Apple · M5 Ultra · Desktop
Best AI Models for Mac Studio M5 Ultra (256 GB)
Runs 70–120B models well; fits models up to 427B, like MiniMax M3.
| # | Model | Speed | llmrun Score | Quant · Memory |
|---|---|---|---|---|
| 1 | Q4_K_M · 186.5 GB · 49.8 t/s | 49.8 tok/s | Q4_K_M · 186.5 GB | |
| 2 | DeepSeek V4 Flash 0731DeepSeek Q4_K_M · 183.0 GB · 36.1 t/s | 36.1 tok/s | Q4_K_M · 183.0 GB | |
| 3 | GLM 5.3 FlashZ.ai Q4_K_M · 205.2 GB · 45.6 t/s | 45.6 tok/s | Q4_K_M · 205.2 GB | |
| 4 | Qwen3.8 27BAlibaba Q4_K_M · 17.9 GB · 49.3 t/s | 49.3 tok/s | Q4_K_M · 17.9 GB | |
| 5 | Hy3Tencent Q4_K_M · 182.3 GB · 32.6 t/s | 32.6 tok/s | Q4_K_M · 182.3 GB |
| # | Model | Speed | Coding Score | Quant · Memory |
|---|---|---|---|---|
| 1 | Q4_K_M · 186.5 GB · 49.8 t/s | 49.8 tok/s | Q4_K_M · 186.5 GB | |
| 2 | DeepSeek V4 Flash 0731DeepSeek Q4_K_M · 183.0 GB · 36.1 t/s | 36.1 tok/s | Q4_K_M · 183.0 GB | |
| 3 | Qwen3.8 27BAlibaba Q4_K_M · 17.9 GB · 49.3 t/s | 49.3 tok/s | Q4_K_M · 17.9 GB | |
| 4 | GLM 5.3 FlashZ.ai Q4_K_M · 205.2 GB · 45.6 t/s | 45.6 tok/s | Q4_K_M · 205.2 GB | |
| 5 | Hy3Tencent Q4_K_M · 182.3 GB · 32.6 t/s | 32.6 tok/s | Q4_K_M · 182.3 GB |
| # | Model | Speed | Reasoning Score | Quant · Memory |
|---|---|---|---|---|
| 1 | Q4_K_M · 183.0 GB · 36.1 t/s | 36.1 tok/s | Q4_K_M · 183.0 GB | |
| 2 | GLM 5.3 FlashZ.ai Q4_K_M · 205.2 GB · 45.6 t/s | 45.6 tok/s | Q4_K_M · 205.2 GB | |
| 3 | Qwen3.8 27BAlibaba Q4_K_M · 17.9 GB · 49.3 t/s | 49.3 tok/s | Q4_K_M · 17.9 GB | |
| 4 | Inkling SmallThinking Machines Q4_K_M · 162.7 GB · 104 t/s | 104 tok/s | Q4_K_M · 162.7 GB | |
| 5 | Hy3Tencent Q4_K_M · 182.3 GB · 32.6 t/s | 32.6 tok/s | Q4_K_M · 182.3 GB |
| # | Model | Speed ↓ | llmrun Score | Quant · Memory |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 264 t/s | 264 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 135 t/s | 135 tok/s | Q4_K_M · 6.6 GB | |
| 3 | GPT OSS 20BOpenAI Q4_K_M · 13.1 GB · 128 t/s | 128 tok/s | Q4_K_M · 13.1 GB | |
| 4 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 109 t/s | 109 tok/s | Q4_K_M · 16.5 GB | |
| 5 | Hy3Tencent Q4_K_M · 182.3 GB · 32.6 t/s | 32.6 tok/s | Q4_K_M · 182.3 GB |
| # | Model | Speed | Vision Score | Quant · Memory |
|---|---|---|---|---|
| 1 | Q4_K_M · 205.2 GB · 45.6 t/s | 45.6 tok/s | Q4_K_M · 205.2 GB | |
| 2 | Qwen3.8 27BAlibaba Q4_K_M · 17.9 GB · 49.3 t/s | 49.3 tok/s | Q4_K_M · 17.9 GB | |
| 3 | Inkling SmallThinking Machines Q4_K_M · 162.7 GB · 104 t/s | 104 tok/s | Q4_K_M · 162.7 GB | |
| 4 | Qwen3.6 27BAlibaba Q4_K_M · 17.9 GB · 49.3 t/s | 49.3 tok/s | Q4_K_M · 17.9 GB | |
| 5 | Muse Glimmer 30BMeta Q4_K_M · 19.6 GB · 46.9 t/s | 46.9 tok/s | Q4_K_M · 19.6 GB |
| # | Model | Speed | Agents Score | Quant · Memory |
|---|---|---|---|---|
| 1 | Q4_K_M · 205.2 GB · 45.6 t/s | 45.6 tok/s | Q4_K_M · 205.2 GB | |
