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 | Qwen3.6-35B-A3Bqwen3.6-35b-a3b |
|---|---|---|
| Pricing | ||
| Request | $0.0336 / request | — |
| Billing | Pay Per Request | — |
| Cache Write (5m) | Not applicable | $5.40 / 1M |
| Cache Write (1h) | Not applicable | $5.40 / 1M |
| Cache Read | Not applicable | $5.40 / 1M |
| Input | — | $5.40 / 1M |
| Output | — | $32.40 / 1M |
| Web Search | — | $0 / 1M |
| Context | ||
| Max context | N/A | 262.1K |
| 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. | Qwen3.6-35B-A3B is an open-weight Mixture-of-Experts (MoE) multimodal model designed for agentic coding and long-horizon workflows. It features ~35–36B total parameters with ~3B activated per token, enabling strong performance with high inference efficiency. The model supports text and image inputs with a ~260K token context window, and is optimized for repository-level reasoning, multi-step development, and tool-driven workflows. With strong benchmark performance and improved coherence across extended tasks, Qwen3.6-35B-A3B is well suited for developer tools, coding agents, and real-world engineering applications that require both reasoning depth and efficiency. |