Qwen3.6 35B-A3B
A smaller sparse Qwen model for coding agents and vision-language tasks.
- Published size
- 35B+
- Active parameters
- 3B
- Context window
- 256K native
- Architecture
- MoE · vision
- License
- Review model card
Deployment considerations
Compare its full checkpoint memory with dense models, rather than treating the 3B activated count as the deployment size.
The language model has 35B total and 3B active parameters, plus a vision encoder. Native context is 262,144 tokens; extended contexts require separate configuration.
GPU memory estimates and minimum / recommended configurations are pending. This profile does not contain measured deployment results.
GPU requirements
- Minimum
- —GPU / VRAM · pending
- Recommended
- —GPU / VRAM · pending
Memory estimates and tested configurations will appear here after checkpoint review and deployment testing.
No invented leaderboards.
Latency, throughput, and cost per token will appear here after a reproducible run. Until then, this page helps you understand the model—not predict its performance.
Qwen3.6 35B-A3B deployment FAQ
How much GPU memory does Qwen3.6 35B-A3B need?
The full checkpoint weight footprint is pending review. Minimum and recommended GPU configurations will be added after testing; the model name or active parameter count alone is not a memory requirement.
Has BenchGrid benchmarked Qwen3.6 35B-A3B?
Not yet. This profile contains publisher specifications and calculated weight-memory estimates. We do not currently publish measured latency, throughput, or cost per token for this model.
Where do these specifications come from?
The specifications are based on the official Alibaba model card linked on this page. Memory estimates use the stated total parameter count, including inactive experts for MoE models. Nominal model sizes are labeled with ~.
Explore your compute options.
Check available hardware, quotas, and current pricing with the provider. These links are not verified deployments or performance recommendations.
