XingChen-AGI/Xing4.0-29B-A4B-GGUF
text-generation model by XingChen-AGI
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Model card & documentation
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This repository provides low-bit quantized weights and a quantization imatrix for Xing4.0-29B-A4B, covering a 2–8-bit quantization range and achieving better accuracy. The quantized GGUF files range from 11–34 GB, allowing you to choose appropriate weights to run on a single consumer-grade GPU. Xing4.0-29B-A4B is a next-generation large language model in the Xing series (formerly TeleChat), developed by China Telecom Artificial Intelligence Technology Co., Ltd. With 29B total parameters and only 4B activated per token, it natively supports a 256K context length, extensible to 512K. It is the…
Read the full model card ↗ · Preview checked 2026-11-03T03:02:23.204Z
Inside the original model card — Document outline
- Running Xing4.0-29B-A4B Locally - Read our guide
- Xing4.0-29B-A4B
- Highlights
- Model Overview
- Benchmark
- Quickstart
- Inference
- Serving
- Recommended Parameters
- Footnotes
- Citation
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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
XingChen-AGI/Xing4.0-29B-A4B-GGUF is a text-generation model repository published by XingChen-AGI on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-generation
- Library
- transformers
- Recent downloads (30 days)
- 8,327
- Cumulative likes
- 154
- Hugging Face trending score
- 74
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-09-16T13:23:49.000Z
- Last modified
- 2026-09-20T03:39:45.000Z
Compatibility and lineage
Language coverage was not reported.
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-24T06:37:30.549Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.