Qwen3.7 Plus Thinking

Qwen3.7 Plus with thinking mode enabled for deeper multimodal reasoning, coding, tool use, screen reading, and productivity workflows.

  • Reasoning
  • Vision
  • Video Input

Added Jun 1, 2026

Pricing

Auto routing · per 1M tokens
Input
$0.40
Output
$1.60
Cache read
$0.080

Specifications

Context window
983.6K
Max output
65.5K
Avg output (7d)
568 tokens
Longer than 53% of models

Benchmarks

Sourced from Artificial Analysis.

Intelligence Index

25.2

Better than 78% of models compared

Coding Index

55.9

Better than 65% of models compared

Agentic Index

17.5

Better than 51% of models compared

Agentic work

AutomationBench-AA

Workflow automation with guardrail penalties

17.4%

Better than 37% of models compared

AutomationBench-AA Tasks Completed

Fully completed workflows without guardrail violations

1.8%

Better than 35% of models compared

AA-Briefcase v1.1

Agentic knowledge work (Elo)

915 Elo

Better than 40% of models compared

GDPval-AA v2.1

Economically valuable tasks (Elo)

768 Elo

Better than 34% of models compared

Document reasoning

GDP.pdf

Professional PDF reasoning: all-pass rate

12.2%

Better than 49% of models compared

AA-LCR v1.1

Long context reasoning with updated grading

73.0%

Better than 67% of models compared

MLCR-AA

Medical long-context reasoning

8.9%

Better than 27% of models compared

Reasoning

HLE

Humanity's Last Exam

35.6%

Better than 82% of models compared

IFBench

Instruction-following benchmark

78.0%

Better than 97% of models compared

CritPt

Research-level physics reasoning

9.1%

Coding

Terminal-Bench v4.0

Practical coding and terminal tasks

1.0%

Better than 40% of models compared

SciCode

Python programming for scientific computing

46.1%

Better than 39% of models compared

Knowledge

AA-Omniscience Accuracy

Proportion of correctly answered questions

22.5%

AA-Omniscience Hallucination Rate

Rate of incorrect answers among non-correct responses

27.7%

Legacy benchmarks

GPQA Diamond (legacy)

Graduate-level scientific reasoning

90.0%

Better than 89% of models compared

Terminal-Bench Hard (legacy)

Agentic coding and terminal use

47.0%

Better than 94% of models compared

T²-Bench Telecom (legacy)

Conversational AI agents in dual-control scenarios

93.0%

Better than 89% of models compared

AA-LCR (unversioned / legacy)

Long context reasoning evaluation

73.0%

Better than 67% of models compared

GDPval-AA (unversioned / legacy)

Economically valuable tasks

13.4%

Last updated Oct 22, 2026

Artificial Analysis

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