gemini-3.5-flash vs minimax-m3
Side-by-side comparison of gemini-3.5-flash and minimax-m3: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. gemini-3.5-flash outperforms minimax-m3 on 5 of 7 shared benchmarks.
gemini-3.5-flash
Input / 1M
$1.50
Output / 1M
$9.00
Context
1.0M
Model ID
google/gemini-3.5-flash
MiniMax
minimax-m3
Input / 1M
$0.30
Output / 1M
$1.20
Context
1M
Model ID
minimaxi/minimax-m3
Benchmark comparison
Intelligence Indexreasoning
gemini-3.5-flash52.0%
minimax-m345.4%
Coding Indexcoding
gemini-3.5-flash70.1%
minimax-m358.6%
GPQA Diamondreasoning
gemini-3.5-flash92.2%
minimax-m392.9%
Terminal-Bench Hardagentic
gemini-3.5-flash40.9%
minimax-m342.4%
τ²-Benchagentic
gemini-3.5-flash95.3%
minimax-m388.9%
SciCodecoding
gemini-3.5-flash53.1%
minimax-m345.4%
Humanity's Last Examreasoning
gemini-3.5-flash42.7%
minimax-m339.0%
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-3.5-flash | minimax-m3 | |
|---|---|---|
| Input price / 1M | $1.50 | $0.30 |
| Output price / 1M | $9.00 | $1.20 |
| Context window | 1.0M tokens | 1M tokens |
| Max output | 66K tokens | 128K tokens |
| Vision input | Yes | Yes |
| Tool calling | Yes | Yes |
| Reasoning | Yes | Yes |
| Prompt caching | Yes | Yes |
| Computer use | N/A | N/A |
| Provider | Google LLC (Gemini API) | MiniMax |
Questions people ask
Is gemini-3.5-flash better than minimax-m3?
gemini-3.5-flash outperforms minimax-m3 on 5 of 7 shared benchmarks. See the benchmark comparison above for specifics: gemini-3.5-flash and minimax-m3 have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, gemini-3.5-flash or minimax-m3?
minimax-m3 is cheaper. gemini-3.5-flash costs $1.50/$9.00 per 1M input/output tokens, while minimax-m3 costs $0.30/$1.20.
Can I use gemini-3.5-flash 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-3.5-flash" and "minimaxi/minimax-m3", no other code changes needed.
What are the context windows?
gemini-3.5-flash 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-3.5-flash and minimax-m3 with one line of code
Requesty provides a single OpenAI-compatible API for 600+ models. Change the model parameter, not your code.