LLM Comparison
Gemini 3.5 Flash-Lite vs MiniMax M2-her
Side-by-side specs, pricing & capabilities
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2/6 models| Organization | ||
| OpenTools Score | 29 20.9 | |
| Family | Gemini | MiniMax |
| Status | Current | Current |
| Release Date | Jul 2026 | Jan 2026 |
| Context Window | 1.0M tokens | 66K tokens |
| Input Price | $0.30/M tokens | $0.30/M tokens |
| Output Price | $2.50/M tokens | $1.20/M tokens |
| Pricing Notes | DeepMind model page lists $0.30 input and $2.50 output per 1M tokens with no caching in the performance table. The ai.google.dev API docs were attempted through ScrapingBee and returned HTTP 400, so exact billing details beyond the official DeepMind price table were not used. | Cache read: $0.0300/M tokens |
| Capabilities | textvisionaudio-inputvideo-inputpdf-inputreasoningcodingtool-usesearch-groundingcomputer-usestructured-output | textcode |
| Max Output | 64K tokens | 2K tokens |
| API Identifier | gemini-3.5-flash-lite | minimax/minimax-m2-her |
| Benchmarks | ||
| Artificial Analysis Intelligence Index v4.3 | 22.7 indexartificial-analysis | — |
| GPQA Diamond | 83.8%artificial-analysis | — |
| SciCode | 41.3%artificial-analysis | — |
| Terminal-Bench 2.1 | 53.6%artificial-analysis | — |
| View Gemini 3.5 Flash-Lite | View MiniMax M2-her | |
Cost Calculator
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| Model | Input | Output | Total / mo | vs Best |
|---|---|---|---|---|
| MiniMax M2-herCheapest | $0.30 | $0.60 | $0.90 | — |
| Gemini 3.5 Flash-Lite | $0.30 | $1.25 | $1.55 | +72% |
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Gemini 3.5 Flash-Lite
Gemini 3.5 Flash-Lite is Google DeepMind general availability low-latency model for high-volume agentic systems, coding, document parsing, translation, and structured automation. Official DeepMind evidence lists 1M input tokens, 64k output tokens, text, image, video, audio, and PDF inputs, text output, tool use, Gemini API availability, and $0.30 input / $2.50 output pricing per million tokens.
MiniMax
MiniMax M2-her
MiniMax M2-her is a language-model variant designed for character role-play and interactive storytelling. MiniMax describes work on world consistency, story progression and adaptation to user preferences. It is distinct from the general-purpose MiniMax M2 family.
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