| 2 | Qwen3.8 27BAlibaba Q4_K_M · 17.9 GB · 49.3 t/s | 49.3 tok/s | Q4_K_M · 17.9 GB | |
| 3 | MiniMax M2.7MiniMax Q4_K_M · 139.6 GB · 49.7 t/s | 49.7 tok/s | Q4_K_M · 139.6 GB | |
| 4 | GLM 4.5Z.ai Q4_K_M · 217.9 GB · 23.1 t/s | 23.1 tok/s | Q4_K_M · 217.9 GB | |
| 5 | Hy3Tencent Q4_K_M · 182.3 GB · 32.6 t/s | 32.6 tok/s | Q4_K_M · 182.3 GB |
The Mac Studio M5 Ultra is the fastest 256 GB machine: it runs 70–120B models well. macOS keeps about 3.5 GB, leaving 252.5 GB for models. With 109 TFLOPS it reads long prompts faster than most 256 GB machines: a 4K-token prompt takes 5.7 s. At its $9,499 MSRP it gives 9.3 tok/s per $1,000, 5th of the 7 machines compared here. M5 Ultra generation, released 2026.
Mac Studio M5 Ultra strengths and weaknesses
Strengths
- Runs 120B MoE models: GPT OSS 120B at 89.0 tok/s in 70.8 GB
- Room for long context: Llama 3.3 70B Instruct at Q4 uses 51.3 GB, leaving 201.2 GB free
Weaknesses
- Slow prompt reading: A 32K-token prompt on MiMo V2.6 Flash RL waits 45.0 s for the first token
- No CUDA: vLLM, AWQ, GPTQ and FP8 builds don't run; use GGUF or MLX
Memory for models
252.5 GB of 256 GBEverything on the size ladder fits. MiMo V2.6 Flash RL and Qwen3.8 27B together use 204.4 GB and leave 48.1 GB free.
Speed per dollar and per watt
On Qwen3.6 35B A3B (35B params, 3B active) at Q4_K_M. New means a shop price, either a street quote or the maker's own price; used is compared with used. The last two columns are the speed you get per $1,000 of price and per 100 W of power; higher is better. The Mac Studio M5 Ultra has no current new price, so it is shown at its MSRP.
| Machine | New price | tok/s | tok/s per $1,000 | tok/s per 100 W |
|---|---|---|---|---|
RTX 509032 GB | about $5,502 | 213 | 38.8 | 37.1 |
Mac Studio M5 Ultra96 GB | about $5,499 | 87.9 | 16.0 | – |
Mac Studio M2 Ultra192 GB | about $5,599 | 75.9 | 13.6 | 25.7 |
Mac Studio M3 Ultra256 GB | about $7,099 | 76.6 | 10.8 | 28.4 |
Mac Studio M5 Ultra256 GB | about $9,499 | 87.9 | 9.3 | – |
Mac Studio M3 Ultra512 GB | about $9,499 | 76.6 | 8.1 | 28.4 |
Mac Studio M5 Ultra512 GB | about $22,299 | 87.9 | 3.9 | – |
Cost per token: the Mac Studio M5 Ultra against 24–512 GB machines and GPUs
On Qwen3.6 35B A3B (35B params, 3B active, Q4_K_M, 4K context). Speed, cost per token and power per token depend on the model.
- Machine, MSRP
- $6.85
- Power
- not published
Each dot is a machine or GPU; hover or tap it for its numbers, click to open it. Machines without a price for the chosen basis are left out. Machines without a published power figure are left out of Per watt and costed without power. How we calculate cost per token
Other memory sizes of the same machine first, then machines and GPUs people weigh against it, each with the one reason it is worth a look. Speeds on Qwen3.6 35B A3B.
Output speed depends on memory bandwidth (1228 GB/s). Grey rows need more than the 252.5 GB available.
