Qwen3.6 35B-A3B
Qwen / 35B / Q4_K_M / ~22 GB
Best for: Reasoning, Coding, Agents·Pop: 88/100
Perf: ~22.8 tok/s · first token ~1.7s
Best for reasoning, coding, agents. Strong fit for 64 GB RAM with balanced speed and quality.
A Mac Studio with 64GB runs the strongest local coding stack: 27B-35B class models at full speed, with enough headroom to keep an autocomplete model loaded alongside. This is where local stops feeling like a compromise.
Qwen / 35B / Q4_K_M / ~22 GB
Best for: Reasoning, Coding, Agents·Pop: 88/100
Perf: ~22.8 tok/s · first token ~1.7s
Best for reasoning, coding, agents. Strong fit for 64 GB RAM with balanced speed and quality.
Qwen / 35B / Q4_K_M / ~20 GB
Best for: Reasoning, Coding, Agent scenarios·Pop: 90/100
Perf: ~22.8 tok/s · first token ~1.7s
Best for reasoning, coding, agent scenarios. Strong fit for 64 GB RAM with balanced speed and quality.
Qwen / 27B / Q4_K_M / ~16 GB
Best for: Chat, Coding, Complex reasoning·Pop: 82/100
Perf: ~28.8 tok/s · first token ~0.8s
Best for chat, coding, complex reasoning. Strong fit for 64 GB RAM with balanced speed and quality.
Qwen / 27B / Q4_K_M / ~18 GB
Best for: Coding, Quality, Long context·Pop: 92/100
Perf: ~28.8 tok/s · first token ~0.8s
Best for coding, quality, long context. Strong fit for 64 GB RAM with balanced speed and quality.
Gemma / 26B / Q4_K_M / ~16 GB
Best for: Chat, Coding, Multimodal·Pop: 86/100
Perf: ~29.8 tok/s · first token ~0.8s
Best for chat, coding, multimodal. Strong fit for 64 GB RAM with balanced speed and quality.
Gemma / 31B / Q4_K_M / ~20 GB
Best for: Quality, Coding, Multimodal·Pop: 84/100
Perf: ~25.5 tok/s · first token ~1.6s
Best for quality, coding, multimodal. Strong fit for 64 GB RAM with balanced speed and quality.
Qwen / 30B / Q4_K_M / ~22 GB
Best for: Quality, Coding·Pop: 78/100
Perf: ~26.2 tok/s · first token ~1.6s
Best for quality, coding. Strong fit for 64 GB RAM with balanced speed and quality.
Gemma / 27B / Q4_K_M / ~21 GB
Best for: Quality, Coding·Pop: 71/100
Perf: ~28.8 tok/s · first token ~0.8s
Best for quality, coding. Strong fit for 64 GB RAM with balanced speed and quality.
The ~45GB budget fits current 27B dense and 35B MoE models, the open-weight tier that competes with cloud assistants on real code review. MoE coders give you that quality at 14B-like speeds, which matters when an agent makes fifty calls in a row.
Use the headroom for parallel workloads: a 4B completion model pinned hot, the big model for chat and refactors, and 32K-64K context for whole-module reasoning. The Studio also makes a natural team inference server, same LAN pattern as a Mini, several times the capacity.
Use the ModelFit wizard to test different RAM and chip configurations for your exact Mac Studio setup.
Open ModelFit Wizard