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Qwen3.5 27B

qwen3.5-27b
Provider logo

Qwen3.5 27B

qwen3.5-27b

Qwen3.5 27B is a native vision-language dense model optimized for fast responses while balancing quality and inference speed.

Added Feb 24, 2026

Model weights

Context Window

260.1K

Max Output

65.5K

Input Price (Auto)

$0.27/1M

Output Price (Auto)

$2.16/1M

Cache Read (Auto)

$0.14/1M

Capabilities

Benchmarks

Performance metrics and benchmarks

Sourced from Artificial Analysis.

Reasoning

GPQA Diamond

Graduate-level scientific reasoning

84.2%

Better than 78% of models compared

HLE

Humanity's Last Exam

13.9%

Better than 67% of models compared

IFBench

Instruction-following benchmark

46.9%

Better than 54% of models compared

T²-Bench Telecom

Conversational AI agents in dual-control scenarios

87.1%

Better than 80% of models compared

AA-LCR

Long context reasoning evaluation

61.0%

Better than 64% of models compared

CritPt

Research-level physics reasoning

0.3%

Coding

SciCode

Python programming for scientific computing

36.7%

Better than 58% of models compared

Terminal-Bench Hard

Agentic coding and terminal use

31.8%

Better than 74% of models compared

Knowledge

AA-Omniscience Accuracy

Proportion of correctly answered questions

15.7%

AA-Omniscience Hallucination Rate

Rate of incorrect answers among non-correct responses

75.1%

Last updated Aug 7, 2026, 12:00 AM

Artificial Analysis

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