Text Generation
MLX
Safetensors
qwen3_5
apple-silicon
speculative-decoding
qwen
qwen3
qwen3-next
mtp
mtplx
local-ai
conversational
4-bit precision
Instructions to use finbase0530/Qwen3.6-27B-MTPLX-Optimized-Speed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use finbase0530/Qwen3.6-27B-MTPLX-Optimized-Speed with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("finbase0530/Qwen3.6-27B-MTPLX-Optimized-Speed") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- Pi new
How to use finbase0530/Qwen3.6-27B-MTPLX-Optimized-Speed with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "finbase0530/Qwen3.6-27B-MTPLX-Optimized-Speed"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "finbase0530/Qwen3.6-27B-MTPLX-Optimized-Speed" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use finbase0530/Qwen3.6-27B-MTPLX-Optimized-Speed with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "finbase0530/Qwen3.6-27B-MTPLX-Optimized-Speed"
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default finbase0530/Qwen3.6-27B-MTPLX-Optimized-Speed
Run Hermes
hermes
- MLX LM
How to use finbase0530/Qwen3.6-27B-MTPLX-Optimized-Speed with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "finbase0530/Qwen3.6-27B-MTPLX-Optimized-Speed"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "finbase0530/Qwen3.6-27B-MTPLX-Optimized-Speed" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "finbase0530/Qwen3.6-27B-MTPLX-Optimized-Speed", "messages": [ {"role": "user", "content": "Hello"} ] }'
File size: 4,514 Bytes
0aa3682 | 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 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 | ---
library_name: mlx
license: apache-2.0
base_model:
- Qwen/Qwen3.6-27B
pipeline_tag: text-generation
tags:
- mlx
- apple-silicon
- speculative-decoding
- qwen
- qwen3
- qwen3-next
- mtp
- mtplx
- local-ai
---
# Qwen3.6-27B MTPLX Optimized Speed
## Run this with MTPLX
**MTPLX** is an MLX-native runtime for native Multi-Token-Prediction speculative decoding on Apple Silicon. Up to **2.24× faster decode** at real coding temperatures (`temp=0.6 / top_p=0.95 / top_k=20`) using the model's own built-in MTP heads — no external drafter, no greedy hack.
```bash
pip install mtplx
mtplx start
```
**Project:** [github.com/youssofal/MTPLX](https://github.com/youssofal/MTPLX)
**Other MTPLX checkpoints:**
- [Qwen3.6-27B-MTPLX-Optimized](https://huggingface.co/Youssofal/Qwen3.6-27B-MTPLX-Optimized) — verified default (GDN8-Speed4 trunk + CyanKiwi INT4 MTP)
- [Qwen3.5-4B-MTPLX-Optimized-Speed](https://huggingface.co/Youssofal/Qwen3.5-4B-MTPLX-Optimized-Speed) — small 4-bit speed-test
- [Qwen3.5-4B-Optimized-MTPLX](https://huggingface.co/Youssofal/Qwen3.5-4B-Optimized-MTPLX) — small 8-bit
---
This is the speed checkpoint for MTPLX v0.1.0-preview. It combines the
MLXCommunity flat 4-bit MLX trunk with the calibrated CyanKiwi INT4 MTP sidecar
and embeds `mtplx_runtime.json` so MTPLX can run it as the optimized speed
variant.
Target repository: `Youssofal/Qwen3.6-27B-MTPLX-Optimized-Speed`
## Runtime
```bash
mtplx pull Youssofal/Qwen3.6-27B-MTPLX-Optimized-Speed
mtplx run "hello" --model Youssofal/Qwen3.6-27B-MTPLX-Optimized-Speed
mtplx serve --model Youssofal/Qwen3.6-27B-MTPLX-Optimized-Speed --port 8000 --no-stats-footer
```
MTPLX v0.1.0-preview supports Qwen3-Next-MTP only. This model is verified for
the `qwen3-next-mtp` backend.
## Sources And Attribution
| Component | Source | Revision | License |
|---|---|---:|---|
| Base model | `Qwen/Qwen3.6-27B` | `6a9e13bd6fc8f0983b9b99948120bc37f49c13e9` | Apache-2.0 |
| Calibrated MTP sidecar source | `cyankiwi/Qwen3.6-27B-AWQ-BF16-INT4` | `8cc526ddcfdd53346f94fb9b5458ca8495a63218` | Apache-2.0 |
| MTPLX conversion and runtime contract | `youssofal/mtplx` | v0.1.0-preview.1 | Apache-2.0 |
The trunk is the MLXCommunity flat 4-bit affine conversion of
`Qwen/Qwen3.6-27B`. The MTP sidecar is derived from the downloaded CyanKiwi
compressed-tensors checkpoint at the revision listed above.
## Verification
`mtplx_runtime.json` records:
- architecture: `qwen3-next-mtp`
- maximum MTP depth: `3`
- recommended profile: `performance-cold`
- recommended draft-only LM head: `3-bit affine, group_size=64`
- recommended draft sampler: temperature `0.70`, top-p `0.95`, top-k `20`
- exactness gate: `Phase 0H paged-verifier smoke`
- exactness max absolute diff: `0.0`
- verified hardware: `Apple M5 Max, 128 GB unified memory`
- verified timestamp: `2026-05-03T23:07:00+0100`
Target sampler used for the recorded contract: temperature `0.6`,
top-p `0.95`, top-k `20`, with thinking mode disabled. The draft proposal
sampler is intentionally slightly hotter at temperature `0.70`; target
verification and residual correction remain exact.
## Performance Honesty
This is the default speed lane. On the local Apple M5 Max fanmax
performance-cold benchmark, this artifact reached **63.056 tok/s** and
**62.886 tok/s** at depth 3 on the long-code 192-token prompt when using its
contract-recommended 3-bit draft-only LM head plus draft sampler temperature
`0.70`, with thinking mode disabled and foreground app load reduced. The
proposal change reduced the measured correction tokens from 6 to 3 and verify
calls from 50 to 49 on the recorded prompt; target sampling remains temperature
`0.6` / top-p `0.95` / top-k `20`. A full greedy diagnostic on the same cleaned
fanmax window measured **60.108 tok/s**. Earlier contract evidence measured
61.527 and 60.900 tok/s, the earlier 3-bit draft-head contract measured 60.038
and 60.061 tok/s, and the older 4-bit draft-only LM head measured 57.668 tok/s
on the same lane.
## Files
- `model-*.safetensors`: MLXCommunity flat 4-bit trunk shards.
- `mtp.safetensors`: calibrated prequantized INT4 MTP sidecar.
- `mtplx_runtime.json`: MTPLX verified runtime contract.
- `MTPLX_PUBLISH_MANIFEST.json`: local staging manifest with source paths,
materialization method, sizes, and optional hashes.
## Links
- **MTPLX**: [github.com/youssofal/MTPLX](https://github.com/youssofal/MTPLX) · `pip install mtplx`
- **Base model**: [Qwen/Qwen3.6-27B](https://huggingface.co/Qwen/Qwen3.6-27B)
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