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 | Olmo 3 7B Instructolmo-3-7b-instruct | Gemini 4 Argongemini-4-argon |
|---|---|---|
| Pricing | ||
| Input | $0.10 / 1M | $2.00 / 1M |
| Output | $0.20 / 1M | $10.00 / 1M |
| Cache Write (5m) | $0.10 / 1M | $2.00 / 1M |
| Cache Write (1h) | $0.10 / 1M | $2.00 / 1M |
| Cache Read | $0.10 / 1M | $2.00 / 1M |
| Web Search | $0 / 1M | $0 / 1M |
| Context | ||
| Max context | 65.5K | 1M |
| Max output | N/A | N/A |
| Capabilities | ||
| Vision | No | Yes |
| Function Calling | Yes | Yes |
| JSON Mode | Yes | Yes |
| Streaming | Yes | Yes |
| Catalogue | ||
| Provider | Allen AI | |
| Category | chat | chat |
| Charge type | Pay As You Go | Pay As You Go |
| Released | — | — |
| Description | ||
| Summary | Olmo 3 7B Instruct is a 7B instruction-tuned version of the Olmo 3 base model, optimized for Q&A, instruction following, and natural conversation. Trained with high-quality data in an open pipeline, it performs well on everyday NLP tasks and is easy to adopt. Released by AI2 under Apache 2.0, it provides a transparent, community-friendly choice for instruction-driven applications. | 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. |