Instructions to use Kecven/Qwen3.8-27B-MTPLX-Q4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Kecven/Qwen3.8-27B-MTPLX-Q4 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Qwen3.8-27B-MTPLX-Q4 Kecven/Qwen3.8-27B-MTPLX-Q4
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Upload README.md with huggingface_hub
Browse files
README.md
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---
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tags:
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- mlx
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library_name: mlx
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---
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---
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license: apache-2.0
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base_model:
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- Qwen/Qwen3.8-27B
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tags:
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- mlx
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- mtplx
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- qwen
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- qwen3.8
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- speculative-decoding
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- mtp
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- quantized
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library_name: mlx
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---
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# Qwen3.8-27B-MTPLX-Q4
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MTPLX-compatible 4-bit conversion of [Qwen/Qwen3.8-27B], built locally from the original BF16 checkpoint while preserving the model's native MTP weights in BF16.
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## Quantization
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- Base model: `Qwen/Qwen3.8-27B`
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- Body: 4-bit affine
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- Group size: 64
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- MTP sidecar: native BF16
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- Maximum verified MTP depth: 3
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- MTPLX version: 2.3.0
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- Source format: BF16 native MTP
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Forge recipe:
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```json
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{
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"body_bits": 4,
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"body_dtype": "auto",
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"body_group_size": 64,
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"body_mode": "affine",
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"mtp_policy": "keep_bf16"
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}
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```
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## Verification Results
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Verified locally with MTPLX Forge using the `long-code-uncapped` suite with a maximum generation budget of 2048 tokens.
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| Mode | Speed | vs AR | Acceptance |
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|---|---:|---:|---|
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| AR / depth 0 | 15.74 tok/s | 1.00× | — |
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| MTP depth 1 | 27.82 tok/s | 1.77× | 96.95% |
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| MTP depth 2 | 36.53 tok/s | 2.32× | 96.13% / 90.66% |
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| MTP depth 3 | **44.34 tok/s** | **2.82×** | 95.90% / 89.55% / 81.72% |
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Forge verdict:
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```text
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mtp_depth_wins
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```
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All tested depths passed the Forge quality verification gate.
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The recommended profile produced by Forge is:
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```text
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sustained
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```
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## MTP Configuration
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```text
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architecture: qwen3-next-mtp
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mtp_depth_max: 3
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mtp_sidecar: bf16
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base_hidden_variant: post_norm
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hidden_variant: post_norm
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concat_order: embedding_hidden
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mtp_position_mode: local
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```
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## Source Provenance
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- Source repository: `Qwen/Qwen3.8-27B`
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- Source commit: `1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0`
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- Conversion: MTPLX Forge
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- MTPLX version: `2.3.0`
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- Forged locally on macOS / Apple Silicon
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The MTP weights were preserved from the original BF16 checkpoint rather than requantized.
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## Performance Notes
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The benchmark numbers above are specific to the machine used for verification and should not be treated as universal throughput figures.
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The more useful result is the relative improvement on the same hardware:
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```text
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15.74 tok/s AR
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↓
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44.34 tok/s MTP depth 3
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2.82× decode throughput
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```
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MTP acceptance remained high through depth 3, with the third speculative position accepted approximately 81.7% of the time.
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## Usage
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This model is intended for use with MTPLX on Apple Silicon.
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After downloading, inspect the included runtime metadata and use the MTPLX runtime to load the model. The Forge-generated runtime metadata contains the verified MTP contract and recommended configuration.
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## License
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This conversion follows the Apache-2.0 license of the original `Qwen/Qwen3.8-27B` checkpoint.
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See the upstream model repository for additional usage information and attribution requirements.
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