AMD Radeon AI PRO R9700
32 GB · 640 GB/s · 300 W
Prices
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No retailer in this market lists it right now.
What two of them run
Every model in the catalogue, with the best quant for this hardware. Estimates, not measurements.
| Model | Quant | Fits | Memory | Max context | Decode @32k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 27B Alibaba Qwen | Q8_0 | fits | 30.7 GB | 256k | 11tok/sest. | 1078 tok/s | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | Q3_K_M | fits | 54.9 GB | 256k | 39tok/sest. | 2528 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 27B Alibaba Qwen | Q8_0 | fits | 30.3 GB | 256k | 11tok/sest. | 1078 tok/s | – |
| Qwen3 Coder Next Alibaba Qwen | Q5_K_M | fits | 55.3 GB | 256k | 58tok/sest. | 6093 tok/s | chat, coding, agents, long documents |
| gpt-oss 120B OpenAI | MXFP4 | fits | 61.7 GB | 50k84k with q8 cache | 49tok/sest. | 4084 tok/s | chat, coding, agents, long documents |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q3_K_M | fits | 59.4 GB | 253k256k with q8 cache | 33tok/sest. | 2557 tok/s | chat, coding, agents, long documents |
| Gemma 4 31B | Q8_0 | fits | 35.2 GB | 256k | 10tok/sest. | 961 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q3_K_M | fits | 52.8 GB | 375k596k with q8 cache | 53tok/sest. | 2811 tok/s | chat, coding, agents, long documents |
| Qwen 3.6 35B-A3B Alibaba Qwen | Q8_0 | fits | 36.5 GB | 256k | 55tok/sest. | 7698 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q8_0 | fits | 30.3 GB | 256k | 11tok/sest. | 1078 tok/s | – |
| Gemma 4 26B-A4B | Q8_0 | fits | 27.3 GB | 256k | 42tok/sest. | 6848 tok/s | chat, coding, agents, long documents |
| GLM 4.5 Air Z.ai | Q3_K_M | fits | 60.5 GB | 42k77k with q8 cache | 14tok/sest. | 940 tok/s | chat |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q5_K_M | fits | 55.2 GB | 256k | 71tok/sest. | 7250 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q8_0 | fits | 36.5 GB | 256k | 55tok/sest. | 7698 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q8_0 | fits | 32.8 GB | 198k | 30tok/sest. | 4019 tok/s | chat, coding, long documents |
| Devstral Small 2 24B Mistral AI | Q8_0 | fits | 29.8 GB | 232k384k with q8 cache | 12tok/sest. | 1138 tok/s | – |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | fits | 34.3 GB | 256k | 59tok/sest. | 8784 tok/s | chat, coding, agents, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 13.5 GB | 128k | 65tok/sest. | 5747 tok/s | chat, coding, agents, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q8_0 | fits | 50.4 GB | 915k1024k with q8 cache | 60tok/sest. | 6634 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q8_0 | fits | 34.7 GB | 256k | 33tok/sest. | 3540 tok/s | chat, coding, agents |
| Qwen3 32B Alibaba Qwen | Q8_0 | fits | 41.9 GB | 40k | 8tok/sest. | 669 tok/s | – |
| Gemma 4 12B | Q8_0 | fits | 14.1 GB | 256k | 26tok/sest. | 2500 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 11.4 GB | 256k | 33tok/sest. | 3116 tok/s | chat, coding, long documents |
| Mistral Small 3.2 24B Mistral AI | Q8_0 | fits | 29.8 GB | 128k | 12tok/sest. | 1138 tok/s | – |
| Gemma 3 27B | Q8_0 | fits | 31.1 GB | 128k | 11tok/sest. | 1144 tok/s | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q8_0 | fits | 41.9 GB | 112k128k with q8 cache | 8tok/sest. | 768 tok/s | – |
| Llama 3.3 70B Meta | Q5_K_M | fits | 58.0 GB | 45k84k with q8 cache | 6tok/sest. | 363 tok/s | – |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 19.9 GB | 256k | 18tok/sest. | 1731 tok/s | chat |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 21.1 GB | 40k | 17tok/sest. | 1556 tok/s | chat |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 14.1 GB | 128k | 26tok/sest. | 2567 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 14.1 GB | 40k | 26tok/sest. | 2567 tok/s | chat, coding |
| Phi-4 14B Microsoft | Q8_0 | fits | 22.2 GB | 16k | 16tok/sest. | 1564 tok/s | chat |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 6.7 GB | 256k | 63tok/sest. | 5830 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 14.1 GB | 256k | 26tok/sest. | 2479 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q8_0 | fits | 15.2 GB | 128k | 24tok/sest. | 2361 tok/s | chat, coding |
| Gemma 4 E4B | Q8_0 | fits | 10.0 GB | 128k | 38tok/sest. | 3914 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 11.4 GB | 125k | 79tok/sest. | 12804 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 11.6 GB | 128k | 32tok/sest. | 2712 tok/s | chat, coding |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | offload | 75.8 GB | – | 4tok/sest. | 466 tok/s | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | offload | 79.4 GB | – | 8tok/sest. | 1236 tok/s | chat |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 94.4 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 103.2 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- Radeon AI PRO R9700
- Memory
- 32 GB GDDR6
- Memory bus
- 256-bit
- Memory bandwidth
- 640 GB/s
- FP16 compute
- 191 TFLOPS
- Software
- ROCm
- Board power
- 300 W
- PCIe generation
- Gen 5
- PCIe lanes
- x16