Run DeepBeepMeep/Wan2.1 locally
DeepBeepMeep/Wan2.1 is a mid-size language model with 4.84 billion parameters, built on the qwen35 architecture. It has been downloaded 376,736 times.
To run DeepBeepMeep/Wan2.1 locally at a 4,096-token context, its quantized versions need between 6.54 GB (Q4_K_M_BIS, lowest quality) and 8.53 GB (Q4_K_M, highest quality) of memory, weights plus KV cache and a system margin included.
For most users the best balance is Q4_K_M_BIS, needing about 6.54 GB. That means DeepBeepMeep/Wan2.1 fits entirely in the VRAM of an 8 GB GPU or larger, running fully on the GPU.
All quantizations
| Quant. | Bits | Quality | Weights | KV | Total | Speed~ | Verdict |
|---|---|---|---|---|---|---|---|
| Q4_K_M_BIS | 9.3 | Excellent | 5.24 GB | 0.5 GB | 6.54 GB | 76.3 t/s | Fits in VRAM |
| Q4_K_M | 12.83 | Excellent | 7.23 GB | 0.5 GB | 8.53 GB | 6.9 t/s | Offload |
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 DeepBeepMeep/Wan2.1?
You need about 6.54 GB of VRAM to run DeepBeepMeep/Wan2.1 entirely on the GPU using the Q4_K_M_BIS quantization (at a 4,096-token context). Smaller quantizations lower the requirement at the cost of quality.
Can I run DeepBeepMeep/Wan2.1 on an 8 GB GPU?
Yes. With 8 GB of VRAM you can run DeepBeepMeep/Wan2.1 fully on the GPU using Q4_K_M_BIS (about 6.54 GB).
Can I run DeepBeepMeep/Wan2.1 on a 16 GB GPU?
Yes. With 16 GB of VRAM you can run DeepBeepMeep/Wan2.1 fully on the GPU using Q4_K_M (about 8.53 GB).
Can I run DeepBeepMeep/Wan2.1 on a 24 GB GPU?
Yes. With 24 GB of VRAM you can run DeepBeepMeep/Wan2.1 fully on the GPU using Q4_K_M (about 8.53 GB).
What is the best quantization for DeepBeepMeep/Wan2.1?
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.