RTX 4090 vs RTX 5090 for local LLMs

The RTX 5090 runs more models well (49 vs 48 of 69), thanks to its 32 GB of memory. On models that fit both, the RTX 5090 should be about 78% faster, because generation speed follows memory bandwidth (1792 vs 1008 GB/s).

NVIDIA RTX 4090

  • 24 GB VRAM
  • 1008 GB/s bandwidth
  • 48/69 models run well
  • $1,599 at launch

NVIDIA RTX 5090

  • 32 GB VRAM
  • 1792 GB/s bandwidth
  • 49/69 models run well
  • $1,999 at launch

Prices are US launch prices (MSRP) for comparison; street prices change daily. Links go to Amazon, where we earn a commission at no cost to you.

Every model, side by side

Best quant that fits and estimated speed at 8K context.

ModelRTX 4090RTX 5090
Qwen3 0.6BFP16 · ~403 tok/sFP16 · ~717 tok/s
Gemma 3 1BFP16 · ~302 tok/sFP16 · ~538 tok/s
Llama 3.2 1BFP16 · ~244 tok/sFP16 · ~434 tok/s
Qwen3 1.7BFP16 · ~149 tok/sFP16 · ~265 tok/s
Llama 3.2 3BFP16 · ~94 tok/sFP16 · ~167 tok/s
Phi-3.5 Mini 3.8BFP16 · ~79 tok/sFP16 · ~141 tok/s
Phi-4 Mini 3.8BFP16 · ~79 tok/sFP16 · ~140 tok/s
Qwen3 4BFP16 · ~75 tok/sFP16 · ~134 tok/s
Gemma 3 4BFP16 · ~70 tok/sFP16 · ~125 tok/s
Mistral 7B v0.3FP16 · ~42 tok/sFP16 · ~74 tok/s
Qwen2.5 7BFP16 · ~40 tok/sFP16 · ~71 tok/s
Qwen2.5 Coder 7BFP16 · ~40 tok/sFP16 · ~71 tok/s
DeepSeek R1 Distill Qwen 7BFP16 · ~40 tok/sFP16 · ~71 tok/s
Llama 3.1 8BFP16 · ~38 tok/sFP16 · ~67 tok/s
Granite 3.3 8BFP16 · ~37 tok/sFP16 · ~66 tok/s
Qwen3 8BFP16 · ~37 tok/sFP16 · ~66 tok/s
DeepSeek R1 0528 Qwen3 8BFP16 · ~37 tok/sFP16 · ~66 tok/s
Gemma 2 9BFP16 · ~33 tok/sFP16 · ~58 tok/s
Gemma 4 12BQ8_0 · ~48 tok/sFP16 · ~45 tok/s
Mistral Nemo 12BQ8_0 · ~47 tok/sFP16 · ~44 tok/s
Gemma 3 12BQ8_0 · ~47 tok/sFP16 · ~44 tok/s
Qwen2.5 14BQ8_0 · ~39 tok/sFP16 · ~37 tok/s
Phi-4 14BQ8_0 · ~39 tok/sFP16 · ~37 tok/s
Phi-4 Reasoning 14BQ8_0 · ~39 tok/sFP16 · ~37 tok/s
Qwen3 14BQ8_0 · ~38 tok/sFP16 · ~36 tok/s
Qwen2.5 Coder 14BQ8_0 · ~38 tok/sFP16 · ~36 tok/s
DeepSeek R1 Distill Qwen 14BQ8_0 · ~38 tok/sFP16 · ~36 tok/s
gpt-oss 20BQ8_0 · ~158 tok/sQ8_0 · ~281 tok/s
Mistral Small 24BQ6_K · ~31 tok/sQ8_0 · ~43 tok/s
Devstral Small 24BQ6_K · ~31 tok/sQ8_0 · ~43 tok/s
Magistral Small 24BQ6_K · ~31 tok/sQ8_0 · ~43 tok/s
Mistral Small 3.2 24BQ6_K · ~31 tok/sQ8_0 · ~42 tok/s
Gemma 4 26B-A4BQ6_K · ~194 tok/sQ8_0 · ~266 tok/s
Gemma 2 27BQ5_K_M · ~31 tok/sQ8_0 · ~37 tok/s
Gemma 3 27BQ5_K_M · ~31 tok/sQ8_0 · ~37 tok/s
Qwen3.8 27BQ6_K · ~27 tok/sQ8_0 · ~36 tok/s
Qwen3.6 27BQ6_K · ~27 tok/sQ8_0 · ~36 tok/s
Qwen3 30B-A3BQ5_K_M · ~258 tok/sQ6_K · ~397 tok/s
Qwen3 Coder 30B-A3BQ5_K_M · ~258 tok/sQ6_K · ~397 tok/s
GLM-4.7 Flash 30B-A3BQ5_K_M · ~283 tok/sQ6_K · ~437 tok/s
Gemma 4 31BQ4_K_M · ~32 tok/sQ6_K · ~42 tok/s
Nemotron 3 Nano 30B-A3BQ5_K_M · ~243 tok/sQ6_K · ~375 tok/s
Qwen2.5 32BQ4_K_M · ~30 tok/sQ6_K · ~40 tok/s
DeepSeek R1 Distill Qwen 32BQ4_K_M · ~30 tok/sQ6_K · ~40 tok/s
Qwen3 32BQ4_K_M · ~30 tok/sQ6_K · ~40 tok/s
QwQ 32BQ4_K_M · ~30 tok/sQ6_K · ~40 tok/s
Qwen2.5 Coder 32BQ4_K_M · ~30 tok/sQ6_K · ~40 tok/s
Qwen3.6 35B-A3BQ4_K_M · ~333 tok/sQ6_K · ~437 tok/s
Mixtral 8x7BQ2_K · ~125 tok/sQ4_K_M · ~137 tok/s
Llama 3.1 70BToo bigQ2_K · ~41 tok/s
Llama 3.3 70BToo bigQ2_K · ~41 tok/s
DeepSeek R1 Distill Llama 70BToo bigQ2_K · ~41 tok/s
Qwen2.5 72BToo bigQ2_K · ~39 tok/s
Qwen3 Coder Next 80B-A3BToo bigQ2_K · ~956 tok/s
GLM-4.5-Air 106B-A12BToo bigToo big
Llama 4 Scout 17B-16EToo bigToo big
gpt-oss 120BToo bigToo big
Qwen3.8 Flash NextToo bigToo big
Qwen3 235B-A22BToo bigToo big
DeepSeek V4 Flash 284B-A13BToo bigToo big
GLM-5.3 Flash 320B-A18BToo bigToo big
MiniMax M3 428B-A23BToo bigToo big
GLM-5 744B-A40BToo bigToo big
GLM-5.3Too bigToo big
DeepSeek V4.1 FlashToo bigToo big
Mistral Large 4 1T-A52BToo bigToo big
DeepSeek V4 Pro 1.6T-A49BToo bigToo big
Qwen3.8 2.4T-A95BToo bigToo big
Kimi K3.1 Pro 2.8T-A104BToo bigToo big