Compare models
Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.
| Attribute | Gemini 3.7 Flashgemini-3.7-flash | Mistral Embed 2312mistral-embed-2312 | Gemini 3.8 Flashgemini-3.8-flash |
|---|---|---|---|
| Pricing | |||
| Input | $0.375 / 1M | $0.125 / 1M | $0.75 / 1M |
| Output | $1.88 / 1M | $0 / 1M | $3.75 / 1M |
| Cache Write (5m) | $0.375 / 1M | $0.125 / 1M | $0.75 / 1M |
| Cache Write (1h) | $0.375 / 1M | $0.125 / 1M | $0.75 / 1M |
| Cache Read | $0.375 / 1M | $0.125 / 1M | $0.75 / 1M |
| Web Search | $0 / 1M | — | $0 / 1M |
| Context | |||
| Max context | 1M | 8.2K | 1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | Yes | No | Yes |
| Function Calling | Yes | No | Yes |
| JSON Mode | Yes | No | Yes |
| Streaming | Yes | No | Yes |
| Catalogue | |||
| Provider | Mistral AI | ||
| Category | chat | embedding | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | — |
| Description | |||
| Summary | Gemini 3.7 Flash is Google's fast multimodal model designed for agentic workflows, coding, and complex multi-step reasoning. It combines responsive inference with reliable problem-solving capabilities, making it well suited for interactive and production-scale applications. Optimized for speed and dependable multi-step execution, Gemini 3.7 Flash is a strong choice for coding assistants, autonomous agents, and high-throughput workflows that require both low latency and capable reasoning. | Mistral Embed is Mistral AI's text embedding model, built for semantic search and RAG workflows. It generates 1024-dimensional vectors that capture meaningful relationships between pieces of text. | Gemini 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality. |