Qwen3.5-4B: API Pricing, Context Window & Benchmarks
Qwen3.5-4B is a language model from Qwen, released in March 2026, with multimodal input.
Qwen3.5-4B is a 4 billion parameter vision-language model using Gated DeltaNet hybrid architecture with a 3:1 ratio of linear attention to full softmax attention. It supports 262K native context length and delivers strong performance for
Qwen3.5-4B benchmarks
Rankings
Quality Tracker
Qwen3.5-4B Performance Across Datasets
Scores sourced from the model's scorecard, paper, or official blog posts
llm-stats.com - Fri Aug 07 2026Qwen3.5-4B model size
Qwen3.5-4B has 4 billion parameters. See how it compares to other models in the same parameter range.
Qwen3.5-4B API
Available from the model provider
Qwen3.5-4B has an official provider API. It is not currently routed through the LLM Stats gateway.
Read the official API documentationQwen3.5-4B latency
Qwen3.5-4B time to first token, sustained output throughput, and failed-request rate from live API traffic over the trailing 7 days.
Qwen3.5-4B examples
Recent arena outputs from Qwen3.5-4B, picked from the highest-ranked matchups.
Qwen3.5-4B license
Qwen3.5-4B is released under the Apache 2.0 license, which permits commercial use, has 4.0B parameters.
- License
- Apache 2.0
- Commercial use allowed
- Parameters
- 4.0B
Apache License 2.0 - allows commercial use
Qwen3.5-4B resources
Official sources for Qwen3.5-4B: api documentation, official playground, source repository, model weights.
Qwen3.5-4B vs other models
The most-compared alternatives to Qwen3.5-4B are Kimi K2 0905, Llama 3.1 Nemotron Ultra 253B v1, Qwen3 VL 235B A22B Instruct. Open any pair side-by-side for benchmarks, pricing, context, and latency.
Models like Qwen3.5-4B
Models ranked just above and below Qwen3.5-4B by LLM Stats score.
FAQ
Common questions about Qwen3.5-4B.