Run HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Aggressive locally
HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Aggressive is a large language model with 26.9 billion parameters, built on the qwen35 architecture. It is released under the apache-2.0 license and has been downloaded 537,352 times.
To run HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Aggressive locally at a 4,096-token context, its quantized versions need between 2.14 GB (F16, lowest quality) and 31.04 GB (Q8_K_P, highest quality) of memory, weights plus KV cache and a system margin included.
For most users the best balance is F16, needing about 2.14 GB. That means HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Aggressive fits entirely in the VRAM of a 6 GB GPU or larger, running fully on the GPU.
All quantizations
| Quant. | Bits | Quality | Weights | KV | Total | Speed~ | Verdict |
|---|---|---|---|---|---|---|---|
| F16 | 0.28 | Very low | 0.86 GB | 0.47 GB | 2.14 GB | 463.0 t/s | Fits in VRAM |
| IQ2_M | 2.98 | Low | 9.32 GB | 0.47 GB | 10.59 GB | 5.4 t/s | Offload |
| Q2_K_P | 3.43 | Fair | 10.73 GB | 0.47 GB | 12.0 GB | 4.7 t/s | Offload |
| IQ3_XS | 3.56 | Fair | 11.15 GB | 0.47 GB | 12.42 GB | 4.5 t/s | Offload |
| IQ3_M | 3.74 | Fair | 11.72 GB | 0.47 GB | 12.99 GB | 4.3 t/s | Offload |
| Q3_K_P | 4.25 | Good | 13.32 GB | 0.47 GB | 14.59 GB | 3.8 t/s | Offload |
| IQ4_XS | 4.49 | Good | 14.05 GB | 0.47 GB | 15.32 GB | 3.6 t/s | Offload |
| Q4_K_P | 5.22 | Very good | 16.33 GB | 0.47 GB | 17.61 GB | 3.1 t/s | Offload |
| Q5_K_P | 6.19 | Very good | 19.38 GB | 0.47 GB | 20.66 GB | 2.6 t/s | Offload |
| Q6_K_P | 6.89 | Excellent | 21.56 GB | 0.47 GB | 22.84 GB | 2.3 t/s | Offload |
| Q8_K_P | 9.51 | Excellent | 29.77 GB | 0.47 GB | 31.04 GB | — | Insufficient |
KV cache computed from the model's exact architecture. Speed is a rough estimate bounded by memory bandwidth.
Frequently asked questions
How much VRAM do you need to run HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Aggressive?
You need about 2.14 GB of VRAM to run HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Aggressive entirely on the GPU using the F16 quantization (at a 4,096-token context). Smaller quantizations lower the requirement at the cost of quality.
Can I run HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Aggressive on an 8 GB GPU?
Yes. With 8 GB of VRAM you can run HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Aggressive fully on the GPU using F16 (about 2.14 GB).
Can I run HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Aggressive on a 16 GB GPU?
Yes. With 16 GB of VRAM you can run HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Aggressive fully on the GPU using IQ4_XS (about 15.32 GB).
Can I run HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Aggressive on a 24 GB GPU?
Yes. With 24 GB of VRAM you can run HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Aggressive fully on the GPU using Q6_K_P (about 22.84 GB).
What is the best quantization for HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Aggressive?
If memory allows, higher bits-per-weight means better quality. A common sweet spot is a Q4_K_M or Q5_K_M quantization, which keeps most of the quality while roughly halving the memory versus 8-bit. Pick the highest quantization that still fits in your VRAM.