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Gemma 4 26B A4B Thinking

google/gemma-4-26b-a4b-it:thinking
BackTry Model
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Gemma 4 26B A4B Thinking

google/gemma-4-26b-a4b-it:thinking
BackTry Model

Google's Gemma 4 26B A4B instruction-tuned model with structured reasoning for more deliberate coding, multimodal analysis, and long-context problem solving.

Added Apr 2, 2026

Model weights

Context Window

262.1K

Max Output

131.1K

Avg output tokens (7d)

2.4K tokens

85%

Input Price (Auto)

$0.14/1M

Output Price (Auto)

$0.42/1M

Cache Read (Auto)

$0.068/1M

Capabilities

Benchmarks

Performance metrics and benchmarks

Sourced from Artificial Analysis.

Intelligence Index

25.7

Better than 70% of models compared

Coding Index

39.3

Better than 55% of models compared

Agentic Index

11.0

Better than 42% of models compared

Reasoning

GPQA Diamond

Graduate-level scientific reasoning

79.2%

Better than 75% of models compared

HLE

Humanity's Last Exam

18.3%

Better than 81% of models compared

IFBench

Instruction-following benchmark

72.4%

Better than 89% of models compared

T²-Bench Telecom

Conversational AI agents in dual-control scenarios

43.6%

Better than 49% of models compared

AA-LCR

Long context reasoning evaluation

55.7%

Better than 69% of models compared

GDPval-AA

Economically valuable tasks

13.4%

CritPt

Research-level physics reasoning

0.0%

Coding

SciCode

Python programming for scientific computing

40.0%

Better than 78% of models compared

Terminal-Bench Hard

Agentic coding and terminal use

13.6%

Better than 52% of models compared

Knowledge

AA-Omniscience Accuracy

Proportion of correctly answered questions

19.1%

AA-Omniscience Hallucination Rate

Rate of incorrect answers among non-correct responses

86.4%

Last updated Jun 28, 2026

Artificial Analysis

Providers

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