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Instinct MI60

Instinct MI60 has 32 GB of VRAM at 1024 GB/s — about 29.76 GiB usable after driver and compositor overhead. 2011 of 2118 indexed models fit at 16K context with q8_0 KV.

Spec sheet· bandwidth, theoreticalFrom the file· fit from summed bytesPredicted· speed
Memory
32 GB
HBM2
Bandwidth
1024 GB/s
4096-bit bus
Tensor FP16
dense
TDP
300 W
KV cachef16q8_0q4_0quantizing the KV cache is a ~2× lever on the dominant term at long context
text 1726vision language 181video 16image 2embedding 26audio tts 21audio asr 39

What fits at 16K context

largest quantization that fits, per model · 2011 of 2118 indexed
ModelBest quantParamsWeightsKVTotal in memoryHeadroomtok/s
Yi-34B-200K-DARE-megamerge-v8Q6_K34.4B26.78 GiB1.99 GiB29.76 GiB0.00 GiB22±26.5%
Nous-Hermes-2-Yi-34BI1-Q6_K34.4B26.78 GiB1.99 GiB29.76 GiB0.00 GiB22±26.5%
Nous-Capybara-limarpv3-34BI1-Q6_K34.4B26.78 GiB1.99 GiB29.76 GiB0.00 GiB22±26.5%
Apertus-70B-Instruct-2509UD-IQ3_XXS70.6B26.01 GiB2.66 GiB29.75 GiB0.01 GiB22±26.5%
Huihui-GLM-4.7-Flash-abliterated-57BMoEI1-IQ4_XS57.3B27.68 GiB1.11 GiB29.73 GiB0.03 GiB77±37%
Salience-1.5-ProMoEQ6_K_L36.0B28.66 GiB0.17 GiB29.73 GiB0.03 GiB115±37%
Qwable-v1MoEQ6_K_L36.0B28.66 GiB0.17 GiB29.73 GiB0.03 GiB115±37%
T-SearchMoEQ6_K_L36.0B28.66 GiB0.17 GiB29.73 GiB0.03 GiB115±37%
Phi-3.5-MoE-instructMoEKV unresolvedQ5_K_L41.9B27.75 GiB1.06 GiB29.72 GiB0.04 GiB58±37%
Rombo-LLM-V3.0-Qwen-72bI1-IQ2_S72.7B26.02 GiB2.66 GiB29.71 GiB0.05 GiB22±26.5%
Qwen2.5-72B-Instruct-abliteratedI1-IQ2_S72.7B26.02 GiB2.66 GiB29.71 GiB0.05 GiB22±26.5%
Qwen2.5-72B-Instruct-abliterated-v2I1-IQ2_S72.7B26.02 GiB2.66 GiB29.71 GiB0.05 GiB22±26.5%
HuatuoGPT-o1-72BIQ2_S72.7B26.02 GiB2.66 GiB29.71 GiB0.05 GiB22±26.5%
MiroThinker-v1.0-72BI1-IQ2_S72.7B26.02 GiB2.66 GiB29.71 GiB0.05 GiB22±26.5%
Malaysian-Qwen2.5-72B-InstructI1-IQ2_S72.7B26.02 GiB2.66 GiB29.71 GiB0.05 GiB22±26.5%
Qwen2.5-72BI1-IQ2_S72.7B26.02 GiB2.66 GiB29.71 GiB0.05 GiB22±26.5%
magnum-v4-72bI1-IQ2_S72.7B26.02 GiB2.66 GiB29.71 GiB0.05 GiB22±26.5%
KAT-Dev-72B-ExpIQ2_S72.7B26.02 GiB2.66 GiB29.71 GiB0.05 GiB22±26.5%
Homer-v1.0-Qwen2.5-72BIQ2_S72.7B26.02 GiB2.66 GiB29.71 GiB0.05 GiB22±26.5%
Tower-Plus-72B-ultra-uncensored-hereticI1-IQ2_S72.7B26.02 GiB2.66 GiB29.71 GiB0.05 GiB22±26.5%
Qwen2.5-VL-72B-InstructIQ2_S73.4B26.02 GiB2.66 GiB29.71 GiB0.05 GiB22±26.5%
UI-TARS-72B-DPOIQ2_S73.4B26.02 GiB2.66 GiB29.71 GiB0.05 GiB22±26.5%
HarmonicHarlequin_v5-20BI1-Q2_K33.3B11.47 GiB17.27 GiB29.68 GiB0.08 GiB22±26.5%
Bernini-RQ8_014.3B28.71 GiB0.00 GiB29.66 GiB0.10 GiB22±26.5%
command-r-35b-writer-v2IQ4_XS35.0B18.02 GiB10.63 GiB29.65 GiB0.11 GiB23±26.5%
Gemma-4-Novelist-Eclipse-31BQ6_K_L32.7B26.60 GiB1.95 GiB29.54 GiB0.22 GiB23±26.5%
Gemma-4-31B-StyleTuneQ6_K_L32.7B26.60 GiB1.95 GiB29.54 GiB0.22 GiB23±26.5%
MiniMax-M2.1-REAP-139B-A10BMoEI1-IQ1_S139B26.55 GiB2.06 GiB29.49 GiB0.27 GiB69±37%
m51Lab-MiniMax-M2.7-REAP-139B-A10BMoEI1-IQ1_S139B26.55 GiB2.06 GiB29.49 GiB0.27 GiB69±37%
