antirez/deepseek-v4-gguf
text-generation model by antirez
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
This quants are specific for the DS4 inference engine. They may work with other inference engines or not (they should, but not the MTP model which requires a specific loader). https://github.com/antirez/ds4 Use q2 on 128 GB Mac machines, q4 on machines with ≥ 256 GB RAM, pair either with MTP for optional speculative decoding. The filename is the spec. In detail, for the q2 file: For the q4 file, only the three routed-expert classes change to Q4K. Everything else is byte-for-byte identical to the q2 recipe. The motivation behind the asymmetry: the routed experts are the majority of the parameter count but each individual expert handles only a fraction…
Read the full model card ↗ · Preview checked 2026-10-29T12:39:33.803Z
Inside the original model card — Document outline
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Documentation belongs to its respective authors. Reported project/model license: mit. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
antirez/deepseek-v4-gguf is a text-generation model repository published by antirez on Hugging Face. The source reports the gguf 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
- gguf
- Recent downloads (30 days)
- 1,116,064
- Cumulative likes
- 495
- Hugging Face trending score
- 2
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2026-04-26T07:54:05.000Z
- Last modified
- 2026-08-31T18:47:37.000Z
Compatibility and lineage
Reported languages: en
Reported base models: deepseek-ai/DeepSeek-V4-Flash
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 2026-11-01T06:51:29.042Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.