Qwen3.6-35B-A3B
Qwen3.6-35B-A3B by Alibaba Qwen (35B parameters, MoE with 3B active per token). At Q4_K_M with an 8K context it needs about 21.4 GiB of memory. The April 2026 refresh of Qwen3.5-35B-A3B: the same 3B-active MoE design and memory needs, aimed at coding and agents.
Last updated: 2026-10-13
Model facts
Run it
ollama run qwen3.6:35b
Memory needed
Weights + KV cache + runtime overhead, in GiB. Lower quantization = less memory, slightly lower quality.
| Quantization | 4K context | 8K context | 32K context |
|---|---|---|---|
| Q4_K_M | 21.3 GiB | 21.4 GiB | 21.9 GiB |
| Q5_K_M | 24.9 GiB | 25.0 GiB | 25.5 GiB |
| Q6_K | 28.8 GiB | 28.9 GiB | 29.3 GiB |
| Q8_0 | 36.9 GiB | 37.0 GiB | 37.5 GiB |
| FP16 | 69.0 GiB | 69.1 GiB | 69.6 GiB |
Which hardware runs it
Best quantization that fits each device with a 8K context. Estimates, not benchmarks. See the methodology.
Frequently asked questions
How much VRAM does Qwen3.6-35B-A3B need?
With an 8K context, about 21.4 GiB at Q4_K_M and 37.0 GiB at Q8_0 (weights + KV cache + runtime overhead). Longer contexts need more memory for the KV cache.
Can Qwen3.6-35B-A3B run on an GeForce RTX 4090?
Yes. Qwen3.6-35B-A3B fits on the GeForce RTX 4090 (24 GB) at Q4_K_M with an 8K context, using about 21.4 GiB, at an estimated 388 tokens/s.
Can I run Qwen3.6-35B-A3B on a Mac?
Yes. Qwen3.6-35B-A3B fits on the M3 Ultra (96 GB) at FP16 with an 8K context, using about 69.1 GiB, at an estimated 89 tokens/s.
Can Qwen3.6-35B-A3B be used commercially?
Qwen3.6-35B-A3B is released under Apache-2.0. The licence allows commercial use (read its conditions).
Sources
- https://github.com/QwenLM/Qwen3.8/blob/main/README.md
- https://huggingface.co/Qwen/Qwen3.6-35B-A3B/blob/main/LICENSE
- https://huggingface.co/Qwen/Qwen3.6-35B-A3B
- https://huggingface.co/Qwen/Qwen3.6-35B-A3B/resolve/main/config.json
- https://huggingface.co/api/models/Qwen/Qwen3.6-35B-A3B?expand[]=safetensors
- https://ollama.com/library/qwen3.6/tags