Run unsloth/Qwen3.6-27B-GGUF locally
unsloth/Qwen3.6-27B-GGUF 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 578,691 times.
To run unsloth/Qwen3.6-27B-GGUF locally at a 4,096-token context, its quantized versions need between 2.14 GB (F16, lowest quality) and 52.25 GB (BF16, highest quality) of memory, weights plus KV cache and a system margin included.
For most users the best balance is F32, needing about 2.99 GB. That means unsloth/Qwen3.6-27B-GGUF 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 |
| F32 | 0.55 | Very low | 1.72 GB | 0.47 GB | 2.99 GB | 233.0 t/s | Fits in VRAM |
| IQ2_XXS | 2.79 | Low | 8.74 GB | 0.47 GB | 10.02 GB | 5.7 t/s | Offload |
| IQ2_M | 3.23 | Low | 10.1 GB | 0.47 GB | 11.38 GB | 4.9 t/s | Offload |
| Q2_K_XL | 3.52 | Fair | 11.04 GB | 0.47 GB | 12.31 GB | 4.5 t/s | Offload |
| IQ3_XXS | 3.57 | Fair | 11.17 GB | 0.47 GB | 12.45 GB | 4.5 t/s | Offload |
| Q3_K_S | 3.68 | Fair | 11.51 GB | 0.47 GB | 12.78 GB | 4.3 t/s | Offload |
| Q3_K_M | 4.04 | Fair | 12.65 GB | 0.47 GB | 13.93 GB | 4.0 t/s | Offload |
| Q3_K_XL | 4.31 | Good | 13.48 GB | 0.47 GB | 14.75 GB | 3.7 t/s | Offload |
| IQ4_XS | 4.59 | Good | 14.38 GB | 0.47 GB | 15.65 GB | 3.5 t/s | Offload |
| Q4_0 | 4.7 | Good | 14.71 GB | 0.47 GB | 15.98 GB | 3.4 t/s | Offload |
| Q4_K_S | 4.72 | Good | 14.77 GB | 0.47 GB | 16.04 GB | 3.4 t/s | Offload |
| IQ4_NL | 4.78 | Good | 14.97 GB | 0.47 GB | 16.24 GB | 3.3 t/s | Offload |
| Q4_K_M | 5.0 | Very good | 15.66 GB | 0.47 GB | 16.94 GB | 3.2 t/s | Offload |
| Q4_1 | 5.13 | Very good | 16.07 GB | 0.47 GB | 17.34 GB | 3.1 t/s | Offload |
| Q4_K_XL | 5.24 | Very good | 16.4 GB | 0.47 GB | 17.68 GB | 3.0 t/s | Offload |
| Q5_K_S | 5.64 | Very good | 17.66 GB | 0.47 GB | 18.93 GB | 2.8 t/s | Offload |
| Q5_K_M | 5.8 | Very good | 18.17 GB | 0.47 GB | 19.44 GB | 2.8 t/s | Offload |
| Q5_K_XL | 5.96 | Very good | 18.66 GB | 0.47 GB | 19.94 GB | 2.7 t/s | Offload |
| Q6_K | 6.7 | Excellent | 20.98 GB | 0.47 GB | 22.25 GB | 2.4 t/s | Offload |
| Q6_K_XL | 7.63 | Excellent | 23.88 GB | 0.47 GB | 25.15 GB | — | Insufficient |
| Q8_0 | 8.51 | Excellent | 26.63 GB | 0.47 GB | 27.91 GB | — | Insufficient |
| Q8_K_XL | 10.51 | Excellent | 32.9 GB | 0.47 GB | 34.17 GB | — | Insufficient |
| BF16 | 16.28 | Excellent | 50.98 GB | 0.47 GB | 52.25 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 unsloth/Qwen3.6-27B-GGUF?
You need about 2.99 GB of VRAM to run unsloth/Qwen3.6-27B-GGUF entirely on the GPU using the F32 quantization (at a 4,096-token context). Smaller quantizations lower the requirement at the cost of quality.
Can I run unsloth/Qwen3.6-27B-GGUF on an 8 GB GPU?
Yes. With 8 GB of VRAM you can run unsloth/Qwen3.6-27B-GGUF fully on the GPU using F32 (about 2.99 GB).
Can I run unsloth/Qwen3.6-27B-GGUF on a 16 GB GPU?
Yes. With 16 GB of VRAM you can run unsloth/Qwen3.6-27B-GGUF fully on the GPU using Q4_0 (about 15.98 GB).
Can I run unsloth/Qwen3.6-27B-GGUF on a 24 GB GPU?
Yes. With 24 GB of VRAM you can run unsloth/Qwen3.6-27B-GGUF fully on the GPU using Q6_K (about 22.25 GB).
What is the best quantization for unsloth/Qwen3.6-27B-GGUF?
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.