readygpu

AMD Radeon AI PRO R9700 vs NVIDIA RTX PRO 4000 Blackwell

For running models locally, priced in the UK. At 32k context the first runs 61 models fully in memory, the second 57.

In short

The AMD Radeon AI PRO R9700 has more memory for models: 32 GB against 24 GB. At 32k context the AMD Radeon AI PRO R9700 runs 61 of the models we track fully in memory and the NVIDIA RTX PRO 4000 Blackwell 57; only the AMD Radeon AI PRO R9700 holds Kimi Linear 48B-A3B. On the models both run fully in memory, the NVIDIA RTX PRO 4000 Blackwell is about 1.2× as fast as the AMD Radeon AI PRO R9700 (estimated, median across models).

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

AMD Radeon AI PRO R9700

£1,674

eBay

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NVIDIA RTX PRO 4000 Blackwell

Not priced here

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Specifications

SpecAMD Radeon AI PRO R9700NVIDIA RTX PRO 4000 Blackwell
GPURadeon AI PRO R9700RTX PRO 4000 Blackwell
Memory32 GB GDDR624 GB GDDR7
Memory bus256-bit192-bit
Memory bandwidth640 GB/s672 GB/s
FP16 compute191 TFLOPS46.9 TFLOPS
SoftwareROCmCUDA
Board power300 W145 W
PCIe generationGen 5Gen 5
PCIe lanesx16x16

