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Gemma 4 31B Thinking

google/gemma-4-31b-it:thinking
BackTry Model
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Gemma 4 31B Thinking

google/gemma-4-31b-it:thinking
BackTry Model

Google's Gemma 4 31B instruction-tuned model with thinking explicitly enabled, exposing reasoning traces for complex multimodal and coding workflows.

Added Apr 2, 2026

Model weights

Context Window

262.1K

Max Output

131.1K

Avg output tokens (7d)

1.6K tokens

62%

Input Price (Auto)

$0.100/1M

Output Price (Auto)

$0.34/1M

Cache Read (Auto)

$0.100/1M

Capabilities

Benchmarks

Performance metrics and benchmarks

Sourced from Artificial Analysis.

Intelligence Index

29.7

Better than 68% of models compared

Coding Index

43.4

Better than 54% of models compared

Agentic Index

14.4

Better than 40% of models compared

Reasoning

GPQA Diamond

Graduate-level scientific reasoning

85.7%

Better than 82% of models compared

HLE

Humanity's Last Exam

23.6%

Better than 79% of models compared

IFBench

Instruction-following benchmark

75.6%

Better than 93% of models compared

T²-Bench Telecom

Conversational AI agents in dual-control scenarios

59.9%

Better than 57% of models compared

AA-LCR

Long context reasoning evaluation

68.3%

Better than 76% of models compared

GDPval-AA

Economically valuable tasks

15.6%

CritPt

Research-level physics reasoning

1.4%

Coding

SciCode

Python programming for scientific computing

43.4%

Better than 80% of models compared

Terminal-Bench Hard

Agentic coding and terminal use

36.4%

Better than 83% of models compared

Knowledge

AA-Omniscience Accuracy

Proportion of correctly answered questions

20.0%

AA-Omniscience Hallucination Rate

Rate of incorrect answers among non-correct responses

85.0%

Last updated Aug 18, 2026

Artificial Analysis

Providers

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