- 9BQwen3.5 9B · Q4_K_M · 6.6 GB135tok/s
- 14BQwen3 14B · Q4_K_M · 11.9 GB90.5tok/s
- 27–31BQwen3.8 27B · Q4_K_M · 17.9 GB49.3tok/s
- 35B MoEQwen3.6 35B A3B · Q4_K_M · 22.0 GB87.9tok/s
- 70BLlama 3.3 70B Instruct · Q4_K_M · 51.3 GB18.5tok/s
- 120B MoEGPT OSS 120B · Q4_K_M · 70.8 GB89.0tok/s
Estimated speeds: Q4_K_M, 4K context, one user. How we estimate
Ultra generations: writing vs compute
M1 Ultra → M5 UltraWriting speed follows memory bandwidth and barely moved: 75.9 to 87.9 tok/s since the M1 Ultra. Compute, which sets how fast prompts are read, grew 3.5×. Indexed to the M1 Ultra; speeds on Qwen3.6 35B A3B, same 128 GB.
All 1346 models on the Mac Studio M5 Ultra
Featured onlyBest quant that fits in 252.5 GB, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works
| Model | Quant | VRAM | Speed | Context | Score | Fit |
|---|---|---|---|---|---|---|
Clef OmniVisionFunctions | Q4_K_M | 27.2 GB | 82.4 t/s | — | S88, Runs great | |
MiMo V2.5ChatFunctions | Q4_K_M | 187.6 GB | 45.9 t/s | 1049K | A78, Runs well | |
Diffusiongemma 26B A4B ITVisionFunctions | Q4_K_M | 16.5 GB | 108.6 t/s | 262K | S93, Runs great | |
| Q4_K_M | 1.8 GB | 588.8 t/s | 262K | S100, Runs great | ||
Ling Flash 2.0ChatFunctions | Q4_K_M | 63.1 GB | 93.2 t/s | 33K | S90, Runs great | |
Olmo 3.1 32B InstructChatFunctions | Q4_K_M | 21.5 GB | 42.6 t/s | 66K | A76, Runs well | |
Phi 4ChatMathCode | Q4_K_M | 12.5 GB | 90.3 t/s | 16K | S90, Runs great | |
| Q4_K_M | 4.8 GB | 325.6 t/s | — | S100, Runs great | ||
JevK5ChatFunctions | Q4_K_M | 3.2 GB | 287.5 t/s | 262K | S100, Runs great | |
| Q4_K_M | 183.9 GB | 34.7 t/s | 1049K | A73, Runs well | ||
| BF16 | 72.6 GB | 12.5 t/s | — | B51, Decent | ||
| Q4_K_M | 183.3 GB | 51.9 t/s | 1049K | A81, Runs well | ||
Qwen3.8 4B DistillChatReasoningFunctions | Q4_K_M | 3.4 GB | 263.7 t/s | 262K | S100, Runs great | |
Agents A1ChatVisionFunctions | Q4_K_M | 21.5 GB | 92.8 t/s | 262K | S90, Runs great | |
Llm Jp 4.1 32B A3b ThinkingChatFunctions | Q4_K_M | 20.1 GB | 109.6 t/s | 66K | S93, Runs great |
Specs
- Chip
- M5 Ultra
- CPU cores
- 30
- GPU cores
- 64
- Unified memory
- 256 GB
- For models
- 252.5 GB (macOS keeps 3.5 GB)
- Memory bandwidth
- 1.2 TB/s
- FP16 (dense)
- 108.8 TFLOPS
- Neural Engine
- 76 TOPS
- Released
- 2026-09-22
- MSRP
- $9,499
Mac Studio M5 Ultra FAQ
Is the Mac Studio M5 Ultra (256 GB) worth it for local LLMs in 2026?
At its $9,499 MSRP it gives 9.3 tok/s per $1,000 on Qwen3.6 35B A3B, 5th of the 7 machines compared here. It runs 70–120B models well; fits models up to 427B, like MiniMax M3.
How much memory is available for AI on the Mac Studio M5 Ultra (256 GB)?
About 252.5 GB of the 256 GB. macOS keeps roughly 3.5 GB for itself and other apps.
What is the largest model the Mac Studio M5 Ultra (256 GB) can run?
MiniMax M3 (427.0B) is the largest at 4-bit or better: at Q4_K_S it uses 242.0 GB, 96% of the available memory, and runs at about 40.0 tok/s.
Can the Mac Studio M5 Ultra (256 GB) run MiMo V2.6 Flash RL?
Yes. MiMo V2.6 Flash RL fits at Q4_K_M, using 186.5 GB of the 252.5 GB available, and it is the best model that runs well on this machine.
How long does the Mac Studio M5 Ultra (256 GB) take to read a long prompt?
On MiMo V2.6 Flash RL, about 5.7 s for a 4K-token prompt and 45 s for a 32K-token document before the first word appears.