LLM Comparison
Gemini 3.5 Flash-Lite vs MiniMax M2-her
Side-by-side specs, pricing & capabilities · Updated August 2026
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2/6 modelsSame tier:
| Organization | ||
| OpenTools Score | 13 9.0 | |
| 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 | 36artificial-analysis | — |
| SWE-Bench Pro | 54.2google-deepmind | — |
| Terminal-Bench 2.1 | 54google-deepmind | — |
| GDPVal-AA v2 | 1140google-deepmind | — |
| View Gemini 3.5 Flash-Lite | View MiniMax M2-her | |
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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% |
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 large language model from MiniMax. Supports up to 65,536 token context window. Available from $0.30/M input tokens.
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