Gemma 4 26B A4B
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. Requests containing video cost $0.10 per million input tokens and $0.40 per million output tokens.
- Reasoning
- Vision
- Video Input
- Structured Output
Added Apr 2, 2026
Model weightsPricing
Auto routing · per 1M tokens- Input
- $0.068
- Output
- $0.23
- Cache read
- $0.037
Specifications
- Context window
- 262.1K
- Max output
- 131.1K
- Parameters
- 26B / 4B
- Total / active
- Avg output (7d)
- 125 tokens
- Longer than 8% of models
Benchmarks
Benchmarks
Sourced from Artificial Analysis.
Intelligence Index
16.7
Coding Index
39.3
Agentic work
AutomationBench-AA
Workflow automation with guardrail penalties
1.9%
Better than 20% of models compared
AA-Briefcase
Agentic knowledge work (Elo)
311 Elo
Better than 17% of models compared
GDPval-AA v2
Economically valuable tasks (Elo)
569 Elo
Better than 29% of models compared
Document reasoning
AA-LCR v1.1
Long context reasoning with updated grading
65.7%
Better than 57% of models compared
Reasoning
HLE
Humanity's Last Exam
19.3%
Better than 67% of models compared
IFBench
Instruction-following benchmark
72.4%
Better than 89% of models compared
CritPt
Research-level physics reasoning
0.0%
Coding
Terminal-Bench Hard (legacy)
Legacy fallback · Agentic coding and terminal use
13.6%
Better than 51% of models compared
SciCode
Python programming for scientific computing
40.0%
Better than 26% of models compared
Knowledge
AA-Omniscience Accuracy
Proportion of correctly answered questions
15.5%
AA-Omniscience Hallucination Rate
Rate of incorrect answers among non-correct responses
92.1%
Legacy benchmarks
GPQA Diamond (legacy)
Graduate-level scientific reasoning
79.2%
Better than 66% of models compared
T²-Bench Telecom (legacy)
Conversational AI agents in dual-control scenarios
43.6%
Better than 48% of models compared
AA-LCR (unversioned / legacy)
Long context reasoning evaluation
65.7%
Better than 57% of models compared
Last updated Oct 3, 2026
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