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- A Reddit user shares their experience using Qwen3.6-27B-Q4_K_M with a 7900XTX GPU, noting that they are not seeing usable speeds and performance issues.
- The user mentions being unable to fit the entire model in VRAM due to context size constraints and quantization choices. They have tried different settings but still face slow token generation and high VRAM usage.
- They found success by reducing the cache precision to Q8, allowing them to use all of the available VRAM with a smaller context window (64k tokens) and achieving a more usable speed of around 50 tokens per second.
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### Takeaways
– Users are encountering performance issues when using high-precision models like Qwen3.6-27B-Q4_K_M on the 7900XTX.
– Context size and cache precision settings significantly impact performance and VRAM utilization.
– Reducing model precision to a lower level (e.g., Q8) can sometimes allow fitting larger contexts within available resources, improving token generation speed.
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