AMD Radeon AI PRO R9700 — Local LLM Performance & Compatibility
作者： Jakub Rusinowski · 最后更新： 2026年9月19日
AMD的32 GB工作站显卡：与RX 9070 XT相同的Navi 48核心，显存翻倍，640 GB/s、300 W，四个DisplayPort 2.1输出。两张卡可得64 GB，价格远低于一张96 GB的NVIDIA显卡。购买前需要确认ROCm支持情况。
Technical Specifications
| VRAM | 32 GB |
| Memory Bandwidth | 640 GB/s |
| TDP | 300 W |
| Architecture | RDNA 4 Navi 48 |
| Release Year | 2025 |
| MSRP at Launch | $1,299 |
| Inference Speed (Llama 3.1 8B Q4_K_M) | 42–87 tok/s (estimated) |
| Inference Speed (Llama 3.3 70B Q4_K_M) | Does not fit — needs ~44 GB of 32 GB usable |
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LLMs Compatible with 32 GB VRAM
All models below run comfortably in 32 GB VRAM with Q4_K_M quantization.
| Command R Family | Command R (35B) · 22 GB VRAM · Q4_K_M · ollama run command-r |
| Qwen 3.5 | Qwen 3.5 35B-A3B · 22 GB VRAM · Q4_K_M · ollama run qwen3.5:35b-a3b |
| Qwen 3.6 | Qwen 3.6 35B-A3B · 22 GB VRAM · Q4_K_M · ollama run qwen3.6:35b-a3b |
| Nex-N2 | Nex-N2 mini · 22 GB VRAM · Q4_K_M · nex-n2 |
| Yi 1.5 Family | Yi 1.5 34B Chat · 22 GB VRAM · Q4_K_M · ollama run yi:34b |
| Qwen 3 | Qwen 3 32B · 21 GB VRAM · Q4_K_M · ollama run qwen3:32b |
| Aya Expanse | Aya Expanse 32B · 20 GB VRAM · Q4_K_M · ollama run aya-expanse:32b |
| DeepSeek R1 | DeepSeek R1 Distill Qwen 32B · 20 GB VRAM · Q4_K_M · ollama run deepseek-r1:32b |
56 more families also fit 32 GB — browse the full model library.
Best Use Cases
- 32 GB workstation AI
- ROCm
- dual-card 64 GB builds
FAQ
Can the AMD Radeon AI PRO R9700 run local LLMs?
Yes — the AMD Radeon AI PRO R9700 has 32 GB VRAM and runs AMD的32 GB工作站显卡：与RX 9070 XT相同的Navi 48核心，显存翻倍，640 GB/s、300 W，四个DisplayPort 2.1输出。两张卡可得64 GB，价格远低于一张96 GB的NVIDIA显卡。购买前需要确认R
How fast is the AMD Radeon AI PRO R9700 for AI inference?
The AMD Radeon AI PRO R9700 is estimated to run Llama 3.1 8B at 42–87 tok/s with Q4_K_M quantization. Llama 3.3 70B does not fit: it needs about 44 GB against 32 GB usable. These are modelled estimates, not measurements — see /en/methodology.
What LLMs can I run on 32 GB VRAM?
With 32 GB you can run: Command R Family, Qwen 3.5, Qwen 3.6, Nex-N2, Yi 1.5 Family. Use Ollama for the easiest setup: ollama run llama3.1:8b.
Compare Similar GPUs
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- NVIDIA GeForce RTX 3090 Ti (24 GB, 0 t/s)
VRAM Tier
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