# AMD Radeon AI PRO R9700 for local LLMs

> 32GB for far less than NVIDIA workstation cards and built for stacking, but no faster per card than an RX 9070 XT.

The R9700 has 32GB of GDDR6 and 640 GB/s of memory bandwidth, which decides how big a model fits and how fast it generates text. It comfortably runs models up to about 35B parameters: the largest in our catalog is Qwen3.6 35B-A3B at Q5_K_M (28GB with 8K context, ~78 tokens/sec). Our top all-round pick for it is Qwen3.8 27B (Q6_K, ~18 tokens/sec).

## Key specs

- Memory: 32GB GDDR6
- Memory bandwidth: 640 GB/s
- Architecture: RDNA 4 (2025)
- Power: 300W
- Typical price: ~$1,800 (checked 2026-10)
- Software: ROCm, Vulkan

## Best models for this GPU

- **Best overall (also coding, reasoning, vision):** Qwen3.8 27B at Q6_K, ~24.8GB with 8K context, ~18 tokens/sec
- **Runner-up (also fastest, largest that fits):** Qwen3.6 35B-A3B at Q5_K_M, ~27.7GB with 8K context, ~78 tokens/sec

## Compatibility (best quantization that fits, 8K context)

| Model | Params | Quant | Memory | Speed | Verdict |
| --- | --- | --- | --- | --- | --- |
| Gemma 4 E4B | 8B | Q8_0 | 10.5GB | ~41 tok/s | Runs well |
| Qwen3.5 9B | 9B | Q8_0 | 12.0GB | ~36 tok/s | Runs well |
| Phi-4 | 14.7B | Q8_0 | 18.3GB | ~26 tok/s | Runs well |
| gpt-oss-20b | 20.9B (3.6B active) | MXFP4 | 15.0GB | ~75 tok/s | Runs well |
| Gemma 4 26B A4B | 26B (3.8B active) | Q6_K | 23.2GB | ~61 tok/s | Runs well |
| Qwen3.8 27B | 27B | Q6_K | 24.8GB | ~18 tok/s | Runs well |
| Gemma 4 31B | 31B | Q5_K_M | 26.0GB | ~18 tok/s | Runs well |
| Qwen3.6 35B-A3B | 35B (3B active) | Q5_K_M | 27.7GB | ~78 tok/s | Runs well |
| GLM-4.5-Air | 106B (12B active) | Q4_K_M | 68.3GB | ~9.2 tok/s | Partial offload |
| Llama 4 Scout | 109B (17B active) | Q4_K_M | 69.5GB | ~6.6 tok/s | Partial offload |
| gpt-oss-120b | 117B (5.1B active) | MXFP4 | 68.3GB | ~23 tok/s | Partial offload |
| Qwen3.5 122B-A10B | 122B (10B active) | Q4_K_M | 77.0GB | ~10 tok/s | Partial offload |
| DeepSeek V4 Flash | 284B (13B active) | - | - | - | Won't fit |
| GLM-5.3-Flash | 320B (18B active) | - | - | - | Won't fit |
| GLM-5.3 | 744B (40B active) | - | - | - | Won't fit |

## Pros
- 32GB per card for less than NVIDIA workstation cards
- Blower cooler for dense multi-GPU builds
- Official ROCm support

## Cons
- 640 GB/s is modest for a 32GB card
- Street price well above the $1,299 MSRP
- Some CUDA-only tools will not run

Full page: https://llamabuilds.ai/gpus/radeon-ai-pro-r9700 · Best models: https://llamabuilds.ai/gpus/radeon-ai-pro-r9700/best-models

Sources: [Wikipedia, Radeon RX 9000 series](https://en.wikipedia.org/wiki/Radeon_RX_9000_series), [Wikipedia, AMD Radeon AI Pro R9000 specifications table](https://en.wikipedia.org/wiki/Template:AMD_Radeon_AI_Pro_R9000)

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Source: https://llamabuilds.ai/gpus/radeon-ai-pro-r9700 · Updated October 14, 2026 · Llama Builds. Speeds marked ~ are estimates from our bandwidth model (https://llamabuilds.ai/methodology); measured results are labeled as such.