Local AI Advisor

Can Mac Studio M4 Max 48 GB run Qwen3.5 35B-A3B?

48 GB unified · 546 GB/s memory bandwidth · Qwen3.5 35B-A3B has 36B parameters (3B active per token).

Short answer

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

Best quantization for chat: 5-bit (23 GB of weights) on LM Studio. Generation: 110–150 tok/s, leaving about 15 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 WebUIExcellent5-bit110–150 tok/sunder 1 s8KDetails
Coding questionswith ContinueExcellent5-bit110–150 tok/s≈3 s16KDetails
Coding in a repositorywith AiderComfortable6-bit85–120 tok/s≈8 s32KDetails
Agentic codingwith OpenCodeComfortable5-bit95–130 tok/s≈10 s32KDetails
Long documents (64K)with Open WebUIExcellent5-bit75–100 tok/s≈30 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 5-bit build with a 64K context. Ollama and llama.cpp download the file straight from Hugging Face.

ollama run hf.co/unsloth/Qwen3.5-35B-A3B-GGUF:Q5_K_M

Downloads 26.25 GB (Q5_K_M). 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.