--- license: apache-2.0 base_model: - Qwen/Qwen3.6-35B-A3B library_name: mlx tags: - mlx - qwen3.6 - qwen3_5_moe - apple-silicon - tool-calling - go --- # Qwen3.6-35B-go-v2 4-bit MLX A Go-focused Qwen3.6-35B-A3B model for Apple Silicon, packaged in MLX. Use it as a coding assistant for Go projects: generating focused patches, explaining diffs, tightening tests, reading tool outputs, and making small repo-aware edits. It was tested with [Swival](https://swival.dev) on file-editing and command-running workflows. This is the plain 4-bit compatibility variant. It does not include native MTP tensors, so it is the best starting point if your MLX loader does not support MTP sidecars. ## Which Variant Should I Use? - **Use this repo** if you want the smallest plain MLX package or need a loader-friendly non-MTP model. - Use [`jedisct1/Qwen3.6-35B-go-v2-8bit.mlx`](https://huggingface.co/jedisct1/Qwen3.6-35B-go-v2-8bit.mlx) if you want more precision without native MTP. - Use [`jedisct1/Qwen3.6-35B-go-v2-bf16.mlx`](https://huggingface.co/jedisct1/Qwen3.6-35B-go-v2-bf16.mlx) if you want full precision without native MTP. - Use [`jedisct1/Qwen3.6-35B-go-v2-MTP-4bit.mlx`](https://huggingface.co/jedisct1/Qwen3.6-35B-go-v2-MTP-4bit.mlx) if your runtime supports native MTP and you want the faster MTP path. ## Usage Requires [mlx-lm](https://github.com/ml-explore/mlx-examples/tree/main/llms/mlx_lm): ```bash pip install mlx-lm ``` ```python from mlx_lm import load, generate model, tokenizer = load("jedisct1/Qwen3.6-35B-go-v2-4bit.mlx") messages = [ {"role": "system", "content": "You are an expert Go developer."}, {"role": "user", "content": "Generate a focused patch that replaces the manual retry loop in fetchUser() with the shared retry helper."}, ] prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) response = generate(model, tokenizer, prompt=prompt, max_tokens=500) print(response) ``` ## What It Is Good At - Writing idiomatic Go patches from a concise change request. - Explaining Go diffs in commit-message style. - Following tool-calling workflows where it needs to inspect files before editing. - Keeping changes focused instead of turning small fixes into broad rewrites. - Working with tests, command output, and repository context. ## Limitations - Outputs should be reviewed before use, especially patches that touch production systems. - The model works best on focused Go changes, tests, and explanations. Very large refactors may need to be split into smaller steps. - Tool calling depends on the runtime and client preserving the chat template and tool schema format.