readygpu

NVIDIA GeForce RTX 4080 Super vs NVIDIA RTX PRO 4000 Blackwell

For running models locally, priced in the US. At 64k context the first runs 31 models fully in memory, the second 48.

In short

The NVIDIA RTX PRO 4000 Blackwell has more memory for models: 24 GB against 16 GB. At 64k context the NVIDIA RTX PRO 4000 Blackwell runs 48 of the models we track fully in memory and the NVIDIA GeForce RTX 4080 Super 31; only the NVIDIA RTX PRO 4000 Blackwell holds Qwen 3.8 27B. On the models both run fully in memory, the NVIDIA GeForce RTX 4080 Super is about 1.1× as fast as the NVIDIA RTX PRO 4000 Blackwell (estimated, median across models).

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

NVIDIA GeForce RTX 4080 Super

$1,300

Amazon

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NVIDIA RTX PRO 4000 Blackwell

Not priced here

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Specifications

SpecNVIDIA GeForce RTX 4080 SuperNVIDIA RTX PRO 4000 Blackwell
GPUGeForce RTX 4080 SuperRTX PRO 4000 Blackwell
Memory16 GB GDDR6X24 GB GDDR7
Memory bus256-bit192-bit
Memory bandwidth736 GB/s672 GB/s
FP16 compute104 TFLOPS46.9 TFLOPS
SoftwareCUDACUDA
Board power320 W145 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 4080 SuperNVIDIA RTX PRO 4000 Blackwell
Qwen 3.8 27Boffload19tok/sQ4_K_M
Qwen 3.6 27Boffload17tok/sQ5_K_M
Qwen 3.6 35B-A3Boffload77tok/sQ4_K_M
Qwen 3.5 27Boffload20tok/sQ4_K_M
Gemma 4 26B-A4Boffload52tok/sUD-Q5_K_M
Qwen 3.5 35B-A3Boffload77tok/sQ4_K_M
GLM 4.7 Flashoffload38tok/sQ4_K_M
Nemotron 3.5 Lightning 30B-A3Boffload94tok/sMXFP4
gpt-oss 20B68tok/sMXFP462tok/sMXFP4
Gemma 4 12B32tok/sQ8_030tok/sQ8_0
Qwen 3.5 9B39tok/sQ8_036tok/sQ8_0
Gemma 3 27Boffload19tok/sQ4_K_M
Ministral 3 14Boffload19tok/sQ6_K
Qwen3 14Boffload18tok/sQ6_K
DeepSeek R1 0528 Qwen3 8B31tok/sQ4_K_M23tok/sQ8_0
Qwen3 8B31tok/sQ4_K_M23tok/sQ8_0
Phi-4 14Boffload18tok/sQ5_K_M
Qwen 3.5 4B68tok/sQ8_062tok/sQ8_0
Ministral 3 8B30tok/sQ5_K_M23tok/sQ8_0
Granite 4.2 8Boffload21tok/sQ8_0
Gemma 4 E4B45tok/sQ8_041tok/sQ8_0
LFM2.5 8B-A1B64tok/sQ8_058tok/sQ8_0
Llama 3.1 8B30tok/sQ6_K27tok/sQ6_K
Qwen2.5 0.5B342tok/sQ8_0312tok/sQ8_0
Qwen3.5 0.8B279tok/sQ8_0255tok/sQ8_0
Qwen3.5 2B202tok/sQ5_K_M184tok/sQ5_K_M
DeepSeek R1 Distill Qwen 1.5B121tok/sQ8_0110tok/sQ8_0
MiniCPM5 2B83tok/sQ8_076tok/sQ8_0
Spark X2.5 4B83tok/smlx-4bit76tok/smlx-4bit
Mellum2.1 12B A2.5B Thinking75tok/sQ8_069tok/sQ8_0
Kimi VL A3B Thinking 250669tok/sQ4_K_M49tok/sQ8_0
FrogNano 4B 260967tok/sQ8_061tok/sQ8_0
LFM2.5 2.6B66tok/sQ8_060tok/sQ8_0
LFM2.5 VL 3B66tok/sQ8_060tok/sQ8_0
Kimi VL A3B65tok/smlx-5bit47tok/smlx-8bit
granite vision 4.1 4b51tok/sQ8_046tok/sQ8_0
