unsloth
Qwen3.6 35B A3B
Qwen3.6 35B A3B is a 34.7B mixture-of-experts qwen35moe model from unsloth, with about 3.0B parameters active per token. Configured context length is 262,144 tokens. License: apache-2.0. Quant sizes are the GGUF file bytes published on Hugging Face when a file exists.
Parameters34.7B / 3.0B active
Context256K
Attentionhybrid
Licenseapache-2.0
40 layers · 2 KV heads · head dim 256 · 30 linear-attention layers · GGUF repo · config
Quant file sizes
| Quant | File size | Source |
|---|---|---|
| BF16 | 64.6 GB | Hugging Face file bytes |
| UD-Q8_K_XL | 35.8 GB | Hugging Face file bytes |
| Q8_0 | 34.4 GB | Hugging Face file bytes |
| UD-Q6_K_XL | 29.7 GB | Hugging Face file bytes |
| UD-Q6_K | 27.3 GB | Hugging Face file bytes |
| UD-Q5_K_XL | 24.8 GB | Hugging Face file bytes |
| UD-Q5_K_M | 24.6 GB | Hugging Face file bytes |
| UD-Q5_K_S | 23.2 GB | Hugging Face file bytes |
| UD-Q4_K_XL | 20.8 GB | Hugging Face file bytes |
| UD-Q4_K_M | 20.6 GB | Hugging Face file bytes |
| UD-Q4_K_S | 19.5 GB | Hugging Face file bytes |
| UD-IQ4_XS | 16.5 GB | Hugging Face file bytes |
| IQ4_NL | 35.0 GB | Hugging Face file bytes |
| UD-Q3_K_XL | 15.7 GB | Hugging Face file bytes |
| Q3_K_M | 15.5 GB | Hugging Face file bytes |
| UD-IQ3_S | 12.7 GB | Hugging Face file bytes |
| Q3_K_S | 14.3 GB | Hugging Face file bytes |
| UD-IQ3_XXS | 12.3 GB | Hugging Face file bytes |
| UD-Q2_K_XL | 11.4 GB | Hugging Face file bytes |
| UD-IQ2_XXS | 10.0 GB | Hugging Face file bytes |
| UD-IQ1_M | 9.36 GB | Hugging Face file bytes |
On common machines
| Device | Verdict | Quant | Speed |
|---|---|---|---|
| GeForce RTX 4060 Ti 8GB | Expert offload | UD-Q4_K_M | 75–102 |
| GeForce RTX 3060 12GB | Tight fit | UD-IQ2_XXS | 180–246 |
| GeForce RTX 4060 Ti 16GB | Tight fit | UD-IQ3_S | 117–160 |
| GeForce RTX 4090 | Tight fit | UD-Q4_K_XL | 264–359 |
| GeForce RTX 5090 | Tight fit | UD-Q6_K | 364–497 |
| Apple M4 Pro | Tight fit | UD-IQ4_XS | 88–120 |
| Apple M5 | Tight fit | UD-IQ2_XXS | 77–104 |
| CPU only · DDR5-5600 | Runs on CPU | UD-Q5_K_S | 21–29 |
Smallest devices that fit it fully
- GeForce RTX 5070 — Tight fit, UD-IQ2_XXS, 336–459 tok/s
- GeForce RTX 4070 Ti — Tight fit, UD-IQ2_XXS, 252–344 tok/s
- GeForce RTX 4070 Super — Tight fit, UD-IQ2_XXS, 252–344 tok/s
- GeForce RTX 4070 — Tight fit, UD-IQ2_XXS, 252–344 tok/s
- GeForce RTX 3080 Ti — Tight fit, UD-IQ2_XXS, 457–623 tok/s
- GeForce RTX 3080 12GB — Tight fit, UD-IQ2_XXS, 457–623 tok/s
Run it
Commands for the GeForce RTX 4060 Ti 16GB estimate (UD-IQ3_S).
llama.cpp
llama-server -hf unsloth/Qwen3.6-35B-A3B-GGUF:UD-IQ3_S -c 8192 -ngl 40
Ollama
ollama run qwen3.6
LM Studio
lms get unsloth/Qwen3.6-35B-A3B-GGUF # Then load quant UD-IQ3_S