What each runs

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

ModelAMD Radeon AI PRO R9700NVIDIA RTX PRO 4000 Blackwell
Qwen 3.8 27B11tok/sQ8_018tok/sQ5_K_M
Qwen 3.6 27B11tok/sQ8_019tok/sQ5_K_M
Gemma 4 31B12tok/sQ6_K19tok/sQ4_K_M
Qwen 3.6 35B-A3B64tok/sQ6_K96tok/sQ4_K_M
Qwen 3.5 27B11tok/sQ8_019tok/sQ5_K_M
Gemma 4 26B-A4B42tok/sQ8_056tok/sUD-Q6_K
Qwen 3.5 35B-A3B67tok/sQ6_K97tok/sQ4_K_M
GLM 4.7 Flash36tok/sQ6_K47tok/sQ5_K_M
Devstral Small 2 24B12tok/sQ8_019tok/sQ5_K_M
Nemotron 3.5 Lightning 30B-A3B68tok/sUD-Q5_K_M102tok/sMXFP4
Kimi Linear 48B-A3B99tok/sQ4_K_Moffload
gpt-oss 20B65tok/sMXFP477tok/sMXFP4
Qwen3 Coder 30B-A3B37tok/sQ6_K50tok/sQ4_K_M
Qwen3 32B11tok/sQ5_K_Moffload
Gemma 4 12B26tok/sQ8_031tok/sQ8_0
Qwen 3.5 9B33tok/sQ8_039tok/sQ8_0
Mistral Small 3.2 24B12tok/sQ8_019tok/sQ5_K_M
DeepSeek R1 Distill Qwen 32B11tok/sQ5_K_Moffload
Gemma 3 27B11tok/sQ8_019tok/sQ5_K_M
Ministral 3 14B18tok/sQ8_021tok/sQ8_0
Qwen3 14B17tok/sQ8_020tok/sQ8_0
DeepSeek R1 0528 Qwen3 8B26tok/sQ8_031tok/sQ8_0
Qwen3 8B26tok/sQ8_031tok/sQ8_0
Phi-4 14B16tok/sQ8_019tok/sQ8_0
Qwen 3.5 4B63tok/sQ8_074tok/sQ8_0
Ministral 3 8B26tok/sQ8_031tok/sQ8_0
Granite 4.2 8B24tok/sQ8_028tok/sQ8_0
Gemma 4 E4B38tok/sQ8_045tok/sQ8_0
LFM2.5 8B-A1B79tok/sQ8_094tok/sQ8_0
Llama 3.1 8B32tok/sQ6_K38tok/sQ6_K
Qwen2.5 0.5B377tok/sQ8_0446tok/sQ8_0
Qwen3.5 0.8B285tok/sQ8_0338tok/sQ8_0
Qwen3.5 2B190tok/sQ5_K_M224tok/sQ5_K_M
DeepSeek R1 Distill Qwen 1.5B124tok/sQ8_0147tok/sQ8_0
MiniCPM5 2B86tok/sQ8_0102tok/sQ8_0
Spark X2.5 4B82tok/smlx-4bit97tok/smlx-4bit
LFM2.5 2.6B72tok/sQ8_085tok/sQ8_0
LFM2.5 VL 3B72tok/sQ8_085tok/sQ8_0
Mellum2.1 12B A2.5B Thinking67tok/sQ8_079tok/sQ8_0
FrogNano 4B 260961tok/sQ8_073tok/sQ8_0
granite vision 4.1 4b56tok/sQ8_066tok/sQ8_0
granite 4.2 3b54tok/sQ8_063tok/sQ8_0
Kimi VL A3B Thinking 250651tok/sQ8_061tok/sQ8_0
Kimi VL A3B49tok/smlx-8bit58tok/smlx-8bit
Ministral 3 3B Instruct 251249tok/sQ8_058tok/sQ8_0
LFM2.5 24B A2B44tok/sQ8_056tok/sQ6_K
GLM 4 9B 041437tok/smlx-5bit43tok/smlx-5bit
DeepSeek R1 Distill Qwen 7B35tok/sQ8_042tok/sQ8_0
GLM 4.6V Flash31tok/sQ8_037tok/sQ8_0
DeepSeek R1 Distill Llama 8B27tok/sQ8_033tok/sQ8_0
GLM 4.1V 9B Thinking27tok/smlx-8bit32tok/smlx-8bit
Ministral 3 8B Reasoning 251226tok/sQ8_031tok/sQ8_0
Ministral 3 14B Reasoning 251218tok/sQ8_021tok/sQ8_0
DeepSeek R1 Distill Qwen 14B16tok/sQ8_019tok/sQ8_0
Qwen3.8 27B OBLITERATED15tok/smlx-4bit18tok/smlx-4bit
Muse Glimmer 30B15tok/sQ6_K17tok/sQ6_K
granite 4.2 30b12tok/sQ5_K_Moffload
Devstral Small 250712tok/sQ8_019tok/sQ5_K_M
Magistral Small 250612tok/sQ8_019tok/sQ5_K_M
Magistral Small 250712tok/sQ8_019tok/sQ5_K_M
Magistral Small 250912tok/sQ8_019tok/sQ5_K_M
Qwen 3.5 122B-A10Boffloadoffload
Qwen3 Coder Nextoffloadoffload
Nemotron 3 Super 120B-A12Boffloadwon't run
Mistral Small 4 119Boffloadoffload
GLM 4.5 Airoffloadoffload
Qwen3 Next 80B-A3Boffloadoffload
Llama 3.3 70Boffloadwon't run
DeepSeek R1 Distill Llama 70Boffloadwon't run
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 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 AMD Radeon AI PRO R9700 or the NVIDIA RTX PRO 4000 Blackwell?
Choose the AMD Radeon AI PRO R9700 to run bigger models. Choose the NVIDIA RTX PRO 4000 Blackwell for speed.
Which can run bigger models, the AMD Radeon AI PRO R9700 or the NVIDIA RTX PRO 4000 Blackwell?
At 32k context the AMD Radeon AI PRO R9700 runs 61 of the models we track fully in memory and the NVIDIA RTX PRO 4000 Blackwell 57; only the AMD Radeon AI PRO R9700 holds Kimi Linear 48B-A3B.
Which is faster for local AI, the AMD Radeon AI PRO R9700 or the NVIDIA RTX PRO 4000 Blackwell?
On the models both run fully in memory, the NVIDIA RTX PRO 4000 Blackwell is about 1.2× as fast as the AMD Radeon AI PRO R9700 (estimated, median across models).

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