Assistant_Pepe_70BQ2_K70.6B25.79 GiB2.66 GiB29.48 GiB0.28 GiB23±26.5%
Hermes-4-70BUD-IQ3_XXS70.6B25.76 GiB2.66 GiB29.44 GiB0.32 GiB23±26.5%
Llama-3.3-70B-InstructUD-IQ3_XXS70.6B25.76 GiB2.66 GiB29.44 GiB0.32 GiB23±26.5%
DeepSeek-R1-Distill-Llama-70BUD-IQ3_XXS70.6B25.76 GiB2.66 GiB29.44 GiB0.32 GiB23±26.5%
Apriel-1.6-15b-ThinkerBF1614.9B26.88 GiB1.59 GiB29.43 GiB0.33 GiB23±26.5%
Qwen3.5-88BMoEI1-Q2_K_S87.7B28.30 GiB0.20 GiB29.42 GiB0.34 GiB104±37%
Kimi-Linear-48B-A3B-InstructMoEQ4_K_L49.1B28.26 GiB0.25 GiB29.42 GiB0.34 GiB23±26.5%
ALIA-40b-fc-2606I1-Q5_K_M40.4B26.78 GiB1.59 GiB29.39 GiB0.37 GiB23±26.5%
ALIA-40b-instruct-2606I1-Q5_K_M40.4B26.78 GiB1.59 GiB29.39 GiB0.37 GiB23±26.5%
Hunyuan-A13B-InstructMoEQ2_K80.4B27.40 GiB1.06 GiB29.36 GiB0.40 GiB23±26.5%
Qwen3-Coder-NextMoEUD-IQ3_S79.7B27.65 GiB0.80 GiB29.34 GiB0.42 GiB108±37%
CalmeRys-78B-Orpo-v0.1I1-IQ2_XXS78.0B25.43 GiB2.86 GiB29.31 GiB0.45 GiB23±26.5%
calme-2.3-rys-78bIQ2_XXS78.0B25.43 GiB2.86 GiB29.31 GiB0.45 GiB23±26.5%
Qwen3.6-27B-Heretic2-Uncensored-Finetune-ThinkingQ8_027.4B27.82 GiB0.53 GiB29.31 GiB0.45 GiB23±26.5%
Devstral-2-123B-Instruct-2512IQ1_S125B25.33 GiB2.92 GiB29.31 GiB0.45 GiB23±26.5%
Mistral-Medium-3.5-128BI1-IQ1_S128B25.33 GiB2.92 GiB29.31 GiB0.45 GiB23±26.5%
XORTRON-NXTXPRTXXLI1-IQ1_S128B25.33 GiB2.92 GiB29.31 GiB0.45 GiB23±26.5%
Darwin-35B-A3B-OpusMoEQ6_K_L36.0B28.22 GiB0.17 GiB29.29 GiB0.47 GiB117±37%
Aurora-Code-1MoEQ6_K_L34.7B28.22 GiB0.17 GiB29.29 GiB0.47 GiB117±37%
grug-35b-v2MoEQ6_K_L35.1B28.22 GiB0.17 GiB29.29 GiB0.47 GiB117±37%
grug-35bMoEQ6_K_L35.1B28.22 GiB0.17 GiB29.29 GiB0.47 GiB117±37%
WorldSim-Opus-3.6-35B-A3BMoEQ6_K_L35.1B28.22 GiB0.17 GiB29.29 GiB0.47 GiB117±37%
Qwen3.6-35B-A3B-AnkoMoEQ6_K_L35.1B28.22 GiB0.17 GiB29.29 GiB0.47 GiB117±37%
KAT-Coder-V2.5-DevMoEQ6_K_L34.7B28.22 GiB0.17 GiB29.29 GiB0.47 GiB117±37%
Ornith-1.0-35BMoEQ6_K_L34.7B28.22 GiB0.17 GiB29.29 GiB0.47 GiB117±37%
Nex-N2-miniMoEQ6_K_L35.1B28.22 GiB0.17 GiB29.29 GiB0.47 GiB117±37%
Maenad-70BI1-IQ3_XXS70.6B25.58 GiB2.66 GiB29.26 GiB0.50 GiB23±26.5%
DeepSeek-R1-Distill-Llama-70B-Uncensored-v2-Unbiased-ReasonerI1-IQ3_XXS70.6B25.58 GiB2.66 GiB29.26 GiB0.50 GiB23±26.5%
Rombos-LLM-70b-Llama-3.3I1-IQ3_XXS70.6B25.58 GiB2.66 GiB29.26 GiB0.50 GiB23±26.5%
L3.3-Electra-R1-70bI1-IQ3_XXS70.6B25.58 GiB2.66 GiB29.26 GiB0.50 GiB23±26.5%
L3.3-70B-Magnum-v4-SEIQ3_XXS70.6B25.58 GiB2.66 GiB29.26 GiB0.50 GiB23±26.5%
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 Instinct MI60 run?
2011 of 2118 indexed open-weight models fit a Instinct MI60 at 16,384 context with q8_0 KV cache, the largest being Yi-34B-200K-DARE-megamerge-v8 at Q6_K. That covers text, vision-language, image, video and speech models.
How much usable memory does a Instinct MI60 actually have?
Its nameplate is 32 GB, but about 29.76 GiB is available to a model once driver and compositor overhead is accounted for.
Is a Instinct MI60 fast for local AI?
Its memory bandwidth is 1024 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.