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 on file-editing and command-running workflows.

This is the plain 8-bit compatibility variant. It does not include native MTP tensors, so it is useful when you want more precision than 4-bit but your loader does not support MTP sidecars.

Which Variant Should I Use?

Use this repo if you want the plain 8-bit MLX package.
Use jedisct1/Qwen3.6-35B-go-v2-4bit.mlx if you want the smallest plain package.
Use jedisct1/Qwen3.6-35B-go-v2-bf16.mlx if you want full precision without native MTP.
Use jedisct1/Qwen3.6-35B-go-v2-MTP-8bit.mlx if your runtime supports native MTP and you want the 8-bit MTP path.

Usage

Requires mlx-lm:

pip install mlx-lm

python

from mlx_lm import load, generate

model, tokenizer = load("jedisct1/Qwen3.6-35B-go-v2-8bit.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.