readygpu

NVIDIA GeForce RTX 4090 vs NVIDIA GeForce RTX 5090

For running models locally, priced in the UK. At 8k context the first runs 51 models fully in memory, the second 52.

In short

The NVIDIA GeForce RTX 5090 has more memory for models: 32 GB against 24 GB. At 8k context the NVIDIA GeForce RTX 5090 runs 52 of the models we track fully in memory and the NVIDIA GeForce RTX 4090 51; only the NVIDIA GeForce RTX 5090 holds Kimi Linear 48B-A3B. On the models both run fully in memory, the NVIDIA GeForce RTX 5090 is about 1.8× as fast as the NVIDIA GeForce RTX 4090 (estimated, median across models). In the UK the NVIDIA GeForce RTX 4090 costs £6,015 at Amazon and the NVIDIA GeForce RTX 5090 £5,000 at eBay: the NVIDIA GeForce RTX 5090 is £1,015 cheaper.

Updated . Speeds are estimates; how they are worked out.

NVIDIA GeForce RTX 4090

£6,015

Amazon

Add to build
NVIDIA GeForce RTX 5090

£5,000

eBay

Add to build

Specifications

SpecNVIDIA GeForce RTX 4090NVIDIA GeForce RTX 5090
GPUGeForce RTX 4090GeForce RTX 5090
Memory24 GB GDDR6X32 GB GDDR7
Memory bus384-bit512-bit
Memory bandwidth1,008 GB/s1,792 GB/s
FP16 compute165 TFLOPS209 TFLOPS
SoftwareCUDACUDA
Board power450 W575 W
PCIe generationGen 4Gen 5
PCIe lanesx16x16

What each runs

Estimated decode speed with the most precise quant that fits each one est.

