Model Overview
- Model Architecture: Kimi-K2-Thinking
- Input: Text
- Output: Text
- Supported Hardware Microarchitecture: AMD MI350/MI355
- ROCm: 7.0
- Transformers: 4.57.6
- Operating System(s): Linux
- Inference Engine: vLLM
- Model Optimizer: AMD-Quark (V0.11.2)
- Quantized layers:
experts,shared_experts,self_attn - Weight quantization: MoE OCP MXFP4, Static; self_attn Perchannel, FP8E4M3, Static
- Activation quantization: MoE OCP MXFP4, Dynamic; self_attn Pertoken, FP8E4M3, Dynamic
- Quantized layers:
- Calibration Dataset: Pile
This model was built with Kimi-K2-Thinking model by applying AMD-Quark for MXFP4 quantization.
Model Quantization
The model was quantized from unsloth/Kimi-K2-Thinking-BF16 using AMD-Quark. Both weights and activations were quantized.
Quantization scripts:
cd Quark/examples/torch/language_modeling/llm_ptq/
exclude_layers="*mlp.gate *lm_head *mlp.gate_proj *mlp.up_proj *mlp.down_proj"
python quantize_quark.py \
--model_dir unsloth/Kimi-K2-Thinking-BF16 \
--quant_scheme mxfp4 \
--layer_quant_scheme '*self_attn*' ptpc_fp8 \
--exclude_layers $exclude_layers \
--output_dir amd/Kimi-K2-Thinking-MXFP4-AttnFP8 \
--file2file_quantization
Deployment
Use with vLLM
This model can be deployed efficiently using the vLLM backend.
Evaluation
The model was evaluated on GSM8K benchmarks.
Accuracy
| Benchmark | Kimi-K2-Thinking | Kimi-K2-Thinking-MXFP4-AttnFP8(this model) | Recovery |
| GSM8K (flexible-extract) | 94.16 | 92.95 | 98.71% |
Reproduction
The GSM8K results were obtained using the lm-evaluation-harness framework, based on the Docker image rocm/vllm-private:vllm_dev_base_mxfp4_20260122, with vLLM, lm-eval and amd-quark compiled and installed from source inside the image.
Launching server
export VLLM_ATTENTION_BACKEND="TRITON_MLA"
export VLLM_ROCM_USE_AITER=1
export VLLM_ROCM_USE_AITER_FUSION_SHARED_EXPERTS=0
vllm serve amd/Kimi-K2-Thinking-MXFP4-AttnFP8 \
--tensor-parallel-size 8 \
--enable-auto-tool-choice \
--tool-call-parser kimi_k2 \
--reasoning-parser kimi_k2 \
--trust-remote-code
Evaluating model in a new terminal
lm_eval \
--model local-completions \
--model_args "model=amd/Kimi-K2-Thinking-MXFP4-AttnFP8,base_url=http://0.0.0.0:8000/v1/completions,tokenized_requests=False,tokenizer_backend=None,num_concurrent=32" \
--tasks gsm8k \
--num_fewshot 5 \
--batch_size 1
License
Modifications Copyright(c) 2025 Advanced Micro Devices, Inc. All rights reserved.
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moonshotai/Kimi-K2-Thinking