DeepSeek R1 AWQ is an open-source language model by cognitivecomputations. Features: LLM, VRAM: 225GB, Context: 160K, License: mit, Quantized, LLM Explorer Score: 0.22.
4-bit Autotrain compatible Awq Base model:deepseek-ai/deepsee... Base model:quantized:deepseek-... Conversational Custom code Deepseek v3 En Endpoints compatible Quantized Region:us Safetensors Sharded Tensorflow Zh
Model Card on HF 🤗: https://huggingface.co/cognitivecomputations/DeepSeek-R1-AWQ
DeepSeek R1 AWQ Benchmarks
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
What is the LLM Explorer Rank (Score)
DeepSeek R1 AWQ Parameters and Internals
Best Alternatives to DeepSeek R1 AWQ
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| DeepSeek V3 AWQ | 160K / 351.9 GB | 1809 | 34 |
| DeepSeek V3 AWQ | 160K / 351.9 GB | 1039 | 35 |
| DeepSeek R1 0528 AWQ | 160K / 205 GB | 8496 | 15 |
| DeepSeek V3.0324 AWQ | 160K / 351.9 GB | 4061 | 22 |
| DeepSeek V3.1 AWQ W4AFP8 | 160K / 225 GB | 15 | 6 |
| DeepSeek R1 AWQ | 160K / 225 GB | 1496 | 86 |
| DeepSeek V3.1 4bit | 160K / 190.1 GB | 28555 | 6 |
| DeepSeek V3.0324 4bit | 160K / 198.7 GB | 1576 | 38 |
| Kimi K2 Thinking NVFP4 | 256K / 210 GB | 15086 | 30 |
| Kimi K2 Thinking BF16 | 256K / 220 GB | 86 | 6 |
Note: green Score (e.g. "73.2") means that the model is better than cognitivecomputations/DeepSeek-R1-AWQ .
Rank the DeepSeek R1 AWQ Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
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Release v20260328a