Local AI Advisor

Can Mac Studio M2 Max 64 GB run Qwen3.6 35B-A3B?

64 GB unified · 400 GB/s memory bandwidth · Qwen3.6 35B-A3B has 36B parameters (3B active per token).

Short answer

Yes, excellent for chat and excellent or better for every workload we test.

Best quantization for chat: 6-bit (28 GB of weights) on LM Studio. Generation: 70–95 tok/s, leaving about 25 GB free for your other apps.

How it rates for each workload

Same model and machine, different jobs. Agents and long documents send far bigger prompts than chat, so they need much more speed and memory.

WorkloadVerdictQuantGenerationFirst replyContext
Chatwith Open WebUIExcellent6-bit70–95 tok/sunder 1 s8KDetails
Coding questionswith ContinueExcellent6-bit70–95 tok/s≈3 s16KDetails
Coding in a repositorywith AiderExcellent6-bit65–85 tok/s≈10 s32KDetails
Agentic codingwith OpenCodeExcellent6-bit60–85 tok/s≈15 s32KDetails
Long documents (64K)with Open WebUIExcellent6-bit50–70 tok/s≈40 s64KDetails

Speeds are estimates calibrated against measured benchmarks on similar hardware. “First reply” is the time to read the workload’s opening prompt. How we calculate

Get it running

Copy-paste commands for the 6-bit build with a 64K context. Ollama and llama.cpp download the file straight from Hugging Face.

ollama run hf.co/unsloth/Qwen3.6-35B-A3B-GGUF:UD-Q6_K_XL

Downloads 31.84 GB (UD-Q6_K_XL). Ollama's default context is small: set OLLAMA_CONTEXT_LENGTH=65536 before `ollama serve` for long prompts.

Different tool, context size or workload?

These pages use typical settings. The full check models your exact setup.