Run Jackrong/Qwopus3.6-27B-Coder-Compat-MTP-GGUF locally

License: apache-2.0 ⬇ 414,734 ❤ 115
Parameters0.46B

Jackrong/Qwopus3.6-27B-Coder-Compat-MTP-GGUF is a compact code-focused language model with 0.46 billion parameters, built on the clip architecture. It is released under the apache-2.0 license and has been downloaded 414,734 times.

To run Jackrong/Qwopus3.6-27B-Coder-Compat-MTP-GGUF locally at a 4,096-token context, its quantized versions need between 2.14 GB (F32, lowest quality) and 28.33 GB (Q8_0, highest quality) of memory, weights plus KV cache and a system margin included.

For most users the best balance is F32, needing about 2.14 GB. That means Jackrong/Qwopus3.6-27B-Coder-Compat-MTP-GGUF fits entirely in the VRAM of a 6 GB GPU or larger, running fully on the GPU.

→ Guide: How much VRAM do you need?

All quantizations

Quant.Bits QualityWeights KVTotal Speed~Verdict
F32 16.17 Excellent 0.87 GB 0.47 GB 2.14 GB 461.3 t/s Fits in VRAM
Q3_K_M 234.42 Excellent 12.57 GB 0.47 GB 13.85 GB 4.0 t/s Offload
Q4_K_M 291.9 Excellent 15.66 GB 0.47 GB 16.93 GB 3.2 t/s Offload
Q5_K_M 339.21 Excellent 18.19 GB 0.47 GB 19.47 GB 2.7 t/s Offload
Q6_K 389.49 Excellent 20.89 GB 0.47 GB 22.17 GB 2.4 t/s Offload
Q8_0 504.37 Excellent 27.05 GB 0.47 GB 28.33 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 Jackrong/Qwopus3.6-27B-Coder-Compat-MTP-GGUF?

You need about 2.14 GB of VRAM to run Jackrong/Qwopus3.6-27B-Coder-Compat-MTP-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 Jackrong/Qwopus3.6-27B-Coder-Compat-MTP-GGUF on an 8 GB GPU?

Yes. With 8 GB of VRAM you can run Jackrong/Qwopus3.6-27B-Coder-Compat-MTP-GGUF fully on the GPU using F32 (about 2.14 GB).

Can I run Jackrong/Qwopus3.6-27B-Coder-Compat-MTP-GGUF on a 16 GB GPU?

Yes. With 16 GB of VRAM you can run Jackrong/Qwopus3.6-27B-Coder-Compat-MTP-GGUF fully on the GPU using Q3_K_M (about 13.85 GB).

Can I run Jackrong/Qwopus3.6-27B-Coder-Compat-MTP-GGUF on a 24 GB GPU?

Yes. With 24 GB of VRAM you can run Jackrong/Qwopus3.6-27B-Coder-Compat-MTP-GGUF fully on the GPU using Q6_K (about 22.17 GB).

What is the best quantization for Jackrong/Qwopus3.6-27B-Coder-Compat-MTP-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.