gemini-2.5-flash vs gpt-4.1
Side-by-side comparison of gemini-2.5-flash and gpt-4.1 — benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. gpt-4.1 outperforms gemini-2.5-flash on 9 of 9 shared benchmarks.
gemini-2.5-flash
Input / 1M
$0.30
Output / 1M
$2.50
Context
1.0M
Model ID
google/gemini-2.5-flash
gpt-4.1
Input / 1M
$2.00
Output / 1M
$8.00
Context
1.0M
Model ID
openai/gpt-4.1
Benchmark comparison
MMLU Proknowledge
gemini-2.5-flash78.4%
gpt-4.185.3%
GPQA Diamondreasoning
gemini-2.5-flash68.3%
gpt-4.174.1%
HumanEvalcoding
gemini-2.5-flash88.5%
gpt-4.191.8%
SWE-Bench Verifiedcoding
gemini-2.5-flash53.2%
gpt-4.168.1%
MATHmath
gemini-2.5-flash85.3%
gpt-4.189.2%
AIME 2024math
gemini-2.5-flash72.1%
gpt-4.172.4%
MMMUmultimodal
gemini-2.5-flash72.5%
gpt-4.174.8%
LiveBenchreasoning
gemini-2.5-flash64.2%
gpt-4.166.7%
τ-bench Retailagentic
gemini-2.5-flash61.5%
gpt-4.165.1%
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-flash | gpt-4.1 | |
|---|---|---|
| Input price / 1M | $0.30 | $2.00 |
| Output price / 1M | $2.50 | $8.00 |
| Context window | 1.0M tokens | 1.0M tokens |
| Max output | 66K tokens | 33K tokens |
| Vision input | Yes | Yes |
| Tool calling | Yes | Yes |
| Reasoning | Yes | — |
| Prompt caching | Yes | Yes |
| Computer use | — | — |
| Provider | Google LLC (Gemini API) | OpenAI Inc. |
Questions people ask
Is gemini-2.5-flash better than gpt-4.1?
gpt-4.1 outperforms gemini-2.5-flash on 9 of 9 shared benchmarks. See the benchmark comparison above for specifics — gemini-2.5-flash and gpt-4.1 have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper — gemini-2.5-flash or gpt-4.1?
gemini-2.5-flash is cheaper. gemini-2.5-flash costs $0.30/$2.50 per 1M input/output tokens, while gpt-4.1 costs $2.00/$8.00.
Can I use gemini-2.5-flash and gpt-4.1 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 "openai/gpt-4.1" — no other code changes needed.
What are the context windows?
gemini-2.5-flash supports up to 1.0M tokens of context. gpt-4.1 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 gpt-4.1 with one line of code
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