lightseekorg / Inkling-MXFP4

huggingface.co
Total runs: 488
24-hour runs: 0
7-day runs: -2.1K
30-day runs: -23.8K
Model's Last Updated: July 17 2026
text-generation

Introduction of Inkling-MXFP4

Model Details of Inkling-MXFP4

Inkling-MXFP4

Model Overview
  • Model Architecture: Thinking Machines Lab Inkling
    • Input: Text, Image, Audio
    • Output: Text
  • Inference Engine: TokenSpeed
  • Model Optimizer: AMD Quark (0.12.post1+rocm72.torch2.11)
    • Quantized layers: MoE routed experts only
    • Weight quantization: OCP MXFP4, static
    • Activation quantization: OCP MXFP4, dynamic

This model was built by applying AMD Quark MXFP4 quantization to the BF16 Thinking Machines Lab Inkling checkpoint. The quantization targets the MoE routed experts, while attention layers and shared experts are kept in BF16.

Environment

The quantization workflow was prepared on an AMD gfx950 system. The inspected container environment was:

  • GPU: AMD MI350/MI355
  • Target graphics version: gfx950
  • ROCm: 7.2.1
  • amdgpu driver: 6.16.13
  • OS: Linux 6.8.0-84, x86_64
  • Python: 3.12.3
  • PyTorch: 2.13.0+rocm7.1
  • AMD Quark: 0.12.post1+rocm72.torch2.11
  • Safetensors: 0.8.0
  • Transformers: 5.13.1

Create and activate the Quark environment:

python3 -m venv ~/.venv-quark
source ~/.venv-quark/bin/activate

Install the required packages:

python -m pip install torch torchvision --index-url https://download.pytorch.org/whl/rocm7.1
python -m pip install amd-quark --extra-index-url https://pypi.amd.com/quark/rocm72/simple
python -m pip install safetensors transformers accelerate tqdm
Model Quantization

The model was quantized with the Quark file-to-file flow. This avoids loading the full BF16 checkpoint into GPU memory at once, which is important for very large MoE checkpoints. Run the quantization script:

python quantize_quark.py \
  --model_dir /path/to/model \
  --output_dir /path/to/output \
  --quant_scheme mxfp4 \
  --file2file_quantization

The script applies the model-specific exclusion policy automatically in file-to-file mode. The resulting checkpoint stores MXFP4 routed-expert weights and scales while preserving non-routed-expert components in BF16.

Deployment

This model can be served with TokenSpeed :

tokenspeed serve \
  --model lightseekorg/Inkling-MXFP4 \
  --attn-tp-size 4 \
  --moe-tp-size 4 \
  --max-model-len 81920 \
  --max-num-seqs 16 \
  --max-prefill-tokens 8192 \
  --chunked-prefill-size 8192 \
  --gpu-memory-utilization 0.95 \
  --disable-cuda-graph-padding \
  --trust-remote-code \
  --dtype bfloat16 \
  --disable-kvstore \
  --kvstore-ratio 0 \
  --block-size 128 \
  --host 127.0.0.1 \
  --port 22015
Evaluation

The following validation results are placeholders and will be updated before public release.

Benchmark BF16 Reference MXFP4
BFCL exact calls 78.3% 79.1%
BFCL all-live macro 75.4% 75.3%
MMAU 77.2% 76.0%
GPQA Diamond 88.1% 85.4%
AIME26 96.4% 96.7%

Runs of lightseekorg Inkling-MXFP4 on huggingface.co

488
Total runs
0
24-hour runs
-520
3-day runs
-2.1K
7-day runs
-23.8K
30-day runs

More Information About Inkling-MXFP4 huggingface.co Model

More Inkling-MXFP4 license Visit here:

https://choosealicense.com/licenses/apache-2.0

Inkling-MXFP4 huggingface.co

Inkling-MXFP4 huggingface.co is an AI model on huggingface.co that provides Inkling-MXFP4's model effect (), which can be used instantly with this lightseekorg Inkling-MXFP4 model. huggingface.co supports a free trial of the Inkling-MXFP4 model, and also provides paid use of the Inkling-MXFP4. Support call Inkling-MXFP4 model through api, including Node.js, Python, http.

lightseekorg Inkling-MXFP4 online free

Inkling-MXFP4 huggingface.co is an online trial and call api platform, which integrates Inkling-MXFP4's modeling effects, including api services, and provides a free online trial of Inkling-MXFP4, you can try Inkling-MXFP4 online for free by clicking the link below.

lightseekorg Inkling-MXFP4 online free url in huggingface.co:

https://huggingface.co/lightseekorg/Inkling-MXFP4

Inkling-MXFP4 install

Inkling-MXFP4 is an open source model from GitHub that offers a free installation service, and any user can find Inkling-MXFP4 on GitHub to install. At the same time, huggingface.co provides the effect of Inkling-MXFP4 install, users can directly use Inkling-MXFP4 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

Inkling-MXFP4 install url in huggingface.co:

https://huggingface.co/lightseekorg/Inkling-MXFP4

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