Google vs MiniMax: Token Pricing, Speed & Intelligence
Full comparison of Google and MiniMax — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.
Gemini 2.5 — the largest context window at the lowest frontier price
Google DeepMind's Gemini family offers some of the most competitive frontier pricing, with Gemini 2.5 Pro delivering top-tier intelligence at $1.25/1M input tokens. The 1M+ token context window is the largest available. Gemini 2.5 Flash is a standout efficient model for vision and multimodal tasks.
MiniMax
Long-context frontier models with 1M token windows
MiniMax is a Chinese AI company offering the MiniMax M-series of large language models. MiniMax M2.7 and M1 support context windows up to 1M tokens and are designed for enterprise chat, long-document analysis, and agentic workflows.
Key metrics
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Live token pricing
Strengths & weaknesses
MiniMax
Key differentiators
Frequently asked questions
Google FAQs
How much does the Google Gemini API cost?
Gemini 2.5 Pro costs $1.25/1M input tokens (up to 200K context) and $10/1M output. Gemini 2.5 Flash is $0.15/$0.60 per 1M tokens. Gemini 2.0 Flash is even cheaper at $0.10/$0.40 per 1M tokens.
What is the context window for Gemini models?
Gemini 2.5 Pro and Flash both support a 1,048,576-token (1M+) context window — the largest available from any major LLM provider. This makes them ideal for processing entire codebases, books, or long document collections.
Does Gemini support vision and multimodal inputs?
Yes. All Gemini 2.x models natively support images, audio, and video inputs alongside text. Gemini 2.5 Flash is particularly strong for vision tasks at a low cost.
MiniMax FAQs
What is MiniMax M2.7?
MiniMax M2.7 is MiniMax's latest chat model, supporting a 205K token context window. It is designed for enterprise chat, long-document analysis, and agentic tasks.
Is MiniMax available internationally?
Yes. The MiniMax API is accessible globally, and models are also available through OpenRouter and other inference aggregators.
Provider resources
Google — Gemini 2.5 — the largest context window at the lowest frontier price
Google DeepMind's Gemini family offers some of the most competitive frontier pricing, with Gemini 2.5 Pro delivering top-tier intelligence at $1.25/1M input tokens. The 1M+ token context window is the largest available. Gemini 2.5 Flash is a standout efficient model for vision and multimodal tasks.
Gemini 2.5 Pro delivers frontier-tier intelligence at $1.25/1M input tokens — the best price-to-performance ratio among all frontier models.
MiniMax — Long-context frontier models with 1M token windows
MiniMax is a Chinese AI company offering the MiniMax M-series of large language models. MiniMax M2.7 and M1 support context windows up to 1M tokens and are designed for enterprise chat, long-document analysis, and agentic workflows.
MiniMax M1 supports a 1M token context window at $0.30/1M input tokens — one of the most cost-effective long-context models available.
Key strengths compared
- ▸1M+ token context window — largest available
- ▸Best price-per-intelligence at frontier tier ($1.25/1M input)
- ▸Native multimodal: text, image, audio, video
MiniMax
- ▸1M token context window
- ▸Competitive pricing
- ▸Strong multilingual performance
Provider category context
Google is a frontier lab, founded in 1998. MiniMax is a frontier lab, founded in 2021. Both are frontier lab providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.
How to choose between them
Both Google and MiniMax are frontier labs with proprietary models. Choose based on benchmark performance for your specific task: Google leads on 1m+ token context window — largest available, while MiniMax leads on 1m token context window. For cost-sensitive workloads, compare the cheapest model tier from each provider in the pricing table above — the gap between efficient-tier models is often larger than between flagship models.