LLM Comparison
Gemini 3.5 Flash-Lite vs MiniMax M2.7
Side-by-side specs, pricing & capabilities · Updated September 2026
Price vs Intelligence
Add to comparison
2/6 modelsSame tier:
| Organization | ||
| OpenTools Score | 24 17.3 | 42 56.5 |
| Family | Gemini | MiniMax |
| Status | Current | Current |
| Release Date | Jul 2026 | Mar 2026 |
| Context Window | 1.0M tokens | 197K 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: $0.0590/M tokens |
| Capabilities | textvisionaudio-inputvideo-inputpdf-inputreasoningcodingtool-usesearch-groundingcomputer-usestructured-output | textcode |
| Max Output | 64K tokens | — |
| API Identifier | gemini-3.5-flash-lite | minimax/minimax-m2.7 |
| Benchmarks | ||
| Artificial Analysis Intelligence Index | 36artificial-analysis | — |
| SWE-Bench Pro | 54.2google-deepmind | — |
| Terminal-Bench 2.1 | 54google-deepmind | 55.4307artificial-analysis |
| GDPVal-AA v2 | 1140google-deepmind | — |
| Artificial Analysis Intelligence Index v4.3 | 22.6607artificial-analysis | 23.2171artificial-analysis |
| GPQA Diamond | 83.8384artificial-analysis | 87.3737artificial-analysis |
| SciCode | 41.3194artificial-analysis | 50.1157artificial-analysis |
| SWE-bench Pro | — | 56.22https://huggingface.co/MiniMaxAI/MiniMax-M2.7 |
| Terminal-Bench 2 | — | 57https://huggingface.co/MiniMaxAI/MiniMax-M2.7 |
| View Gemini 3.5 Flash-Lite | View MiniMax M2.7 | |
Cost Calculator
Enter your expected monthly token usage to compare costs.
| Model | Input | Output | Total / mo | vs Best |
|---|---|---|---|---|
| MiniMax M2.7Cheapest | $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 M2.7
MiniMax M2.7 is a large language model from MiniMax. Supports up to 196,608 token context window. Available from $0.30/M input tokens.
More Comparisons
Looking for more AI models?
Browse All LLMs