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 | Qwen3 VL 235B A22B Instructqwen3-vl-235b-a22b-instruct |
|---|---|---|
| Pricing | ||
| Request | $0.0336 / request | — |
| Billing | Pay Per Request | — |
| Cache Write (5m) | Not applicable | $0.30 / 1M |
| Cache Write (1h) | Not applicable | $0.30 / 1M |
| Cache Read | Not applicable | $0.30 / 1M |
| Input | — | $0.30 / 1M |
| Output | — | $1.50 / 1M |
| Web Search | — | $0 / 1M |
| Context | ||
| Max context | N/A | 131.1K |
| Max output | N/A | N/A |
| Capabilities | ||
| Vision | Yes | Yes |
| Function Calling | No | Yes |
| JSON Mode | No | Yes |
| Streaming | No | Yes |
| Catalogue | ||
| Provider | Alibaba | |
| Category | image | chat |
| Charge type | Pay Per Request | 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. | Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that combines strong language generation with image and video understanding, aimed at general vision-language tasks like VQA, document parsing, chart/table extraction, and multilingual OCR. It features robust perception, spatial grounding, and long-context visual comprehension, and supports agent-style workflows such as multi-image dialogue, video timeline alignment, GUI control, and visual-to-code assistance. With competitive benchmark performance and strong text-only ability, it's well suited for production uses across document AI, OCR, UI assistance, spatial reasoning, and vision-language research. |