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 | Mistral Medium 3.5mistral-medium-3-5 | Gemini 4 Argongemini-4-argon |
|---|---|---|
| Pricing | ||
| Input | $1.50 / 1M | $2.00 / 1M |
| Output | $7.50 / 1M | $10.00 / 1M |
| Cache Write (5m) | $1.50 / 1M | $2.00 / 1M |
| Cache Write (1h) | $1.50 / 1M | $2.00 / 1M |
| Cache Read | $1.50 / 1M | $2.00 / 1M |
| Web Search | $0 / 1M | $0 / 1M |
| Context | ||
| Max context | 262.1K | 1M |
| Max output | N/A | N/A |
| Capabilities | ||
| Vision | Yes | Yes |
| Function Calling | Yes | Yes |
| JSON Mode | Yes | Yes |
| Streaming | Yes | Yes |
| Catalogue | ||
| Provider | Mistral | |
| Category | chat | chat |
| Charge type | Pay As You Go | Pay As You Go |
| Released | — | — |
| Description | ||
| Summary | Mistral Medium 3.5 is a 128B dense instruction-following model from Mistral AI, supporting text and image inputs with text output. It is designed for agentic workflows, coding, and complex multi-step reasoning, with strong reliability in multi-tool orchestration and long-horizon tasks. The model features a 256K token context window, configurable reasoning effort per request, and a custom vision encoder that handles variable image sizes and aspect ratios. With support for self-hosting on as few as four GPUs and availability under open weights, it is well suited for scalable, production-grade deployments. | Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response. |