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gemini-2.5-pro vs gemini-2.5-flash

Side-by-side comparison of gemini-2.5-pro and gemini-2.5-flash— benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. gemini-2.5-pro outperforms gemini-2.5-flash on 11 of 11 shared benchmarks.

Benchmark comparison

Intelligence Indexreasoning
gemini-2.5-pro34.6%
gemini-2.5-flash27.0%
Coding Indexcoding
gemini-2.5-pro32.0%
gemini-2.5-flash22.2%
Math Indexmath
gemini-2.5-pro87.7%
gemini-2.5-flash73.3%
GPQA Diamondreasoning
gemini-2.5-pro84.4%
gemini-2.5-flash79.0%
AIME 2025math
gemini-2.5-pro87.7%
gemini-2.5-flash73.3%
LiveCodeBenchcoding
gemini-2.5-pro80.1%
gemini-2.5-flash69.5%
Terminal-Bench Hardagentic
gemini-2.5-pro26.5%
gemini-2.5-flash13.6%
τ²-Benchagentic
gemini-2.5-pro54.1%
gemini-2.5-flash31.6%
SciCodecoding
gemini-2.5-pro42.8%
gemini-2.5-flash39.4%
MMLU Proknowledge
gemini-2.5-pro86.2%
gemini-2.5-flash83.2%
Humanity's Last Examreasoning
gemini-2.5-pro21.1%
gemini-2.5-flash11.1%

Scores sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and don't capture every aspect of model quality.

Pricing & specifications

gemini-2.5-progemini-2.5-flash
Input price / 1M$1.25$0.30
Output price / 1M$10.00$2.50
Context window1.0M tokens1.0M tokens
Max output66K tokens66K tokens
Vision inputYesYes
Tool callingYesYes
ReasoningYesYes
Prompt cachingYesYes
Computer use
ProviderGoogle LLC (Gemini API)Google LLC (Gemini API)

Questions people ask

Is gemini-2.5-pro better than gemini-2.5-flash?
gemini-2.5-pro outperforms gemini-2.5-flash on 11 of 11 shared benchmarks. See the benchmark comparison above for specifics — gemini-2.5-pro and gemini-2.5-flash have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper — gemini-2.5-pro or gemini-2.5-flash?
gemini-2.5-flash is cheaper. gemini-2.5-pro costs $1.25/$10.00 per 1M input/output tokens, while gemini-2.5-flash costs $0.30/$2.50.
Can I use gemini-2.5-pro and gemini-2.5-flash through the same API?
Yes. Requesty provides a single OpenAI-compatible API that routes to both. Change just the "model" parameter to switch — "google/gemini-2.5-pro" or "google/gemini-2.5-flash" — no other code changes needed.
What are the context windows?
gemini-2.5-pro supports up to 1.0M tokens of context. gemini-2.5-flash supports up to 1.0M tokens. Longer context means you can feed larger documents or codebases in a single prompt, though quality often degrades past 128K for most models.

Switch between gemini-2.5-pro and gemini-2.5-flash with one line of code

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