Apodex-1.1-mini vs Darwin-36B-Opus

Apodex-1.1-mini

An agent cousin fine-tuned from Qwen3.5-35B-A3B for long tasks with files, code and tools, with parallel tool calling and about 3B active parameters. It needs 32 GB for Apodex's GGUF, NVFP4 or GPTQ-Int4 builds or about 86 GB in BF16, and Apodex's API serves it too. The main risks are no safety results and no replies from the publisher.

Darwin-36B-Opus

A text-only reasoning cousin merged from Qwen3.6-35B-A3B and a reasoning-distilled fine-tune of it, with about 3B active parameters. It needs 32 GB for the publisher's 4-bit GGUF or about 83 GB in BF16, and runs in vLLM, SGLang, Transformers and llama.cpp. The main risks are an undisclosed merge method, a card that disagrees with its files, and no safety results.

Apodex-1.1-mini

1. Serve it with vllm serve apodex/Apodex-1.1-mini --enable-auto-tool-choice --tool-call-parser qwen3_coder --reasoning-parser qwen3, or the same parsers in SGLang, so tool calls and reasoning come back parsed
2. For llama.cpp, llama-server -hf apodex/Apodex-1.1-mini-GGUF:Q4_K_M --jinja --reasoning-format deepseek, and the card passes the repository's chat_template.jinja with --chat-template-file
3. Pass tools through the API's tools parameter rather than in the system prompt, as the card asks
4. The card recommends temperature 1.0, top_p 0.95, repetition_penalty 1.05 and max_tokens up to 32,768
5. Send your own system prompt, or set identity_mode, since the template otherwise adds an Apodex identity block
6. The template keeps all earlier reasoning in the context unless preserve_thinking is false, which grows long agent sessions
7. Thinking is on by default, send chat_template_kwargs with enable_thinking false for short tasks, a switch the card doesn't mention
8. The card's Python example has a broken line where it runs the tool (available_toolsname), so fix it to available_tools[name](**args) before running
9. Validate JSON output yourself, since structured output isn't documented

Darwin-36B-Opus

1. Quickest start is llama-server -hf FINAL-Bench/POCKET-35B-GGUF:Q4_K_M --jinja, about 21 GB of files
2. On the reference machine BF16 fits, vllm serve FINAL-Bench/Darwin-36B-Opus --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder, the parsers for Qwen3.6's format
3. Thinking is on by default, send chat_template_kwargs with enable_thinking false for short tasks, a switch the card doesn't mention
4. The card suggests temperature 0.6 to 0.7 and at least 5,120 new tokens for its think traces
5. generation_config.json stops only on the end-of-text token, so add <|im_end|> as a stop token if a runtime keeps generating after the turn ends
6. Text only, the vision encoder of Qwen3.6-35B-A3B isn't in these files
7. Validate JSON output yourself, since structured output isn't documented