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192 GB VRAM · 5300 GB/s · Vulkan

AI models for Instinct MI300X

Here are the best open models for each job on the Instinct MI300X, and every model's grade below.

Your hardware

…

Memory
GB
Bandwidth
GB/s
Context

 

Most intelligent on your …

Intelligence (ECI) of the most intelligent models that load · colour shows how well they run

Expected speed

Tokens per second on your … for the most intelligent models that run well

Models available with more memory

Open models that run well (grade B or better) at each memory size

Scores from Oct 8, 2026 · 0 new models in the last two months

Every model on the Instinct MI300X

Q4_K_M, 8K context, 192 GB of memory. Change your setup above for exact numbers.

GradeModelMemorySpeed
StInkling Small 266B149 GB~178 tok/s
SqwenQwen3 235B A22B Thinking 2507 235.1B134.2 GB~141 tok/s
SqwenQwen3 235B A22B Instruct 2507 235.1B134.2 GB~141 tok/s
SminimaxMiniMax M2.5 228.7B131.1 GB~180 tok/s
SminimaxMiniMax M2.7 228.7B131.5 GB~180 tok/s
ScohereCommand A+ 218.8B126.7 GB~133 tok/s
SqwenQwen3.8 Flash Next 180B111.9 GB~204 tok/s
SmistralMistral Medium 3.5 128B 127.7B72.8 GB~48 tok/s
SqwenQwen3.5 122B A10B 125.1B71.8 GB~186 tok/s
SmistralMistral Small 4 119B 119.4B68.1 GB~205 tok/s
Sopenaigpt-oss 120b 116.8B59 GB~216 tok/s
SmetaLlama 4 Scout 17B 16E 108.6B62.7 GB~155 tok/s
SqwenQwen3 Coder Next 79.7B45.7 GB~226 tok/s
SmetaLlama 3.3 70B Instruct 70.6B42.4 GB~73 tok/s
SmoonshotKimi Linear 48B A3B 49.1B28.4 GB~227 tok/s
SqwenQwen3.6 35B A3B 36B21.2 GB~226 tok/s
SqwenQwen3.5 35B A3B 36B21 GB~226 tok/s
Sai2Olmo 3.1 32B Think 32.2B19.7 GB~117 tok/s
SnvidiaNemotron 3.5 Lightning 30B A3B 31.6B24.1 GB~221 tok/s
SgoogleGemma 4 31B 31.3B18.8 GB~120 tok/s
SzaiGLM 4.7 Flash 31.2B17.8 GB~226 tok/s
SqwenQwen3 30B A3B Thinking 2507 30.5B18.3 GB~221 tok/s
SqwenQwen3 30B A3B Instruct 2507 30.5B18.3 GB~221 tok/s
ScohereNorth Mini Code 1.0 30.5B18.2 GB~223 tok/s
SibmGranite 4.2 30B 29.3B19.1 GB~122 tok/s
SqwenQwen3.8 27B 27.8B17 GB~126 tok/s
SqwenQwen3.6 27B 27.8B16.5 GB~129 tok/s
SgoogleGemma 4 26B A4B 25.8B16.5 GB~217 tok/s
SmistralDevstral Small 2 24B 24B14.9 GB~137 tok/s
SmistralMagistral Small 2509 24B14.9 GB~137 tok/s
SmistralMistral Small 3.2 24B 24B14.9 GB~137 tok/s
SmistralMagistral Small 2506 23.6B14.9 GB~137 tok/s
Sopenaigpt-oss 20b 20.9B11.3 GB~224 tok/s
SmicrosoftPhi-4 14B 14.7B10.1 GB~163 tok/s
SmistralMinistral 3 14B 14B9.2 GB~168 tok/s
SgoogleGemma 4 12B 12B7.4 GB~177 tok/s
SqwenQwen3.5 9B 9.7B5.8 GB~189 tok/s
SmistralMinistral 3 8B 8.9B6.2 GB~190 tok/s
SibmGranite 4.2 8B 8.8B6.7 GB~186 tok/s
SmetaLlama 3.1 8B Instruct 8B5.9 GB~192 tok/s
SgoogleGemma 4 E4B 8B5.1 GB~196 tok/s
Sai2Olmo 3 7B Instruct 7.3B7 GB~183 tok/s
SgoogleGemma 4 E2B 5.1B3.3 GB~213 tok/s
SqwenQwen3.5 4B 4.7B3.1 GB~216 tok/s
SmistralMinistral 3 3B 3.9B3.1 GB~219 tok/s
SibmGranite 4.2 3B 3.7B3.1 GB~218 tok/s
SmetaLlama 3.2 3B Instruct 3.2B3.1 GB~220 tok/s
ShuggingfaceSmolLM3 3B 3.1B2.6 GB~223 tok/s
SliquidLFM2.5 2.6B 2.7B2 GB~228 tok/s
SqwenQwen3.5 2B 2.3B1.6 GB~233 tok/s
SqwenQwen3.5 0.8B 0.9B0.9 GB~243 tok/s
BzaiGLM 5.3 Flash 321.3B176.1 GB~158 tok/s
BdeepseekDeepSeek V4 Flash 0731 304.2B161 GB~176 tok/s
BdeepseekDeepSeek V4 Flash 290.9B166.7 GB~171 tok/s
CzaiGLM 4.7 358.3B204.8 GB~34 tok/s
19 models do not fit on the Instinct MI300X
GradeModelMemorySpeed
FmoonshotKimi K3 2.8T1,584.5 GB—
FdeepseekDeepSeek V4 Pro 0813 1.7T886.8 GB—
FdeepseekDeepSeek V4 Pro 1.6T886.8 GB—
FmoonshotKimi K2.6 1T578.8 GB—
FmoonshotKimi K2.7 Code 1T578.8 GB—
FmoonshotKimi K2.5 1T579.4 GB—
FmoonshotKimi K2 Thinking 1T579.4 GB—
FmoonshotKimi K2 Instruct 1T579 GB—
FtInkling 952.4B534 GB—
FdeepseekDeepSeek V4.1 Flash 763.2B435.8 GB—
FzaiGLM 5.1 753.9B429.2 GB—
FzaiGLM 5 753.9B425.7 GB—
FzaiGLM 5.2 753.3B424.5 GB—
FdeepseekDeepSeek V3.2 Exp 685.4B391.5 GB—
FdeepseekDeepSeek V3.2 685.4B378.5 GB—
FdeepseekDeepSeek V3.1 684.5B378.4 GB—
FnvidiaNemotron 3 Ultra 550B A55B 560.5B321.8 GB—
FminimaxMiniMax M3 427B244.6 GB—
FqwenQwen3.5 397B A17B 403.4B227.9 GB—

Share a measured speed

Run one of these and paste the whole output below (or just the tokens per second):

llama-bench -m model.gguf
ollama run model --verbose

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