AMD Radeon RX 6700 XT for local LLMs
Written by Jakub Rusinowski · Last updated
With 12 GB of GDDR6 at 384 GB/s, the RX 6700 XT runs 76 catalogued models at Q4_K_M with 8K context. The largest that fits is Qwen 3 14B (~11.1 GB), and the top pick is Cosmos 3 Nano.
12 GB of GDDR6 on a 192-bit bus, 384 GB/s. No speed calibration for RDNA 2: fit verdicts only.
Models that run on the RX 6700 XT
Q4_K_M, 8K context, 12 GB usable. Ranked by quality and speed.
| Model | Memory · marker = 12 GB | VRAM | Speed |
|---|---|---|---|
| Cosmos 3 Nano Cosmos 3 | 10.5 GB | — | |
| Ministral 3 14B Ministral 3 | 9.3 GB | — | |
| DeepSeek R1 Distill Qwen 14B DeepSeek R1 | 10.6 GB | — | |
| Mellum2.1 12B Thinking Mellum2.1 | 9 GB | — | |
| Gemma 4 12B (Unified) Gemma 4 | 8.7 GB | — | |
| Mistral NeMo 12B Mistral Family | 9.4 GB | — | |
| Gemma 3 12B Instruct Gemma 3 | 9.1 GB | — | |
| Bielik PL 11B v3.0 Instruct Bielik | 7.4 GB | — | |
| Llama 3.2 Vision 11B Llama 3.2 Vision | 8.5 GB | — | |
| Llama 3.2 11B Vision Instruct Llama 3.2 Family | 8.5 GB | — | |
| Falcon 3 10B Instruct Falcon 3 | 8.4 GB | — | |
| Qwen 3.5 9B Qwen 3.5 | 6.6 GB | — |
Buy it or rent the same memory
Buy the card, or rent a GPU with the same memory by the hour to try models first.
or compare on Vast.ai from $0.35/hr (typical low · varies)
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Speed vs other GPUs
Llama 3.1 8B, Q4_K_M. Estimated ranges. How this is calculated
Specifications
Specs last updated 2026-10-07.
- Memory
- 12 GB GDDR6
- Memory bandwidth
- 384 GB/s
- Memory bus
- 192-bit
- Architecture
- RDNA 2 Navi 22
- Series
- RX 6000-series
- Board power
- 230 W
- Release year
- 2021
- Compute backends
- ROCM, VULKAN
- Usable for models
- 12 GB
Similar GPUs
Frequently asked questions
Can the AMD Radeon RX 6700 XT run local LLMs?
Yes. With 12 GB (12 GB usable by a model) it runs 76 of the catalogued models at Q4_K_M with 8K context; the largest is Qwen 3 14B, needing about 11.1 GB.
How fast is the AMD Radeon RX 6700 XT for AI inference?
This site has no speed calibration for the RDNA 2 Navi 22 architecture, so it publishes fit verdicts for this card but no tokens-per-second estimate. Llama 3.3 70B does not fit: it needs about 44 GB against 12 GB usable.
What LLMs can I run on 12 GB?
Among the best that fit: Cosmos 3 Nano, Ministral 3 14B, DeepSeek R1 Distill Qwen 14B, Mellum2.1 12B Thinking, Gemma 4 12B (Unified).