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Qwen3.6 27B

qwen/qwen3.6-27b
BackTry Model
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Qwen3.6 27B

qwen/qwen3.6-27b
BackTry Model

Qwen3.6 27B is a native vision-language dense model with stronger agentic coding and STEM reasoning than Qwen 3.5 27B. It also improves spatial intelligence (including object localization/detection), plus video understanding, document OCR, and visual-agent workflows.

Added Apr 23, 2026

Model weights

Context Window

260.1K

Max Output

65.5K

Avg output tokens (7d)

144 tokens

10%

Input Price (Auto)

$0.30/1M

Output Price (Auto)

$2.00/1M

Cache Read (Auto)

$0.030/1M

Capabilities

Benchmarks

Performance metrics and benchmarks

Sourced from Artificial Analysis.

Intelligence Index

19.8

Better than 68% of models compared

Coding Index

46.6

Better than 55% of models compared

Agentic work

T²-Bench Telecom (legacy)

Legacy fallback · Conversational AI agents in dual-control scenarios

93.6%

Better than 90% of models compared

GDPval-AA v2

Economically valuable tasks (Elo)

1043 Elo

Better than 50% of models compared

Document reasoning

AA-LCR v1.1

Long context reasoning with updated grading

66.7%

Better than 62% of models compared

Reasoning

HLE

Humanity's Last Exam

15.1%

Better than 66% of models compared

IFBench

Instruction-following benchmark

45.7%

Better than 53% of models compared

Coding

Terminal-Bench Hard (legacy)

Legacy fallback · Agentic coding and terminal use

21.2%

Better than 61% of models compared

Legacy benchmarks

GPQA Diamond (legacy)

Graduate-level scientific reasoning

82.9%

Better than 72% of models compared

AA-LCR (unversioned / legacy)

Long context reasoning evaluation

66.7%

Better than 62% of models compared

Last updated Sep 11, 2026

Artificial Analysis

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