#1 · Good
Qwen 3 MoE (235B/22B active)
Mixture of Experts behemoth. Only 22B params active at once = fast despite massive size. Top-tier.
chatcodereasoningquality
Apple Silicon hardware guide
Best local LLMs for Mac Studio M4 Ultra 128GB
Mac Studio M4 Ultra 128GB with 128GB unified memory is a large model local inference 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
128GB
Compatible models
166
Best pick
Qwen 3 MoE (235B/22B active)
Quick answer
For Mac Studio M4 Ultra 128GB, 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.
Top compatible local LLMs
#2 · Good
Mistral Large (123B)
Mistral flagship. 128K context. Top-tier coding and multilingual. 262K downloads. Requires serious hardware.
chatcodequality
#3 · Good
Command A (111B)
Cohere enterprise flagship. Top-tier for RAG and enterprise use. 58K downloads.
chatgeneralquality
#4 · Good
Command A (111B)
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
#5 · Comfortable
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
#6 · Comfortable
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
#7 · Good
Llama 4 Scout (17B/109B MoE)
Meta Llama 4 Scout — natively multimodal MoE with 16 experts. 10M-token context window. Outperforms Gemma 3 and Mistral Small on most benchmarks at similar active cost. Llama 4 Community License.
chatvisionreasoningmultimodalpower
#8 · Good
Qwen 3.5 MoE (122B/10B active)
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
#9 · Comfortable
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
#10 · 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
#11 · 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
#12 · Comfortable
Qwen 3 (32B)
Near GPT-4 intelligence locally. Thinking mode demolishes hard problems. The local AI dream.
chatcodereasoningpowerquality
Buying note
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