Qwen 3 235b A22B 2507 Thinking
The thinking version of Qwen 3 235b A22B 2507, with enhanced reasoning capabilities and step-by-step problem solving.
Added Sep 11, 2025
Model weightsPricing
Auto routing · per 1M tokens- Input
- $0.30
- Output
- $0.50
Specifications
- Context window
- 256K
- Max output
- 262.1K
- Parameters
- 235B / 22B
- Total / active
- Avg output (7d)
- 1.5K tokens
- Longer than 83% of models
Benchmarks
Benchmarks
Sourced from Artificial Analysis.
Intelligence Index
12.7
Coding Index
22.1
Agentic Index
1.3
Agentic work
AutomationBench-AA
Workflow automation with guardrail penalties
2.2%
Better than 21% of models compared
AA-Briefcase
Agentic knowledge work (Elo)
172 Elo
Better than 12% of models compared
GDPval-AA v2
Economically valuable tasks (Elo)
302 Elo
Better than 18% of models compared
Document reasoning
GDP.pdf
Professional PDF reasoning: all-pass rate
4.8%
Better than 23% of models compared
AA-LCR v1.1
Long context reasoning with updated grading
72.0%
Better than 67% of models compared
Reasoning
HLE
Humanity's Last Exam
15.9%
Better than 63% of models compared
IFBench
Instruction-following benchmark
51.2%
Better than 61% of models compared
CritPt
Research-level physics reasoning
0.0%
Coding
Terminal-Bench v4.0
Practical coding and terminal tasks
0.0%
Better than 16% of models compared
SciCode
Python programming for scientific computing
41.4%
Better than 29% of models compared
LiveCodeBench
Contamination-free coding benchmark
78.8%
Better than 90% of models compared
Math
AIME 2025
American Invitational Mathematics Examination 2025
91.0%
Better than 92% of models compared
AIME
American Invitational Mathematics Examination
94.0%
Better than 98% of models compared
Math-500
Diverse mathematical problem solving benchmark
98.4%
Better than 95% of models compared
Knowledge
MMLU-Pro
Professional and academic subject knowledge
84.3%
Better than 89% of models compared
AA-Omniscience Accuracy
Proportion of correctly answered questions
22.8%
AA-Omniscience Hallucination Rate
Rate of incorrect answers among non-correct responses
89.8%
Legacy benchmarks
GPQA Diamond (legacy)
Graduate-level scientific reasoning
79.0%
Better than 65% of models compared
Terminal-Bench Hard (legacy)
Agentic coding and terminal use
13.6%
Better than 50% of models compared
T²-Bench Telecom (legacy)
Conversational AI agents in dual-control scenarios
53.2%
Better than 54% of models compared
AA-LCR (unversioned / legacy)
Long context reasoning evaluation
72.0%
Better than 67% of models compared
GDPval-AA (unversioned / legacy)
Economically valuable tasks
0.0%
Last updated Oct 1, 2026
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