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gemini-2.5-pro vs minimax-m3

Side-by-side comparison of gemini-2.5-pro and minimax-m3: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. minimax-m3 outperforms gemini-2.5-pro on 7 of 7 shared benchmarks.

Benchmark comparison

Intelligence Indexreasoning
gemini-2.5-pro34.6%
minimax-m354.7%
Coding Indexcoding
gemini-2.5-pro32.0%
minimax-m343.4%
Math Indexmath
gemini-2.5-pro87.7%
minimax-m3N/A
GPQA Diamondreasoning
gemini-2.5-pro84.4%
minimax-m392.9%
AIME 2025math
gemini-2.5-pro87.7%
minimax-m3N/A
LiveCodeBenchcoding
gemini-2.5-pro80.1%
minimax-m3N/A
Terminal-Bench Hardagentic
gemini-2.5-pro26.5%
minimax-m342.4%
τ²-Benchagentic
gemini-2.5-pro54.1%
minimax-m388.9%
SciCodecoding
gemini-2.5-pro42.8%
minimax-m345.4%
MMLU Proknowledge
gemini-2.5-pro86.2%
minimax-m3N/A
Humanity's Last Examreasoning
gemini-2.5-pro21.1%
minimax-m337.1%

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-prominimax-m3
Input price / 1M$1.25$0.30
Output price / 1M$10.00$1.20
Context window1.0M tokens1M tokens
Max output66K tokens128K tokens
Vision inputYesYes
Tool callingYesYes
ReasoningYesYes
Prompt cachingYesYes
Computer useN/AN/A
ProviderGoogle LLC (Gemini API)MiniMax

Questions people ask

Is gemini-2.5-pro better than minimax-m3?
minimax-m3 outperforms gemini-2.5-pro on 7 of 7 shared benchmarks. See the benchmark comparison above for specifics: gemini-2.5-pro and minimax-m3 have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, gemini-2.5-pro or minimax-m3?
minimax-m3 is cheaper. gemini-2.5-pro costs $1.25/$10.00 per 1M input/output tokens, while minimax-m3 costs $0.30/$1.20.
Can I use gemini-2.5-pro and minimax-m3 through the same API?
Yes. Requesty provides a single OpenAI-compatible API that routes to both. Change just the "model" parameter to switch between "google/gemini-2.5-pro" and "minimaxi/minimax-m3", no other code changes needed.
What are the context windows?
gemini-2.5-pro supports up to 1.0M tokens of context. minimax-m3 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-pro and minimax-m3 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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