---
pipeline_tag: text-generation
base_model:
- deepseek-ai/DeepSeek-R1
license: mit
---

Results from running `vllm serve RedHatAI/DeepSeek-R1-NVFP4-FP8-BLOCK --tensor-parallel-size=4` on 4 B200s, with `python vllm/tests/evals/gsm8k/gsm8k_eval.py --port 8000`:

```
Running GSM8K evaluation: 1319 questions, 5-shot
Evaluating: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1319/1319 [01:49<00:00, 12.09it/s]

Results:
Accuracy: 0.952
Invalid responses: 0.000
Total latency: 109.097 s
Questions per second: 12.090
Total output tokens: 124914
Output tokens per second: 1144.985
```

Compare to results with `nvidia/DeepSeek-R1-NVFP4`
```
Running GSM8K evaluation: 1319 questions, 5-shot
Evaluating: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1319/1319 [01:52<00:00, 11.74it/s]

Results:
Accuracy: 0.954
Invalid responses: 0.000
Total latency: 112.357 s
Questions per second: 11.739
Total output tokens: 128126
Output tokens per second: 1140.344
```