Xing4.0 Guide: VRAM Requirements, GGUF Builds

Everything Local Model Watch has published about the Xing4.0 family: 1 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.

At a Glance

Item Value
Base model(s) XingChen-AGI/Xing4.0-29B-A4B
Publisher China Telecom (Xing, TeleChat)
Parameters 31.2B
License (model card) apache-2.0
Smallest VRAM tier 24GB
Articles 1

Hardware Requirements

Estimated requirements (calculated by Local Model Watch) — 31.2B parameters

Your VRAM Quantization File size Est. memory needed
24GB (RTX 4090 / 3090, etc.) IQ4_NL 18.7GB 22.5GB

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. File sizes are measured from the converted build XingChen-AGI/Xing4.0-29B-A4B-GGUF. Compare with other models in our VRAM quick reference. What the quantization names mean: glossary.

Can You Run It Locally?

Runs in Ollama, LM Studio and llama.cpp via a converted build.

The publisher ships safetensors, but XingChen-AGI/Xing4.0-29B-A4B-GGUF provides a GGUF build you can use.

License — apache-2.0 (Commercial use allowed): Permits commercial use, modification and redistribution. Redistribution requires including the license and stating changes; includes a patent grant.

Compression: the IQ4_NL build measures 5.15 bits per weight — about 32% the size of the original 16-bit weights, calculated by this site from the actual file sizes.

Compiled by this site’s code from the published formats, converted builds we have found, and each engine’s own model registry. “Not found" means we have not seen such a build, not that none exists. License summaries are not legal advice — check the publisher’s original terms before relying on them.

Quantized and Converted Variants

→ Scroll horizontally to see all columns

Added Publisher Format Repository Smallest VRAM tier (build, est. memory)
2026-09-28 XingChen-AGI GGUF (imatrix) XingChen-AGI/Xing4.0-29B-A4B-GGUF IQ4_NL 22.5GB (fits in 24GB VRAM)
2026-09-28 XingChen-AGI FP8 XingChen-AGI/Xing4.0-29B-A4B-FP8 FP8 37.1GB (fits in 48GB VRAM)
2026-09-28 mlx-community MLX mlx-community/Xing4.0-29B-A4B-OptiQ-4bit MLX 4bit 23.0GB (fits in 24GB VRAM)

File sizes of each build:

  • Available builds in XingChen-AGI/Xing4.0-29B-A4B-GGUF: IQ4_NL 18.7GB
  • Available builds in XingChen-AGI/Xing4.0-29B-A4B-FP8: FP8 30.9GB
  • Available builds in mlx-community/Xing4.0-29B-A4B-OptiQ-4bit: MLX 4bit 19.2GB

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.

Articles (the family’s own models first, then newest)

Published Model Type Article
2026-09-28 XingChen-AGI/Xing4.0-29B-A4B New Models Xing4.0-29B-A4B 29B MoE Model Strong in Coding Agents: 24GB+ VRAM

Repositories

Last updated 2026-09-28 (JST). Assembled by code from our article log; no text on this page is written by an AI model.