering the base model and its fine-tunes, plus converted builds we tracked after publication. Memory requirements below are computed by this site from file sizes, not quoted from model cards. Part of our model family index<\/a>.<\/p>\n

At a Glance<\/h2>\n
\n\n\n\n\n\n\n\n\n\n\n
Item<\/th>\nValue<\/th>\n<\/tr>\n<\/thead>\n
Family<\/td>\nQwen\/Qwen3.8-27B<\/a><\/td>\n<\/tr>\n
Publisher<\/td>\nQwen<\/td>\n<\/tr>\n
Parameters<\/td>\n27.8B<\/td>\n<\/tr>\n
License (model card)<\/td>\napache-2.0<\/td>\n<\/tr>\n
Smallest VRAM tier<\/td>\n12GB<\/td>\n<\/tr>\n
Articles<\/td>\n6<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

Hardware Requirements<\/h2>\n

Estimated requirements (calculated by Local Model Watch)<\/strong> \u2014 27.8B parameters (taken from the base model Qwen\/Qwen3.8-27B)<\/p>\n

\n\n\n\n\n\n
Your VRAM<\/th>\nQuantization<\/th>\nFile size<\/th>\nEst. memory needed<\/th>\n<\/tr>\n<\/thead>\n
12GB (RTX 4070 \/ 3060 12GB, etc.)<\/td>\nQ2_0<\/td>\n7.1GB<\/td>\n8.5GB<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

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’s authors. Compare with other models in our VRAM quick reference<\/a>. What the quantization names mean: glossary<\/a>.<\/em><\/p>\n

Figures are for prism-ml\/Ternary-Bonsai-2-27B-gguf-dev, the most recent model in this family with a hardware estimate.<\/em><\/p>\n

Quantized and Converted Variants<\/h2>\n
\n

\u2192 Scroll horizontally to see all columns<\/p>\n\n\n\n\n\n
Added<\/th>\nPublisher<\/th>\nFormat<\/th>\nRepository<\/th>\nSmallest VRAM tier (build, est. memory)<\/th>\n<\/tr>\n<\/thead>\n
2026-09-18<\/td>\nprism-ml<\/td>\nGGUF<\/td>\nprism-ml\/Ternary-Bonsai-2-27B-gguf-dev<\/a><\/td>\nQ2_0 8.5GB (fits in 12GB VRAM)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

This section is appended automatically by Local Model Watch when a converted build of this model appears after publication. Memory figures are estimated from the size of the distributed files.<\/em><\/p>\n

Articles (newest first)<\/h2>\n
\n\n\n\n\n\n\n\n\n
Published<\/th>\nModel<\/th>\nType<\/th>\nArticle<\/th>\n<\/tr>\n<\/thead>\n
2026-09-18<\/td>\nprism-ml\/Ternary-Bonsai-2-27B-gguf-dev<\/td>\nNew Models<\/td>\nPrism ML Releases Ternary-Bonsai-2-27B-gguf-dev Build<\/a><\/td>\n<\/tr>\n
2026-09-18<\/td>\nprism-ml\/Ternary-Bonsai-2-27B-gguf<\/td>\nNew Models<\/td>\nPrism ML Releases Ternary-Bonsai-2-27B-gguf: A 1.72 bpw Ternary Model<\/a><\/td>\n<\/tr>\n
2026-09-15<\/td>\nbartowski\/vectionlabs_Salience-27B-R6-GGUF<\/td>\nNew Models<\/td>\nSalience-27B-R6 GGUF Released by bartowski<\/a><\/td>\n<\/tr>\n
2026-09-12<\/td>\nagentionai\/Signal-3.8-27B-GGUF<\/td>\nNew Models<\/td>\nSignal-3.8-27B-GGUF: Faster and More Token-Efficient<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

Repositories<\/h2>\n