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 weightsContext Window
262.1K
Max Output
131.1K
Avg output tokens (7d)
2.4K tokens
Input Price (Auto)
$0.100/1M
Output Price (Auto)
$0.40/1M
Cache Read (Auto)
$0.050/1M
Capabilities
Benchmarks
Benchmarks
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
26.1
Coding Index
39.3
Agentic Index
11.0
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
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