POST /v1/chat/completionsGemini 2.5 Pro
gemini-2.5-proGemini 2.5 Pro is Google’s advanced Gemini 2.5 model for complex tasks, deep reasoning, and coding. Official Gemini 2.5 materials describe the generation as “thinking” before responding, with improved performance and accuracy on hard tasks. It remains a strong choice for users who need deliberate reasoning and multimodal understanding.
Total Context
1Mtokens
Max Output
65.5Ktokens
Released
Jun 17, 2025
Modalities
Gemini 2.5 Pro Price
| Input Price | Output Price | Cache Read |
|---|---|---|
| $1.25/M | $10/M | $0.125/M |
Gemini 2.5 Pro API
Gemini 2.5 Pro Benchmark
Gemini 2.5 Pro
27
/100
Artificial Analysis Intelligence Index
Artificial Analysis broad capability aggregate
Index score
32
/100
Artificial Analysis Coding Index
Artificial Analysis software task aggregate
Index score
87.7
/100
Artificial Analysis Math Index
Artificial Analysis math reasoning aggregate
Index score
Knowledge & Reasoning
MMLU-Pro
Advanced multi-task knowledge
86.2%
GPQA
Advanced science problem solving
84.4%
HLE
Broad expert-level exam set
21.1%
Coding & Engineering
LiveCodeBench
Live coding problems
80.1%
SciCode
Scientific coding challenges
42.8%
Terminal-Bench Hard
Hard terminal task execution
26.5%
Math
MATH-500
Advanced math problem solving
96.7%
AIME
Competition math problems
88.7%
AIME 2025
Competition math problems
87.7%
Instruction Following & Agent Tasks
IFBench
Prompt constraint adherence
48.7%
AA-LCR
Long-context reasoning
66%
τ²-Bench
Agent workflow tasks
54.1%
Metrics sourced from Artificial Analysis
Frequently asked questions about Gemini 2.5 Pro
Understand what Gemini 2.5 Pro is, its best uses, distinguishing strengths, practical tradeoffs, and safe TokenHub integration guidance.
What is Gemini 2.5 Pro, and where does it fit in Google’s model lineup?+
Gemini 2.5 Pro is Google’s established Gemini 2.5 Pro reasoning model for code, STEM, large datasets, and long documents. It remains a defined model generation, but newer models in the same family may be preferable for new evaluations.
Which workloads are the best fit for Gemini 2.5 Pro?+
Best-fit scenarios include complex multi-step reasoning, mathematics, science, and engineering problems, and analysis of long documents and datasets. Test representative inputs and define measurable acceptance criteria before production.
Why might a team select Gemini 2.5 Pro over a smaller or older model?+
Key strengths include strong reasoning on difficult problems, strong handling of long context, and support for varied multimodal inputs. This combination is especially useful for mathematics, science, and engineering problems.
What should be validated before relying on Gemini 2.5 Pro?+
Consider another model when the project can adopt a newer Gemini generation, very low latency is the main requirement, or the workflow cannot include human review for important decisions. Verify important factual, legal, financial, medical, or operational outputs with qualified human review.
What is the practical TokenHub setup guidance for Gemini 2.5 Pro?+
In TokenHub, select the exact model identifier displayed for Gemini 2.5 Pro, use the endpoint documented for your account, and authenticate with your TokenHub credentials. Confirm the TokenHub-exposed input types, tools, grounding options, and model lifecycle rather than assuming full Gemini API parity.
Media and Discussions
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