Radeon RX 7600 XT
16 GB GDDR6 · 288 GB/s · 190 W
RX 7600 XT 16 GB · 64 GB RAM → gpt-oss-20b
GPU · AMD
RX 7600 XT for local LLMs: which models run?
With 16 GB of VRAM and 288 GB/s of bandwidth, the RX 7600 XT runs models up to about gpt-oss-20b entirely on the GPU.
- VRAM16 GB GDDR6
- Bandwidth288 GB/s
- Board power190 W
- ArchitectureRDNA 3
Specifications
- VRAM
- 16 GB
- Memory type
- GDDR6
- Memory bus
- 128-bit
- Bandwidth
- 288 GB/s
- Board power
- 190 W
- Backends
- Vulkan
- Interface
- PCIe 4.0 x8
- Released
- January 2024
- Segment
- Consumer
- FP16 compute
- Not available
Official specData updated 24 days agoSource: AMD specifications
What the RX 7600 XT runs
| gpt-oss-20bMXFP4 · 8K~12.9 GB · 59–100 tok/s estimate | Excellent |
|---|---|
| Gemma 2 9B ITQ8_0 · 8K~12.7 GB · 17–25 tok/s estimate | Excellent |
| Qwen3 8BQ8_0 · 8K~10.5 GB · 19–29 tok/s estimate | Excellent |
| Llama 3.1 8B InstructQ8_0 · 8K~10.1 GB · 20–30 tok/s estimate | Excellent |
| DeepSeek R1 Distill Llama 8BQ8_0 · 8K~10.1 GB · 20–30 tok/s estimate | Excellent |
| Qwen2.5 7B InstructQ8_0 · 8K~9.2 GB · 21–32 tok/s estimate | Excellent |
| Mistral 7B Instruct v0.3Q8_0 · 8K~9.1 GB · 22–33 tok/s estimate | Excellent |
| Gemma 3 4B ITQ8_0 · 8K~5.4 GB · 40–62 tok/s estimate | Excellent |
| Qwen3 4BQ8_0 · 8K~6.1 GB · 35–55 tok/s estimate | Excellent |
| Phi-4 Mini Instruct 3.8BQ8_0 · 8K~5.9 GB · 37–58 tok/s estimate | Excellent |
| Llama 3.2 3B InstructQ8_0 · 8K~5.1 GB · 44–69 tok/s estimate | Excellent |
| Qwen3 1.7BQ8_0 · 8K~3.6 GB · 71–114 tok/s estimate | Excellent |
| Llama 3.2 1B InstructQ8_0 · 8K~2.5 GB · 114–182 tok/s estimate | Excellent |
| Qwen3 0.6BQ8_0 · 8K~2.5 GB · 131–230 tok/s estimate | Excellent |
| Mistral Small 3.2 24B InstructIQ4_XS · 8K~14.6 GB · 14–20 tok/s estimate | Compatible |
| Qwen3 14BQ6_K · 8K~14 GB · 14–21 tok/s estimate | Compatible |
| DeepSeek R1 Distill Qwen 14BQ6_K · 8K~14.2 GB · 14–21 tok/s estimate | Compatible |
| Qwen2.5 14B InstructQ6_K · 8K~14.2 GB · 14–21 tok/s estimate | Compatible |
| Phi-4 14BQ6_K · 8K~14.1 GB · 14–21 tok/s estimate | Compatible |
| Mistral Nemo 12B InstructQ8_0 · 8K~14.8 GB · 13–20 tok/s estimate | Compatible |
| Gemma 3 12B ITQ8_0 · 8K~14.1 GB · 14–21 tok/s estimate | Compatible |
| Qwen3 30B-A3BQ3_K_M · 8K~15.3 GB · 55–107 tok/s estimate | Compatible with limits |
| Gemma 3 27B ITQ3_K_M · 8K~15.3 GB · 13–19 tok/s estimate | Compatible with limits |
| Mixtral 8x7B InstructQ3_K_M · 8K~21.5 GB · 8–16 tok/s estimate | CPU/GPU offload |
| Qwen3 32BQ3_K_M · 8K~18.5 GB · 4–8 tok/s estimate | CPU/GPU offload |
| DeepSeek R1 Distill Qwen 32BQ3_K_M · 8K~18.5 GB · 4–8 tok/s estimate | CPU/GPU offload |
| Qwen2.5 32B InstructQ3_K_M · 8K~18.5 GB · 4–8 tok/s estimate | CPU/GPU offload |
| Qwen2.5 Coder 32B InstructQ3_K_M · 8K~18.5 GB · 4–8 tok/s estimate | CPU/GPU offload |
| QwQ 32BQ3_K_M · 8K~18.5 GB · 4–8 tok/s estimate | CPU/GPU offload |
| Qwen3 Coder 30B-A3B InstructQ3_K_M · 8K~15.9 GB · 39–93 tok/s estimate | CPU/GPU offload |
| Gemma 2 27B ITQ3_K_M · 8K~16.4 GB · 7.5–14 tok/s estimate | CPU/GPU offload |
| gpt-oss-120bMXFP4 · 8K~63.2 GB · 8–17 tok/s estimate | Possible but slow |
| Llama 4 Scout 17B-16E InstructQ3_K_M · 8K~55.6 GB · 2.5–5.5 tok/s estimate | Possible but slow |
| Qwen2.5 72B InstructQ3_K_M · 8K~38.2 GB · 0.8–1.6 tok/s estimate | Not recommended |
| Llama 3.3 70B InstructQ3_K_M · 8K~36.9 GB · 0.9–1.7 tok/s estimate | Not recommended |
| DeepSeek R1 Distill Llama 70BQ3_K_M · 8K~36.9 GB · 0.9–1.7 tok/s estimate | Not recommended |
| DeepSeek R1 (671B)Q8_0 · 8K~699 GB · No data | Incompatible |
| Qwen3 235B-A22BQ8_0 · 8K~247 GB · No data | Incompatible |
For each model, the highest-precision quantization that runs entirely in fast memory; otherwise the one with the best result. Speeds are ranges; "estimate" unless a benchmark exists for this exact hardware.
EstimateData updated 24 days agoSource: Run LLM Locally engine
Limits in plain words
16 GB of VRAM holds the weights and KV cache of models up to about gpt-oss-20b at Q4_K_M. Bigger models spill into system RAM and slow down sharply: generation speed is then limited by RAM bandwidth, not by the GPU.
Where to buy a RX 7600 XT
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Frequently asked questions
Which LLMs can the RX 7600 XT run?
Entirely on the GPU: Qwen3 30B-A3B (Q3_K_M), Gemma 3 27B IT (Q3_K_M), Mistral Small 3.2 24B Instruct (IQ4_XS), gpt-oss-20b (MXFP4), Qwen3 14B (Q6_K), DeepSeek R1 Distill Qwen 14B (Q6_K), Qwen2.5 14B Instruct (Q6_K), Phi-4 14B (Q6_K). Larger models need CPU/GPU offload.
Can the RX 7600 XT run a 70B model?
Not recommended: a 70B model at Q4_K_M needs about 45 GB; the RX 7600 XT has 16 GB.
How is the speed estimated?
Token generation reads every active weight once per token, so it is limited by memory bandwidth (288 GB/s here). We apply an efficiency range per backend and label the result as an estimate until real benchmarks exist.