#1 · Tight but possible
DeepSeek V3.1 (671B MoE)
Hybrid thinking/non-thinking model. Full 671B MoE for maximum quality, 37B active at inference. Significant step up from V3.0. Requires server-grade hardware. MIT licensed.
chatreasoningquality
Apple Silicon hardware guide
Best local LLMs for Mac Studio M3 Ultra 512GB
Mac Studio M3 Ultra 512GB with 512GB unified memory is a server-grade local AI on Apple Silicon machine. This page lists local AI models that fit its memory budget, with realistic performance expectations for LM Studio and similar runtimes.
Chip
M3 Ultra
Unified memory
512GB
Compatible models
200
Best pick
DeepSeek V3.1 (671B MoE)
Quick answer
For Mac Studio M3 Ultra 512GB, start with DeepSeek V3.1 (671B MoE). 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
DeepSeek V3 (671B MoE)
671B MoE with 37B active params. The original massive DeepSeek. 2.4M downloads. Server-grade only.
chatcodequality
#3 · Comfortable
DeepSeek V4 Flash (284B MoE)
Efficient DeepSeek V4 variant: 284B total, 13B active, 1M-token context. Flash-Max can approach Pro reasoning with larger thinking budget. MIT licensed.
chatcodereasoningpoweragentic
#4 · Good
Llama 4 Maverick (17B/400B MoE)
Meta Llama 4 Maverick — 128-expert MoE flagship. Matches or beats GPT-4o and Gemini 2.0 Flash on reasoning, coding and multimodal benchmarks. 1M-token context. Server-grade hardware only. Llama 4 Community License.
chatvisionreasoningmultimodalquality
#5 · Comfortable
Qwen 3 MoE (235B/22B active)
Mixture of Experts behemoth. Only 22B params active at once = fast despite massive size. Top-tier.
chatcodereasoningquality
#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 · Comfortable
GPT-OSS (120B)
OpenAI flagship open-weight reasoning model. 128K context, strong tool use and Apache 2.0 licensing, now practical for 96GB+ local workstations via GGUF MXFP4.
chatcodereasoningbeastgeneral
#8 · Comfortable
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 3.5 MoE (397B/17B active)
Flagship open-source Qwen 3.5. Only 17B active params despite 397B total — world-class quality at MoE efficiency. Matches GPT-4o on major benchmarks. Requires multi-GPU or server-grade hardware. Apache 2.0.
chatcodereasoningquality
#10 · Comfortable
GLM-5.2 (744B MoE)
Z.ai flagship open model for long-horizon coding, reasoning and agentic work. 744B total, 40B active, 1M-token context, MIT license. Unsloth Dynamic GGUF makes it technically local, but it needs workstation/server-class memory: ~245GB total memory for 2-bit and 372GB+ for 4-bit.
chatcodereasoningqualityagentic
#11 · Tight but possible
DeepSeek V3.2 Exp (671B MoE)
Experimental V3.2 with DeepSeek Sparse Attention (DSA) — halves inference cost vs V3.1 on long context while keeping quality. 128K context, improved coding & tool-use. MIT licensed. Server-grade.
chatcodereasoningquality
#12 · Good
GLM 4.6 (355B MoE)
Zhipu AI flagship — full GLM 4.6. 200K context, strong tool-calling & agentic workflows. Competes with Claude 3.5 Sonnet on reasoning and code. MIT licensed. Server-grade hardware.
chatcodereasoningqualitygeneral
Buying note
This page is about local AI fit, not a live price tracker. Prices and availability change. If an Amazon link is present, it may be an affiliate link that supports LocalClaw at no extra cost.