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gemini-2.5-flash vs claude-sonnet-4-5

Side-by-side comparison of gemini-2.5-flash and claude-sonnet-4-5 — benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. claude-sonnet-4-5 outperforms gemini-2.5-flash on 9 of 9 shared benchmarks.

Benchmark comparison

MMLU Proknowledge
gemini-2.5-flash78.4%
claude-sonnet-4-583.8%
GPQA Diamondreasoning
gemini-2.5-flash68.3%
claude-sonnet-4-574.2%
HumanEvalcoding
gemini-2.5-flash88.5%
claude-sonnet-4-592.0%
SWE-Bench Verifiedcoding
gemini-2.5-flash53.2%
claude-sonnet-4-570.8%
MATHmath
gemini-2.5-flash85.3%
claude-sonnet-4-587.5%
AIME 2024math
gemini-2.5-flash72.1%
claude-sonnet-4-576.1%
MMMUmultimodal
gemini-2.5-flash72.5%
claude-sonnet-4-573.1%
LiveBenchreasoning
gemini-2.5-flash64.2%
claude-sonnet-4-569.5%
τ-bench Retailagentic
gemini-2.5-flash61.5%
claude-sonnet-4-567.3%

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-flashclaude-sonnet-4-5
Input price / 1M$0.30$3.00
Output price / 1M$2.50$15.00
Context window1.0M tokens1M tokens
Max output66K tokens64K tokens
Vision inputYesYes
Tool callingYesYes
ReasoningYesYes
Prompt cachingYesYes
Computer useYes
ProviderGoogle LLC (Gemini API)Anthropic PBC

Questions people ask

Is gemini-2.5-flash better than claude-sonnet-4-5?
claude-sonnet-4-5 outperforms gemini-2.5-flash on 9 of 9 shared benchmarks. See the benchmark comparison above for specifics — gemini-2.5-flash and claude-sonnet-4-5 have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper — gemini-2.5-flash or claude-sonnet-4-5?
gemini-2.5-flash is cheaper. gemini-2.5-flash costs $0.30/$2.50 per 1M input/output tokens, while claude-sonnet-4-5 costs $3.00/$15.00.
Can I use gemini-2.5-flash and claude-sonnet-4-5 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 "anthropic/claude-sonnet-4-5" — no other code changes needed.
What are the context windows?
gemini-2.5-flash supports up to 1.0M tokens of context. claude-sonnet-4-5 supports up to 1M 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 claude-sonnet-4-5 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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