Qwen3 VL 235B A22B Instruct
Routed across multiple providers, which may include Alibaba, a Chinese entity; provider-specific privacy and logging guarantees may vary. Qwen3 Vision‑Language model (235B MoE, ≈22B active) tuned for instruction following and grounded visual QA. Excels at image understanding, dense OCR, charts/diagrams, and multi‑image context.
- Vision
Pricing
Auto routing · per 1M tokens- Input
- $0.30
- Output
- $1.90
Specifications
- Context window
- 131.1K
- Max output
- 32.8K
- Parameters
- 235B / 22B
- Total / active
- Avg output (7d)
- 196 tokens
- Longer than 12% of models
Benchmarks
Benchmarks
Sourced from Artificial Analysis.
Intelligence Index
9.9
Agentic work
T²-Bench Telecom (legacy)
Legacy fallback · Conversational AI agents in dual-control scenarios
35.1%
Better than 43% of models compared
Document reasoning
AA-LCR v1.1
Long context reasoning with updated grading
32.7%
Better than 32% of models compared
Reasoning
HLE
Humanity's Last Exam
6.6%
Better than 40% of models compared
IFBench
Instruction-following benchmark
42.7%
Better than 45% of models compared
CritPt
Research-level physics reasoning
0.0%
Coding
Terminal-Bench Hard (legacy)
Legacy fallback · Agentic coding and terminal use
6.8%
Better than 37% of models compared
LiveCodeBench
Contamination-free coding benchmark
59.4%
Better than 66% of models compared
Math
AIME 2025
American Invitational Mathematics Examination 2025
70.7%
Better than 65% of models compared
Knowledge
MMLU-Pro
Professional and academic subject knowledge
82.3%
Better than 80% of models compared
AA-Omniscience Accuracy
Proportion of correctly answered questions
18.6%
AA-Omniscience Hallucination Rate
Rate of incorrect answers among non-correct responses
87.1%
Legacy benchmarks
GPQA Diamond (legacy)
Graduate-level scientific reasoning
71.2%
Better than 50% of models compared
AA-LCR (unversioned / legacy)
Long context reasoning evaluation
32.7%
Better than 32% of models compared
Last updated Oct 1, 2026
Artificial AnalysisProviders
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