Apple · apple

Apple M3 Ultra

Apple M3 Ultra has 256 GB of unified memory at 819 GB/s — about 178.56 GiB usable after driver and compositor overhead. 2108 of 2118 indexed models fit at 8K context with q8_0 KV. Note only 192 GB of its 256 GB is allocatable to the GPU.

Spec sheet· bandwidth, theoreticalFrom the file· fit from summed bytesPredicted· speed
Memory
256 GB
LPDDR5-6400
Bandwidth
819 GB/s
1024-bit bus
Tensor FP16
dense
TDP
KV cachef16q8_0q4_0quantizing the KV cache is a ~2× lever on the dominant term at long context
vision language 192text 1812image 2audio tts 21audio asr 39video 16embedding 26

What fits at 8K context

largest quantization that fits, per model · 2108 of 2118 indexed
ModelBest quantParamsWeightsKVTotal in memoryHeadroomtok/s
MiniMax-M3MoEQ3_K_L427B190.89 GiB0.50 GiB191.96 GiB0.04 GiB20±37%
GLM-4.5MoEIQ4_NL358B189.74 GiB1.53 GiB191.86 GiB0.14 GiB17±37%
GLM-4.7MoEIQ4_NL358B189.62 GiB1.53 GiB191.74 GiB0.26 GiB17±37%
GLM-4.6-Derestricted-v3MoEIQ4_NL357B188.93 GiB1.53 GiB191.05 GiB0.95 GiB17±37%
GLM-4.6MoEIQ4_NL357B188.93 GiB1.53 GiB191.05 GiB0.95 GiB17±37%
GLM-5.1MoEIQ2_XXS754B189.92 GiB0.36 GiB190.89 GiB1.11 GiB20±37%
GLM-5MoEUD-IQ1_S754B189.71 GiB0.36 GiB190.67 GiB1.33 GiB20±37%
Qwen3-Coder-480B-A35B-InstructMoEUD-IQ3_XXS480B187.70 GiB1.03 GiB189.31 GiB2.69 GiB17±37%
openPangu-2.0-FlashMoEKV unresolvedBF16100B188.04 GiB0.21 GiB188.81 GiB3.19 GiB21±37%
cogito-671b-v2.1MoEUD-IQ1_M671B187.19 GiB0.28 GiB188.11 GiB3.89 GiB21±37%
DeepSeek-V3.1-TerminusMoEUD-IQ1_M685B187.19 GiB0.28 GiB188.10 GiB3.90 GiB21±37%
DeepSeek-V3-0324MoEUD-IQ1_M685B186.94 GiB0.28 GiB187.85 GiB4.15 GiB21±37%
cogito-v2-preview-deepseek-671B-MoEMoEUD-IQ1_M671B186.85 GiB0.28 GiB187.76 GiB4.24 GiB21±37%
DeepSeek-R1-0528MoEUD-IQ1_M685B186.69 GiB0.28 GiB187.60 GiB4.40 GiB21±37%
DeepSeek-TNG-R1T2-ChimeraMoEUD-IQ1_M685B186.69 GiB0.28 GiB187.60 GiB4.40 GiB21±37%
DeepSeek-Prover-V2-671BMoEUD-IQ1_M685B186.06 GiB0.28 GiB186.98 GiB5.02 GiB21±37%
DeepSeek-V3.2MoEUD-IQ1_M685B185.62 GiB0.28 GiB186.54 GiB5.46 GiB21±37%
Qwen3.5-397B-A17BMoEUD-IQ4_NL403B185.08 GiB0.12 GiB185.80 GiB6.20 GiB24±37%
Qwen3-Coder-REAP-363B-A35BMoEIQ4_XS363B183.56 GiB1.03 GiB185.17 GiB6.83 GiB16±37%
MiniMax-M2.7MoEQ6_K229B183.52 GiB1.03 GiB185.09 GiB6.91 GiB20±37%
Hermes-4-405BQ3_K_M406B181.96 GiB2.09 GiB184.88 GiB7.12 GiB4±8.3%
Hermes-3-Llama-3.1-405BQ3_K_M406B181.96 GiB2.09 GiB184.88 GiB7.12 GiB4±8.3%
r1-1776MoEIQ2_S671B183.47 GiB0.28 GiB184.38 GiB7.62 GiB21±37%
DeepSeek-R1MoEIQ2_S685B183.47 GiB0.28 GiB184.38 GiB7.62 GiB21±37%
Ornith-1.0-397BMoEUD-IQ4_NL397B182.60 GiB0.12 GiB183.32 GiB8.68 GiB24±37%
MiMo-V2.5MoEKV unresolvedQ4_1311B180.99 GiB0.50 GiB182.08 GiB9.92 GiB21±37%
NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16MoEUD-IQ2_M561B180.64 GiB0.00 GiB181.23 GiB10.77 GiB20±37%
MiMo-V2-FlashMoEKV unresolvedQ4_1310B180.12 GiB0.50 GiB181.22 GiB10.78 GiB21±37%
Qwen3-235B-A22BMoEQ6_K235B179.80 GiB0.78 GiB181.17 GiB10.83 GiB16±37%
Qwen3-235B-A22B-Instruct-2507MoEQ6_K235B179.80 GiB0.78 GiB181.17 GiB10.83 GiB16±37%
Qwen3-235B-A22B-Thinking-2507MoEQ6_K235B179.80 GiB0.78 GiB181.17 GiB10.83 GiB16±37%
Qwen3-VL-235B-A22B-ThinkingMoEQ6_K236B179.76 GiB0.78 GiB181.12 GiB10.88 GiB16±37%