granite 4.2 3b49tok/sQ8_045tok/sQ8_0
Ministral 3 3B Instruct 251243tok/sQ8_039tok/sQ8_0
GLM 4 9B 041442tok/smlx-5bit38tok/smlx-5bit
DeepSeek R1 Distill Qwen 7B39tok/sQ8_035tok/sQ8_0
GLM 4.6V Flash36tok/sQ8_033tok/sQ8_0
GLM 4.1V 9B Thinking32tok/smlx-8bit29tok/smlx-8bit
DeepSeek R1 Distill Llama 8B30tok/sQ6_K24tok/sQ8_0
Ministral 3 8B Reasoning 251230tok/sQ5_K_M23tok/sQ8_0
LFM2.5 24B A2Boffload36tok/sQ5_K_M
Muse Glimmer 30Boffload20tok/sQ5_K_M
Ministral 3 14B Reasoning 2512offload19tok/sQ6_K
DeepSeek R1 Distill Qwen 14Boffload18tok/sQ5_K_M
Qwen 3.5 122B-A10Bwon't runoffload
Gemma 4 31Boffloadoffload
Qwen3 Coder Nextwon't runoffload
Mistral Small 4 119Boffloadoffload
Devstral Small 2 24Boffloadoffload
Qwen3 Next 80B-A3Bwon't runoffload
Kimi Linear 48B-A3Boffloadoffload
Qwen3 Coder 30B-A3Boffloadoffload
Qwen3 32Boffloadoffload
Mistral Small 3.2 24Boffloadoffload
DeepSeek R1 Distill Qwen 32Boffloadoffload
Devstral Small 2507offloadoffload
Magistral Small 2506offloadoffload
Magistral Small 2507offloadoffload
Magistral Small 2509offloadoffload
Qwen3.8 27B OBLITERATEDoffloadoffload
granite 4.2 30boffloadoffload
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
Nemotron 3 Super 120B-A12Bwon't runwon't run
gpt-oss 120Bwon't runwon't run
GLM 4.5 Airwon't runwon't run
Llama 3.3 70Bwon't runwon't run
DeepSeek R1won't runwon't run
DeepSeek R1 0528won't runwon't run
DeepSeek R1 Distill Llama 70Bwon't runwon't run
DeepSeek R1 Zerowon't runwon't run
DeepSeek V3won't runwon't run
DeepSeek V3 0324won't runwon't run
DeepSeek V3.1won't runwon't run
DeepSeek V3.1 Terminuswon'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 4.5won't runwon't run
GLM 4.5Vwon't runwon't run
GLM 4.6won't runwon't run
GLM 4.6Vwon't runwon't run
GLM 4.7won't runwon't run
GLM 5won'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 Dev 72Bwon'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 4080 Super or the NVIDIA RTX PRO 4000 Blackwell?
Choose the NVIDIA RTX PRO 4000 Blackwell to run bigger models. Choose the NVIDIA GeForce RTX 4080 Super for speed.
Which can run bigger models, the NVIDIA GeForce RTX 4080 Super or the NVIDIA RTX PRO 4000 Blackwell?
At 64k context the NVIDIA RTX PRO 4000 Blackwell runs 48 of the models we track fully in memory and the NVIDIA GeForce RTX 4080 Super 31; only the NVIDIA RTX PRO 4000 Blackwell holds Qwen 3.8 27B.
Which is faster for local AI, the NVIDIA GeForce RTX 4080 Super or the NVIDIA RTX PRO 4000 Blackwell?
On the models both run fully in memory, the NVIDIA GeForce RTX 4080 Super is about 1.1× as fast as the NVIDIA RTX PRO 4000 Blackwell (estimated, median across models).

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