ModelNVIDIA GeForce RTX 4090NVIDIA GeForce RTX 5090
Qwen 3.8 27B28tok/sUD-Q6_K37tok/sQ8_0
Qwen 3.6 27B27tok/sQ6_K38tok/sQ8_0
Gemma 4 31B27tok/sQ5_K_M42tok/sQ6_K
Qwen 3.6 35B-A3B179tok/sQ4_K_M237tok/sQ6_K
Qwen 3.5 27B27tok/sQ6_K38tok/sQ8_0
Gemma 4 26B-A4B95tok/sUD-Q6_K147tok/sQ8_0
Qwen 3.5 35B-A3B181tok/sQ4_K_M253tok/sQ6_K
GLM 4.7 Flash94tok/sQ5_K_M117tok/sQ8_0
Devstral Small 2 24B30tok/sQ6_K42tok/sQ8_0
gpt-oss 20B142tok/sMXFP4253tok/sMXFP4
Qwen3 Coder 30B-A3B128tok/sQ5_K_M204tok/sQ6_K
Kimi Linear 48B-A3Boffload343tok/sQ4_K_M
Qwen3 32B29tok/sQ4_K_M38tok/sQ6_K
Gemma 4 12B48tok/sQ8_085tok/sQ8_0
Qwen 3.5 9B64tok/sQ8_0113tok/sQ8_0
Mistral Small 3.2 24B30tok/sQ6_K42tok/sQ8_0
DeepSeek R1 Distill Qwen 32B28tok/sQ4_K_M38tok/sQ6_K
Gemma 3 27B27tok/sQ6_K37tok/sQ8_0
Ministral 3 14B40tok/sQ8_071tok/sQ8_0
Qwen3 14B37tok/sQ8_065tok/sQ8_0
DeepSeek R1 0528 Qwen3 8B63tok/sQ8_0112tok/sQ8_0
Qwen3 8B63tok/sQ8_0112tok/sQ8_0
Phi-4 14B36tok/sQ8_064tok/sQ8_0
Qwen 3.5 4B130tok/sQ8_0231tok/sQ8_0
Ministral 3 8B62tok/sQ8_0109tok/sQ8_0
Granite 4.2 8B59tok/sQ8_0104tok/sQ8_0
Gemma 4 E4B74tok/sQ8_0131tok/sQ8_0
LFM2.5 8B-A1B256tok/sQ8_0455tok/sQ8_0
Llama 3.1 8B82tok/sQ6_K145tok/sQ6_K
Qwen2.5 0.5B989tok/sQ8_01759tok/sQ8_0
Qwen3.5 0.8B671tok/sQ8_01193tok/sQ8_0
Qwen3.5 2B402tok/sQ5_K_M715tok/sQ5_K_M
DeepSeek R1 Distill Qwen 1.5B294tok/sQ8_0522tok/sQ8_0
MiniCPM5 2B206tok/sQ8_0366tok/sQ8_0
LFM2.5 2.6B185tok/sQ8_0329tok/sQ8_0
LFM2.5 VL 3B185tok/sQ8_0329tok/sQ8_0
LFM2.5 24B A2B154tok/sQ6_K238tok/sQ8_0
granite vision 4.1 4b146tok/sQ8_0259tok/sQ8_0
granite 4.2 3b137tok/sQ8_0243tok/sQ8_0
Mellum2.1 12B A2.5B Thinking133tok/sQ8_0236tok/sQ8_0
Kimi VL A3B107tok/smlx-8bit190tok/smlx-8bit
DeepSeek R1 Distill Qwen 7B73tok/sQ8_0130tok/sQ8_0
DeepSeek R1 Distill Llama 8B65tok/sQ8_0116tok/sQ8_0
Ministral 3 8B Reasoning 251262tok/sQ8_0109tok/sQ8_0
GLM 4.6V Flash61tok/sQ8_0108tok/sQ8_0
GLM 4.1V 9B Thinking52tok/smlx-8bit92tok/smlx-8bit
DeepSeek R1 Distill Qwen 14B36tok/sQ8_064tok/sQ8_0
Devstral Small 250735tok/sQ5_K_M42tok/sQ8_0
Magistral Small 250735tok/sQ5_K_M42tok/sQ8_0
Magistral Small 250935tok/sQ5_K_M42tok/sQ8_0
Magistral Small 250630tok/sQ6_K42tok/sQ8_0
granite 4.2 30b27tok/sQ5_K_M42tok/sQ6_K
Qwen 3.5 122B-A10Boffloadoffload
Qwen3 Coder Nextoffloadoffload
Nemotron 3 Super 120B-A12Bwon't runoffload
Mistral Small 4 119Boffloadoffload
GLM 4.5 Airoffloadoffload
Qwen3 Next 80B-A3Boffloadoffload
Nemotron 3.5 Lightning 30B-A3Boffloadoffload
Llama 3.3 70Boffloadoffload
DeepSeek R1 Distill Llama 70Boffloadoffload
DeepSeek V4 Flashwon't runwon't run
GLM 5.3 Flashwon't runwon't run
Qwen 3.8 Flash Nextwon't runwon't run
MiniMax M2.7won't runwon't run
gpt-oss 120Bwon't runwon't run
DeepSeek R1won't runwon't run
DeepSeek R1 0528won't runwon't run
DeepSeek V3 0324won't runwon't run
DeepSeek V3.1won't runwon't run
DeepSeek V3.2won't runwon't run
DeepSeek V4 Flash 0731won't runwon't run
DeepSeek V4 Flash Vision Expwon't runwon't run
Devstral 2 123B Instruct 2512won't runwon't run
GLM 4.5Vwon't runwon't run
GLM 4.6Vwon't runwon't run
GLM 4.7won't runwon't run
GLM 5.1won't runwon't run
GLM 5.2won't runwon't run
GLM 5.3won't runwon't run
Kimi K2won't runwon't run
Kimi K2 Instruct 0905won't runwon't run
Kimi K2 Thinkingwon't runwon't run
Kimi K2.5won't runwon't run
MiniMax M2won't runwon't run
MiniMax M2.1won't runwon't run
MiniMax M2.5won't runwon't run
MiniMax M3won't runwon't run
Mistral Medium 3.5 128Bwon't runwon't run

Questions

Which is better for local AI, the NVIDIA GeForce RTX 4090 or the NVIDIA GeForce RTX 5090?
Choose the NVIDIA GeForce RTX 5090 to run bigger models. Choose the NVIDIA GeForce RTX 5090 for speed. Choose the NVIDIA GeForce RTX 5090 to spend less.
Which can run bigger models, the NVIDIA GeForce RTX 4090 or the NVIDIA GeForce RTX 5090?
At 8k context the NVIDIA GeForce RTX 5090 runs 52 of the models we track fully in memory and the NVIDIA GeForce RTX 4090 51; only the NVIDIA GeForce RTX 5090 holds Kimi Linear 48B-A3B.
Which is faster for local AI, the NVIDIA GeForce RTX 4090 or the NVIDIA GeForce RTX 5090?
On the models both run fully in memory, the NVIDIA GeForce RTX 5090 is about 1.8× as fast as the NVIDIA GeForce RTX 4090 (estimated, median across models).
What is the price difference between the NVIDIA GeForce RTX 4090 and the NVIDIA GeForce RTX 5090?
In the UK the NVIDIA GeForce RTX 4090 costs £6,015 at Amazon and the NVIDIA GeForce RTX 5090 £5,000 at eBay: the NVIDIA GeForce RTX 5090 is £1,015 cheaper.

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