File size: 1,797 Bytes
de70ea5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 | ---
tags:
- fp8
- quantized
- mistral
- roleplay
- creative-writing
- reasoning
base_model: TheDrummer/Behemoth-R1-123B-v2
library_name: transformers
pipeline_tag: text-generation
license: apache-2.0
---
# Behemoth-R1-123B-v2 FP8 Dynamic
FP8 Dynamic quantization of [TheDrummer/Behemoth-R1-123B-v2](https://huggingface.co/TheDrummer/Behemoth-R1-123B-v2) using llmcompressor.
## Model Details
- **Base Model**: TheDrummer/Behemoth-R1-123B-v2 (Mistral Large 2411 finetune)
- **Quantization**: FP8 Dynamic (W8A8) via llmcompressor
- **Scheme**: FP8_DYNAMIC, lm_head excluded
- **Size**: ~123 GB (vs 246 GB FP16)
- **Format**: SafeTensors with compressed-tensors metadata
## Usage with vLLM
```bash
python3 -m vllm.entrypoints.openai.api_server \
--model Irvollo/Behemoth-R1-123B-v2-FP8-Dynamic \
--quantization compressed-tensors \
--dtype bfloat16 \
--max-model-len 32768 \
--gpu-memory-utilization 0.95 \
--enable-prefix-caching \
--trust-remote-code
```
## Reasoning / Thinking
Supports native reasoning via `<think>` tag prefill:
```json
{
"messages": [
{"role": "user", "content": "Your question"},
{"role": "assistant", "content": "<think>\n"}
],
"continue_final_message": true,
"add_generation_prompt": false
}
```
## Hardware Requirements
- **Single GPU**: H200 NVL (141 GB) — tight with ~18 GB KV cache
- **Recommended**: 2x A100 80GB or H100 for comfortable KV headroom
## Quantization Details
- Quantized on 2x NVIDIA B200 (358 GB VRAM)
- Calibration: 616 linear layers in <1 second
- Total pipeline: ~11 minutes
- Tool: [llmcompressor](https://github.com/vllm-project/llm-compressor)
## Credits
- Original model by [TheDrummer](https://huggingface.co/TheDrummer)
- FP8 quantization by [Irvollo](https://huggingface.co/Irvollo)
|