Model reference · open weights
Qwen3.6-MTP is an open-weight language model from unsloth, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
Read our How to Run Qwen3.6 MTP Guide! To run in llama.cpp: Set -DGGMLCUDA=OFF for CPU/Metal. -np 1 and --mmproj are not yet supported with MTP. - Developer Role Support so Qwen3.6 can work in <a href="https://unsloth.ai/docs/basics/codex"Codex</a, OpenCode and more! - Qwen3.6 can now be run and fine-tuned in <a href="https://unsloth.ai/docs/new/studio"Unsloth Studio</a. <a href="https://unsloth.ai/docs/models/qwen3.6"Read our guide</a. - Tool calling improvements: Makes parsing nested objects to make tool calling succeed more. Qwen3.6-27B [](https://chat.qwen.ai) [!Note] This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format. These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc. Following the February release of the Qwen3.5 series, we're pleased to share the first open-weight variant of Qwen3.6. Built on direct feedback from the community, Qwen3.6 prioritizes stability and real-world utility, offering developers a more intuitive, responsive, and genuinely productive coding experience. Qwen3.6 Highlights This release delivers substantial upgrades, particularly in - Agentic Coding: the model now handles frontend workflows and repository-level reasoning with greater fluency and precision. - Thinking Preservation: we've introduced a new option to retain reasoning context from historical messages, streamlining iterative development and reducing overhead. For more details, please refer to our blog post Qwen3.6-27B. Model Overview - Type: Causal Language Model with Vision Encoder - Training Stage: Pre-training & Post-training - Language Model - Number of Parameters: 27B - Hidden Dimension: 5120 - Token Embedding: 248320 (Padded) - Number of Layers: 64 - Hidden Layout: 16 × (3 × (Gated DeltaNet → FFN) → 1 × (Gated Attention → FFN)) - Gated DeltaNet: - Number of Linear Attention Heads: 48 for V and 16 for QK - Head Dimension: 128 - Gated Attention: - Number of Attention Heads: 24 for Q and 4 for KV - Head Dimension: 256 - Rotary Position Embedding Dimension: 64 - Feed Forward Network: - Intermediate Dimension: 17408 - LM Output: 248320 (Padded) - MTP: tr
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | unsloth |
|---|---|
| Type | Language models |
| Variants | 1 |
| Runs with | transformers |
| Based on | Qwen/Qwen3.6-27B |
| Released | 2026-05-11 |
| Popularity | 902k downloads / month |
| Likes | 1,306 |
| Licence | Open weights |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| Qwen3.6-27B-MTP-GGUF | — | GGUF | — | — | Weights ↗ |
Using it via the API
Once AxForge deploys qwen3-6-mtp for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (qwen3-6-mtp below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/chat/completions \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"qwen3-6-mtp","messages":[{"role":"user","content":"Hello"}]}'
Details
Tags
Licence
Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