Which AI models run on a AMD Radeon RX 7900 XT?
With 20 GB of VRAM, here are the popular models you can run locally (4,096-token context, ~32.0 GB system RAM assumed), ranked by popularity.
The AMD Radeon RX 7900 XT comes with 20 GB of VRAM. Among the popular GGUF models we track, it can run 34 of them entirely in VRAM — including Llama-3.2-1B-Instruct-Q8_0-GGUF, Qwen3-4B-GGUF, gpt-oss-20b-GGUF.
Larger models such as Qwen3-Coder-Next-GGUF still run on a AMD Radeon RX 7900 XT but require offloading part of the model to system RAM, which lowers speed. Models that exceed both VRAM and RAM are not listed.
| Model | Size | Quant. | Quality | Memory | Speed~ | Verdict |
|---|---|---|---|---|---|---|
| hugging-quants/Llama-3.2-1B-Instruct-Q8_0-GGUF | 1.24B | Q8_0 | Excellent | 2.57 GB | 325.1 t/s | Fits in VRAM |
| Qwen/Qwen3-4B-GGUF | 4.02B | Q8_0 | Excellent | 5.75 GB | 100.3 t/s | Fits in VRAM |
| unsloth/gpt-oss-20b-GGUF | 20.91B | F16 | Very good | 13.83 GB | 31.1 t/s | Fits in VRAM |
| janhq/Jan-v3.5-4B-gguf | 4.41B | GGUF | Excellent | 10.04 GB | 48.6 t/s | Fits in VRAM |
| bartowski/gemma-2-2b-it-GGUF | 2.61B | F32 | Excellent | 11.33 GB | 41.0 t/s | Fits in VRAM |
| MaziyarPanahi/Qwen3-0.6B-GGUF | 0.75B | GGUF | Excellent | 2.62 GB | 284.6 t/s | Fits in VRAM |
| MaziyarPanahi/Qwen3-14B-GGUF | 14.77B | Q6_K | Excellent | 13.94 GB | 35.4 t/s | Fits in VRAM |
| MaziyarPanahi/Qwen3-8B-GGUF | 8.19B | GGUF | Excellent | 17.44 GB | 26.2 t/s | Fits in VRAM |
| MaziyarPanahi/Qwen3-32B-GGUF | 32.76B | Q3_K_L | Good | 19.7 GB | 24.8 t/s | Fits in VRAM |
| MaziyarPanahi/Qwen3-1.7B-GGUF | 2.03B | GGUF | Excellent | 5.28 GB | 105.5 t/s | Fits in VRAM |
| MaziyarPanahi/Qwen3-30B-A3B-GGUF | 30.53B | Q3_K_L | Fair | 18.27 GB | 27.0 t/s | Fits in VRAM |
| bartowski/Meta-Llama-3.1-8B-Instruct-GGUF | 8.03B | Q8_0 | Excellent | 10.12 GB | 50.3 t/s | Fits in VRAM |
| Qwen/Qwen2.5-1.5B-Instruct-GGUF | 1.78B | GGUF | Excellent | 4.76 GB | 120.6 t/s | Fits in VRAM |
| unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF | 30.53B | Q4_K_XL | Good | 19.92 GB | 24.3 t/s | Fits in VRAM |
| MaziyarPanahi/Phi-3.5-mini-instruct-GGUF | 3.82B | Q8_0 | Excellent | 5.53 GB | 105.8 t/s | Fits in VRAM |
| Qwen/Qwen2.5-3B-Instruct-GGUF | 3.4B | GGUF | Excellent | 8.02 GB | 63.2 t/s | Fits in VRAM |
| bartowski/Llama-3.2-3B-Instruct-GGUF | 3.21B | F16 | Excellent | 7.66 GB | 66.8 t/s | Fits in VRAM |
| Qwen/Qwen2.5-0.5B-Instruct-GGUF | 0.63B | GGUF | Excellent | 2.36 GB | 339.1 t/s | Fits in VRAM |
| MaziyarPanahi/Qwen3-4B-Instruct-2507-GGUF | 4.02B | GGUF | Excellent | 9.27 GB | 53.3 t/s | Fits in VRAM |
| LiquidAI/LFM2.5-8B-A1B-GGUF | 8.47B | BF16 | Excellent | 17.99 GB | 25.3 t/s | Fits in VRAM |
| MaziyarPanahi/Mistral-7B-Instruct-v0.3-GGUF | 7.25B | GGUF | Excellent | 15.6 GB | 29.6 t/s | Fits in VRAM |