Qwen3-VL-235B-A22B-InstructMoEQ6_K236B179.76 GiB0.78 GiB181.12 GiB10.88 GiB16±37%
Qwen3-235B-A22B-abliteratedMoEI1-Q6_K235B179.76 GiB0.78 GiB181.12 GiB10.88 GiB16±37%
DeepSeek-Coder-V2-Instruct-0724MoEQ6_K236B180.25 GiB0.28 GiB181.12 GiB10.88 GiB20±37%
DeepSeek-V2.5MoEQ6_K236B180.25 GiB0.28 GiB181.12 GiB10.88 GiB20±37%
DeepSeek-Coder-V2-InstructMoEQ6_K236B180.25 GiB0.28 GiB181.12 GiB10.88 GiB20±37%
grok-2MoEQ5_K_M270B178.41 GiB1.06 GiB180.17 GiB11.83 GiB7±37%
DeepSeek-V3.1MoEUD-IQ1_S685B179.11 GiB0.28 GiB180.02 GiB11.98 GiB21±37%
GLM-4.6-REAP-268B-A32BMoEQ5_K_M269B177.71 GiB1.53 GiB179.83 GiB12.17 GiB16±37%
Llama-4-Maverick-17B-128E-InstructMoEKV unresolvedQ3_K_M402B177.95 GiB0.80 GiB179.32 GiB12.68 GiB26±37%
command-a-plus-05-2026-bf16MoEQ6_K219B176.79 GiB0.36 GiB177.70 GiB14.30 GiB17±37%
Trinity-Large-PreviewMoEQ3_K_M399B176.43 GiB0.67 GiB177.68 GiB14.32 GiB25±37%
Nex-N2-ProMoEIQ3_M397B176.93 GiB0.12 GiB177.66 GiB14.34 GiB24±37%
Trinity-Large-TrueBaseMoEI1-Q3_K_M399B176.30 GiB0.67 GiB177.55 GiB14.45 GiB25±37%
Trinity-Large-ThinkingMoEIQ3_M399B176.24 GiB0.67 GiB177.49 GiB14.51 GiB25±37%
Hy3MoEQ4_1299B174.90 GiB1.33 GiB176.81 GiB15.19 GiB19±37%
MiniMax-M2.1MoEQ6_K229B174.91 GiB1.03 GiB176.48 GiB15.52 GiB21±37%
MiniMax-M2MoEQ6_K229B174.91 GiB1.03 GiB176.48 GiB15.52 GiB21±37%
MiniMax-M2.5MoEQ6_K229B174.87 GiB1.03 GiB176.43 GiB15.57 GiB21±37%
MiniMax-M2.7-BF16-ultra-uncensored-hereticMoEQ6_K229B174.87 GiB1.03 GiB176.43 GiB15.57 GiB21±37%
ERNIE-4.5-300B-A47B-PTQ4_1300B174.57 GiB0.90 GiB176.14 GiB15.86 GiB4±8.3%
Qwen3.5-REAP-262B-A17BMoEQ5_K_M262B172.96 GiB0.12 GiB173.68 GiB18.32 GiB23±37%
Minimax-M3-abliterated-cleanMoEQ3_K_S427B171.06 GiB0.50 GiB172.12 GiB19.88 GiB22±37%
GLM-5.2MoEQ3_K_M753B169.33 GiB0.36 GiB170.29 GiB21.71 GiB22±37%
GLM-4.7-REAP-218B-A32BMoEQ6_K218B167.57 GiB1.53 GiB169.68 GiB22.32 GiB15±37%
Solar-Open2-250BMoEQ5_K_M250B165.65 GiB0.80 GiB167.02 GiB24.98 GiB24±37%
Step-3.7-FlashQ6_K_L201B160.20 GiB2.14 GiB162.92 GiB29.08 GiB4±8.3%
DeepSeek-V4-FlashMoEQ4_K291B153.33 GiB0.03 GiB153.96 GiB38.04 GiB27±37%
step-3.5-flashQ6_K199B150.81 GiB2.14 GiB153.53 GiB38.47 GiB5±8.3%
From the filePredictedwhat these mean

Speed is modeled, not measured: decode is memory-bandwidth bound, so tokens per second is bytes read per token against achievable bandwidth. Mixture-of-experts models carry a wider band because only the routed experts are read each step, and few have been measured publicly.

Questions people ask

What AI models can a Apple M3 Ultra run?
2108 of 2118 indexed open-weight models fit a Apple M3 Ultra at 8,192 context with q8_0 KV cache, the largest being MiniMax-M3 at Q3_K_L. That covers text, vision-language, image, video and speech models.
How much usable memory does a Apple M3 Ultra actually have?
Its nameplate is 256 GB, but about 178.56 GiB is available to a model once driver and compositor overhead is accounted for, and only 192 GB of the pool can be allocated to the GPU at all.
Is a Apple M3 Ultra fast for local AI?
Its memory bandwidth is 819 GB/s, and that figure — not teraflops — is what governs token generation speed. Capacity decides what you can run; bandwidth decides how fast it runs.