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 3.1 Flash Lite Image (Google Vertex AI)gemini-3.1-flash-lite-image-vertex | Whisper 1whisper-1 | Gemini 4 Argongemini-4-argon |
|---|---|---|---|
| Pricing | |||
| Request | $0.0336 / request | — | — |
| Billing | Pay Per Request | — | — |
| Cache Write (5m) | Not applicable | Not applicable | $2.00 / 1M |
| Cache Write (1h) | Not applicable | Not applicable | $2.00 / 1M |
| Cache Read | Not applicable | Not applicable | $2.00 / 1M |
| Input | — | $75.00 / 1M | $2.00 / 1M |
| Output | — | $75.00 / 1M | $10.00 / 1M |
| Web Search | — | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | N/A | N/A | 1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | Yes | No | Yes |
| Function Calling | No | No | Yes |
| JSON Mode | No | Yes | Yes |
| Streaming | No | No | Yes |
| Catalogue | |||
| Provider | OpenAI | ||
| Category | image | voice | chat |
| Charge type | Pay Per Request | Pay As You Go | Pay As You Go |
| Released | — | — | — |
| Description | |||
| Summary | Gemini 3.1 Flash Lite Image served from Google Vertex AI. 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. | Whisper (whisper-1) is OpenAI's open-source automatic speech recognition (ASR) model, designed for audio transcription and translation. It supports 50+ languages and processes audio files up to 25 MB, accepting formats such as mp3, mp4, wav, and webm. Optimized for reliable speech-to-text conversion across diverse audio inputs, Whisper is priced per minute of audio, billed to the nearest second, making it well suited for transcription, localization, and voice-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. |