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gemini-2.5-flash vs gemini-2.5-pro

Side-by-side comparison of gemini-2.5-flash and gemini-2.5-pro — benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. gemini-2.5-pro outperforms gemini-2.5-flash on 9 of 9 shared benchmarks.

Benchmark comparison

MMLU Proknowledge
gemini-2.5-flash78.4%
gemini-2.5-pro86.2%
GPQA Diamondreasoning
gemini-2.5-flash68.3%
gemini-2.5-pro84.0%
HumanEvalcoding
gemini-2.5-flash88.5%
gemini-2.5-pro93.2%
SWE-Bench Verifiedcoding
gemini-2.5-flash53.2%
gemini-2.5-pro63.8%
MATHmath
gemini-2.5-flash85.3%
gemini-2.5-pro91.4%
AIME 2024math
gemini-2.5-flash72.1%
gemini-2.5-pro88.0%
MMMUmultimodal
gemini-2.5-flash72.5%
gemini-2.5-pro81.7%
LiveBenchreasoning
gemini-2.5-flash64.2%
gemini-2.5-pro73.6%
τ-bench Retailagentic
gemini-2.5-flash61.5%
gemini-2.5-pro69.8%

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-flashgemini-2.5-pro
Input price / 1M$0.30$1.25
Output price / 1M$2.50$10.00
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-flash better than gemini-2.5-pro?
gemini-2.5-pro outperforms gemini-2.5-flash on 9 of 9 shared benchmarks. See the benchmark comparison above for specifics — gemini-2.5-flash and gemini-2.5-pro have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper — gemini-2.5-flash or gemini-2.5-pro?
gemini-2.5-flash is cheaper. gemini-2.5-flash costs $0.30/$2.50 per 1M input/output tokens, while gemini-2.5-pro costs $1.25/$10.00.
Can I use gemini-2.5-flash and gemini-2.5-pro 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-flash" or "google/gemini-2.5-pro" — no other code changes needed.
What are the context windows?
gemini-2.5-flash supports up to 1.0M tokens of context. gemini-2.5-pro 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-flash and gemini-2.5-pro with one line of code

Requesty provides a single OpenAI-compatible API for 400+ models. Change the model parameter, not your code.

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