deepseek-v4-gguf
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).
Params
—
Context
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Downloads 30d
875 K
Likes
423
Download history
daily snapshots · 10 days875 K654 K
Jul 28Jul 31Aug 3Aug 6
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| DeepSeek-V4-Flash-MTP-Q4K-Q8_0-F32.gguf | Q8_0 | 3.8 GB | 4.7 GB | ✅ Runs comfortably |
| DeepSeek-V4-Pro-Q4K-Layers00-30.gguf | GGUF | 457.5 GB | 503.8 GB | ❌ Won’t fit |
| DeepSeek-V4-Pro-IQ2XXS-w2Q2K-AProjQ8-SExpQ8-OutQ8-Instruct-imatrix.gguf | Q8 | 464.6 GB | 511.6 GB | ❌ Won’t fit |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Run it
copy-paste, exact tags checked against the Hub$ ollama run deepseek-v4-gguf # pin the quantization explicitly $ ollama run deepseek-v4-gguf-gguf
$ huggingface-cli download antirez/deepseek-v4-gguf-GGUF \
DeepSeek-V4-Pro-Q4K-Layers00-30.gguf --local-dir .
$ llama-cli -m DeepSeek-V4-Pro-Q4K-Layers00-30.gguf \
-c 8192 -ngl 99 -t 8 --color
$ curl -s https://aimodelscomparison.com/api/v1/models/deepseek-v4-gguf
{
"hf_id": "antirez/deepseek-v4-gguf",
"params_b": null,
"context_length": null,
"license": { "id": "mit", "commercial": "yes" },
"downloads_30d": 875129,
"vram_estimates": [
{ "quant": "GGUF", "gb": 503.8 },
{ "quant": "Q8", "gb": 511.6 }
],
"updated_at": "2026-08-05T01:00:14Z"
}
Specifications
- Licence
- mit
- First seen on the Hub
- 2026-04-26
- Base model
- DeepSeek-V4-Flash
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
Family
Base model and the most-downloaded derivatives in the catalog.
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