Apple Silicon hardware guide

Best local LLMs for Mac Studio M4 Ultra 256GB

Mac Studio M4 Ultra 256GB with 256GB unified memory is a frontier open-weight model experiments machine. This page lists local AI models that fit its memory budget, with realistic performance expectations for LM Studio and similar runtimes.

Chip
M4 Ultra
Unified memory
256GB
Compatible models
168
Best pick
Qwen 3 MoE (235B/22B active)

Quick answer

For Mac Studio M4 Ultra 256GB, start with Qwen 3 MoE (235B/22B active). Models marked “Comfortable” leave useful memory headroom; “Tight but possible” can work, but you should close other apps and prefer lower quantization.

Mac Studio · M4 Ultra · 256GB RAM · 2TB SSD · Monster

Top compatible local LLMs

#1 · Comfortable

Qwen 3 MoE (235B/22B active)

235B (22B active) · 96GB min · Q4_K_M · 80GB

Mixture of Experts behemoth. Only 22B params active at once = fast despite massive size. Top-tier.

chatcodereasoningquality
#2 · Comfortable

DeepSeek V3.2 (37B/671B MoE)

37B (671B MoE) · 48GB min · Q4_K_M · 40GB

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
#3 · Comfortable

Mistral Large (123B)

123B · 96GB min · Q4_K_M · 70GB

Mistral flagship. 128K context. Top-tier coding and multilingual. 262K downloads. Requires serious hardware.

chatcodequality
#4 · Comfortable

Command A (111B)

111B · 80GB min · Q4_K_M · 64GB

Cohere enterprise flagship. Top-tier for RAG and enterprise use. 58K downloads.

chatgeneralquality
#5 · Comfortable

Command A (111B)

111B · 96GB min · Q4_K_M · 68GB

Cohere open-weight flagship optimised for agentic workflows and long-context RAG. 256K context, excellent multilingual coverage (23 languages). CC-BY-NC 4.0 — non-commercial.

chatreasoningqualitygeneralpower
#6 · Comfortable

WizardLM 2 (8x22B)

8x22B (141B total) · 96GB min · Q4_K_M · 88GB

Microsoft AI's ultra-popular fine-tune of Mixtral 8x22B. Apache 2.0 license. Exceptional instruction following and conversational quality.

chatcodepowerqualitygeneral
#7 · Comfortable

Qwen 3.5 MoE (122B/10B active)

122B (10B active) · 80GB min · Q4_K_M · 65GB

Large MoE model with only 10B active params. 60% cheaper to run than Qwen3-Max. 256K context. Top-tier reasoning, coding and multilingual. Hybrid think/non-think. Apache 2.0.

chatcodereasoningqualitypower
#8 · Comfortable

Qwen 3 Next (80B/3B MoE)

80B (3B active) · 64GB min · Q4_K_M · 48GB

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
#9 · Comfortable

Qwen 3.6 (27B)

27B · 32GB min · Q4_K_M · 17GB

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
#10 · Comfortable

Qwen 3 Coder (30B)

30B · 24GB min · Q4_K_M · 18GB

Qwen flagship coding model. Designed for agentic coding with 256K context. Outperforms Claude 3.5 Sonnet on SWE-bench. Apache 2.0.

codepowerquality
#11 · Good

MiniMax M2 (230B MoE)

230B (10B active) · 192GB min · Q4_K_M · 140GB

MiniMax MoE flagship with 10B active params and 4M-token long-context. Specialised for agentic coding and tool-use. Competitive with GPT-4 class models at a fraction of the inference cost. MIT licensed.

chatcodereasoningquality
#12 · Comfortable

Qwen 3 (32B)

32B · 32GB min · Q4_K_M · 20GB

Near GPT-4 intelligence locally. Thinking mode demolishes hard problems. The local AI dream.

chatcodereasoningpowerquality

Buying note

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