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Gemma 4 26B A4B

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

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

Google's Gemma 4 26B A4B instruction-tuned model built for scalable reasoning, coding, long-context, and multimodal workflows. This route is tuned for faster direct answers while preserving multimodal and structured output support.

Added Apr 2, 2026

Model weights

Context Window

262.1K

Max Output

131.1K

Avg output tokens (7d)

398 tokens

13%

Input Price (Auto)

$0.12/1M

Output Price (Auto)

$0.40/1M

Cache Read (Auto)

$0.060/1M

Capabilities

Benchmarks

Performance metrics and benchmarks

Sourced from Artificial Analysis.

Intelligence Index

26.1

Better than 65% of models compared

Coding Index

39.3

Better than 50% of models compared

Agentic Index

11.0

Better than 36% of models compared

Reasoning

GPQA Diamond

Graduate-level scientific reasoning

79.2%

Better than 69% of models compared

HLE

Humanity's Last Exam

19.3%

Better than 74% 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 48% of models compared

AA-LCR

Long context reasoning evaluation

61.7%

Better than 65% 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 71% of models compared

Terminal-Bench Hard

Agentic coding and terminal use

13.6%

Better than 51% 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 Aug 16, 2026

Artificial Analysis

Providers

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