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.
- Gemini 3.1 Flash Lite Image (Google AI Studio)GoogleEnterprise & partner accessRemove
- Claude Opus 4.8AnthropicRemove
| Attribute | Gemini 3.1 Flash Lite Image (Google AI Studio)gemini-3.1-flash-lite-image-aistudio | Claude Opus 4.8claude-opus-4-8 |
|---|---|---|
| Pricing | ||
| Request | $0.0336 / request | — |
| Billing | Pay Per Request | — |
| Cache Write (5m) | Not applicable | $6.25 / 1M |
| Cache Write (1h) | Not applicable | $10.00 / 1M |
| Cache Read | Not applicable | $0.50 / 1M |
| Input | — | $5.00 / 1M |
| Output | — | $25.00 / 1M |
| Web Search | — | $0 / 1M |
| Context | ||
| Max context | N/A | 1M |
| Max output | N/A | N/A |
| Capabilities | ||
| Vision | Yes | Yes |
| Function Calling | No | Yes |
| JSON Mode | No | Yes |
| Streaming | No | Yes |
| Catalogue | ||
| Provider | Anthropic | |
| Category | image | chat |
| Charge type | Pay Per Request | Pay As You Go |
| Released | — | — |
| Description | ||
| Summary | Gemini 3.1 Flash Lite Image served from Google AI Studio. Billed per image at US$0.0336. Call it through /v1/chat/completions with stream set to false; the image is returned in the message content as a base64 data URI. Maximum output resolution is 1K. A request for a larger size returns a 1K image with the same aspect ratio at the same price. When a size is reduced, the response carries an X-Image-Resolution-Capped header with the requested and delivered size. | Claude Opus 4.8 is Anthropic's most capable generally available model in the Opus family, designed for highly autonomous agents, long-horizon workflows, and advanced knowledge work. It supports text, image, and file inputs with text output, includes reasoning capabilities, and features a 1M-token context window for maintaining coherence across extended tasks and sessions. The model excels at multi-step reasoning, complex coding, and end-to-end project orchestration, including large codebases, multi-stage debugging, and long-running asynchronous agent pipelines. Beyond software engineering, it is highly effective for document drafting, presentation creation, data analysis, and memory-driven workflows, delivering consistent quality across very long outputs and complex projects. |