#1 · Good
Llama 3.3 (70B)
Meta's 70B workhorse. Good finetune ecosystem. Outperformed by GLM 4.5 Air and DeepSeek V3.2 for raw quality.
chatpowerqualitygeneral
Apple Silicon hardware guide
Best local LLMs for Mac Studio M4 Max 64GB
Mac Studio M4 Max 64GB with 64GB unified memory is a high-end local LLM workstation machine. This page lists local AI models that fit its memory budget, with realistic performance expectations for LM Studio and similar runtimes.
Chip
M4 Max
Unified memory
64GB
Compatible models
155
Best pick
Llama 3.3 (70B)
Quick answer
For Mac Studio M4 Max 64GB, start with Llama 3.3 (70B). Models marked “Comfortable” leave useful memory headroom; “Tight but possible” can work, but you should close other apps and prefer lower quantization.
Top compatible local LLMs
#2 · Tight but possible
Qwen 2.5 (72B)
Alibaba's massive 72B. Among the best open models globally. Exceptional multilingual + coding + reasoning.
chatcodequalitygeneral
#3 · Good
Trinity Large Preview (70B MoE)
Arcee AI's massive MoE open model. ~400B total parameters, 70B active per forward pass. Ranks near the top of global usage leaderboards. Exceptional versatility across reasoning, coding and chat. Free and open-source. Apache 2.0.
chatcodereasoningpowerquality
#4 · Good
Kimi Linear 48B-A3B Instruct
Moonshot AI efficient Kimi model with linear-attention style architecture and 3B active parameters. Strong long-context, reasoning and coding signal. MIT licensed.
chatcodereasoningpowermoe
#5 · Good
DeepSeek V3.2 (37B/671B MoE)
DeepSeek's massive MoE flagship. 37B active out of 671B total. Exceptional coding, reasoning and general capabilities. Ranks #6 on global usage leaderboards with 29B monthly tokens. MIT licensed.
chatcodereasoningpowerquality
#6 · Tight but possible
Qwen 3 Next (80B/3B MoE)
Alibaba's next-gen MoE with hybrid-gated DeltaNet attention. Only 3B active params — runs at dense 7B speed with 70B quality. 256K native context (extensible to 1M). Hybrid thinking mode. Apache 2.0.
chatcodereasoningpowerquality
#7 · Comfortable
Qwen 3.6 (27B)
Qwen 3.6 flagship dense model. Hybrid thinking mode with /think toggle for deep chain-of-thought reasoning. 128K context, 29+ languages. Significantly outperforms Qwen3.5-27B on reasoning, coding & math. Apache 2.0.
chatcodereasoningpowerquality
#8 · Comfortable
Qwen 3 Coder (30B)
Qwen flagship coding model. Designed for agentic coding with 256K context. Outperforms Claude 3.5 Sonnet on SWE-bench. Apache 2.0.
codepowerquality
#9 · Comfortable
Qwen 3 (32B)
Near GPT-4 intelligence locally. Thinking mode demolishes hard problems. The local AI dream.
chatcodereasoningpowerquality
#10 · Comfortable
Kimi K2.5 (32B/1T MoE)
Moonshot AI's agentic flagship. 1T total MoE parameters with 32B active per forward pass. Unmatched long-context reasoning at 256K tokens. Designed for complex agentic tasks and tool use. Model License — check moonshotai.com for commercial terms.
chatcodereasoningpowerquality
#11 · Comfortable
Gemma 4 26B A4B
Gemma 4 MoE flagship-for-workstations: 26B total with ~4B active parameters. 256K context and excellent quality-per-watt for local inference. Apache 2.0.
chatcodereasoningpowermultimodal
#12 · Comfortable
Gemma 4 31B
Largest Gemma 4 model for premium local quality. Strong coding and reasoning with 256K context and broad multilingual support. Apache 2.0.
chatcodereasoningqualitymultimodal
Buying note
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