| MaziyarPanahi/gemma-3-4b-it-GGUF | 3.88B | GGUF | Excellent | 8.98 GB | 55.3 t/s | Fits in VRAM |
| MaziyarPanahi/Meta-Llama-3-8B-Instruct-GGUF | 8.03B | GGUF | Excellent | 17.13 GB | 26.7 t/s | Fits in VRAM |
| MaziyarPanahi/Qwen2.5-7B-Instruct-GGUF | 7.62B | GGUF | Excellent | 16.32 GB | 28.2 t/s | Fits in VRAM |
| MaziyarPanahi/Phi-4-mini-instruct-GGUF | 3.84B | GGUF | Excellent | 8.9 GB | 55.9 t/s | Fits in VRAM |
| MaziyarPanahi/Yi-Coder-1.5B-Chat-GGUF | 1.48B | GGUF | Excellent | 4.14 GB | 145.4 t/s | Fits in VRAM |
| MaziyarPanahi/DeepSeek-R1-0528-Qwen3-8B-GGUF | 8.19B | GGUF | Excellent | 17.44 GB | 26.2 t/s | Fits in VRAM |
| MaziyarPanahi/Mistral-Nemo-Instruct-2407-GGUF | 12.25B | Q8_0 | Excellent | 14.62 GB | 33.0 t/s | Fits in VRAM |
| MaziyarPanahi/Llama-3-8B-Instruct-32k-v0.1-GGUF | 8.03B | GGUF | Excellent | 17.13 GB | 26.7 t/s | Fits in VRAM |
| MaziyarPanahi/gemma-3-1b-it-GGUF | 1.0B | GGUF | Excellent | 3.15 GB | 214.0 t/s | Fits in VRAM |
| MaziyarPanahi/Meta-Llama-3.1-70B-Instruct-GGUF | 70.55B | IQ1_S | Very low | 19.14 GB | 28.0 t/s | Fits in VRAM |
| TheBloke/Mistral-7B-Instruct-v0.2-GGUF | 7.24B | Q8_0 | Excellent | 9.27 GB | 55.8 t/s | Fits in VRAM |
| MaziyarPanahi/Yi-Coder-9B-Chat-GGUF | 8.83B | GGUF | Excellent | 18.68 GB | 24.3 t/s | Fits in VRAM |
| MaziyarPanahi/gemma-3-12b-it-GGUF | 11.77B | Q8_0 | Excellent | 14.11 GB | 34.3 t/s | Fits in VRAM |
| unsloth/Qwen3-Coder-Next-GGUF | 79.67B | Q4_1 | Very good | 51.73 GB | 1.1 t/s | Offload |
| Qwen/Qwen2.5-Coder-32B-Instruct-GGUF | 32.76B | Q5_K_M | Excellent | 46.89 GB | 1.2 t/s | Offload |
| MaziyarPanahi/Mixtral-8x22B-v0.1-GGUF | 140.62B | Q2_K | Low | 50.2 GB | 1.0 t/s | Offload |
| MaziyarPanahi/Llama-3.3-70B-Instruct-GGUF | 70.55B | Q5_K_M | Very good | 51.37 GB | 1.1 t/s | Offload |
"Fits in VRAM" = fast, fully on GPU. "Offload" = part on system RAM, slower. Speed is a rough estimate.
Frequently asked questions
How much VRAM does the AMD Radeon RX 7900 XT have?
The AMD Radeon RX 7900 XT has 20 GB of VRAM, which determines how large a model it can run entirely on the GPU.
What is the best LLM to run on a AMD Radeon RX 7900 XT?
Among popular models, hugging-quants/Llama-3.2-1B-Instruct-Q8_0-GGUF runs well on a AMD Radeon RX 7900 XT using the Q8_0 quantization (about 2.57 GB). Larger models trade speed for capability via RAM offloading.
Can a AMD Radeon RX 7900 XT run a 7–8B model?
Yes. A 7–8B model like Qwen3-8B-GGUF fits entirely in the 20 GB of a AMD Radeon RX 7900 XT (GGUF).
Can a AMD Radeon RX 7900 XT run a 13–14B model?
Yes. A 13–14B model like Qwen3-14B-GGUF fits entirely in the 20 GB of a AMD Radeon RX 7900 XT (Q6_K).
Can a AMD Radeon RX 7900 XT run a 70B model?
Yes. A 70B model like Meta-Llama-3.1-70B-Instruct-GGUF fits entirely in the 20 GB of a AMD Radeon RX 7900 XT (IQ1_S).