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24 GB VRAM · 1008 GB/s · CUDA

AI models for RTX 4090

Here are the best open models for each job on the RTX 4090, 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 RTX 4090

Q4_K_M, 8K context, 24 GB of memory. Change your setup above for exact numbers.

GradeModelMemorySpeed
SzaiGLM 4.7 Flash 31.2B17.8 GB~333 tok/s
SqwenQwen3 30B A3B Thinking 2507 30.5B18.3 GB~274 tok/s
SqwenQwen3 30B A3B Instruct 2507 30.5B18.3 GB~274 tok/s
ScohereNorth Mini Code 1.0 30.5B18.2 GB~293 tok/s
SgoogleGemma 4 26B A4B 25.8B16.5 GB~236 tok/s
SmistralDevstral Small 2 24B 24B14.9 GB~44 tok/s
SmistralMagistral Small 2509 24B14.9 GB~44 tok/s
SmistralMistral Small 3.2 24B 24B14.9 GB~44 tok/s
SmistralMagistral Small 2506 23.6B14.9 GB~44 tok/s
Sopenaigpt-oss 20b 20.9B11.3 GB~314 tok/s
SmicrosoftPhi-4 14B 14.7B10.1 GB~68 tok/s
SmistralMinistral 3 14B 14B9.2 GB~74 tok/s
SgoogleGemma 4 12B 12B7.4 GB~88 tok/s
SqwenQwen3.5 9B 9.7B5.8 GB~114 tok/s
SmistralMinistral 3 8B 8.9B6.2 GB~114 tok/s
SibmGranite 4.2 8B 8.8B6.7 GB~106 tok/s
SmetaLlama 3.1 8B Instruct 8B5.9 GB~121 tok/s
SgoogleGemma 4 E4B 8B5.1 GB~130 tok/s
Sai2Olmo 3 7B Instruct 7.3B7 GB~100 tok/s
SgoogleGemma 4 E2B 5.1B3.3 GB~210 tok/s
SqwenQwen3.5 4B 4.7B3.1 GB~230 tok/s
SmistralMinistral 3 3B 3.9B3.1 GB~256 tok/s
SibmGranite 4.2 3B 3.7B3.1 GB~249 tok/s
SmetaLlama 3.2 3B Instruct 3.2B3.1 GB~265 tok/s
ShuggingfaceSmolLM3 3B 3.1B2.6 GB~298 tok/s
SliquidLFM2.5 2.6B 2.7B2 GB~377 tok/s
SqwenQwen3.5 2B 2.3B1.6 GB~496 tok/s
SqwenQwen3.5 0.8B 0.9B0.9 GB~1,133 tok/s
AqwenQwen3.8 27B 27.8B17 GB~37 tok/s
AqwenQwen3.6 27B 27.8B16.5 GB~39 tok/s
BqwenQwen3.6 35B A3B 36B21.2 GB~340 tok/s
BqwenQwen3.5 35B A3B 36B21 GB~344 tok/s
Bai2Olmo 3.1 32B Think 32.2B19.7 GB~32 tok/s
BgoogleGemma 4 31B 31.3B18.8 GB~34 tok/s
BibmGranite 4.2 30B 29.3B19.1 GB~35 tok/s
CmoonshotKimi Linear 48B A3B 49.1B28.4 GB~107 tok/s
CnvidiaNemotron 3.5 Lightning 30B A3B 31.6B24.1 GB~175 tok/s
DmetaLlama 3.3 70B Instruct 70.6B42.4 GB~2 tok/s
36 models do not fit on the RTX 4090
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—
FzaiGLM 4.7 358.3B204.8 GB—
FzaiGLM 5.3 Flash 321.3B176.1 GB—
FdeepseekDeepSeek V4 Flash 0731 304.2B161 GB—
FdeepseekDeepSeek V4 Flash 290.9B166.7 GB—
FtInkling Small 266B149 GB—
FqwenQwen3 235B A22B Thinking 2507 235.1B134.2 GB—
FqwenQwen3 235B A22B Instruct 2507 235.1B134.2 GB—
FminimaxMiniMax M2.5 228.7B131.1 GB—
FminimaxMiniMax M2.7 228.7B131.5 GB—
FcohereCommand A+ 218.8B126.7 GB—
FqwenQwen3.8 Flash Next 180B111.9 GB—
FmistralMistral Medium 3.5 128B 127.7B72.8 GB—
FqwenQwen3.5 122B A10B 125.1B71.8 GB—
FmistralMistral Small 4 119B 119.4B68.1 GB—
Fopenaigpt-oss 120b 116.8B59 GB—
FmetaLlama 4 Scout 17B 16E 108.6B62.7 GB—
FqwenQwen3 Coder Next 79.7B45.7 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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