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 | Nemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:free | MiniMax M3minimax-m3 | Gemini 3.1 Flash Image (Google Vertex AI)gemini-3.1-flash-image-vertex |
|---|---|---|---|
| Pricing | |||
| Input | $0 / 1M | $0.30 / 1M | — |
| Output | $0 / 1M | $1.20 / 1M | — |
| Cache Write | $0 / 1M | — | — |
| Cache Read | $0 / 1M | $0.30 / 1M | Not applicable |
| Cache Write (5m) | — | $0.30 / 1M | Not applicable |
| Cache Write (1h) | — | $0.30 / 1M | Not applicable |
| Web Search | — | $0 / 1M | — |
| Request | — | — | $0.067 / request |
| Billing | — | — | Pay Per Request |
| Context | |||
| Max context | 1M | 1M | N/A |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | Yes | Yes | Yes |
| Function Calling | Yes | Yes | No |
| JSON Mode | Yes | Yes | No |
| Streaming | Yes | Yes | No |
| Catalogue | |||
| Provider | NVIDIA | MiniMax | |
| Category | chat | chat | image |
| Charge type | Free | Pay As You Go | Pay Per Request |
| Released | — | — | — |
| Description | |||
| Summary | NVIDIA Nemotron 3.5 Super VL is an open multimodal Mixture-of-Experts (MoE) model featuring 120B total parameters with 12B activated per token. Built on a hybrid Mamba–Transformer architecture with multi-token prediction, it supports text, images, documents, GUI screenshots, and video inputs, along with a 1M-token context window for complex, long-horizon workflows. Optimized for multimodal reasoning, visual understanding, and agentic tool use, the model supports configurable reasoning modes and token budgets. It is well suited for document intelligence, web research, coding validation, customer service, GUI analysis, and video understanding, enabling efficient, long-running multimodal agent applications. | MiniMax-M3 is a multimodal foundation model from MiniMax, supporting text, image, and video inputs with text output and a 1M-token context window. It is designed for long-horizon agentic workflows, coding, and tool-driven task execution, enabling sustained reasoning across complex tasks. Built on MiniMax Sparse Attention (MSA), the model dramatically improves long-context efficiency by replacing full attention with KV-block selection, reducing compute costs at 1M-token contexts while maintaining strong performance. Trained as a native multimodal model and optimized for multi-turn, production-style collaboration, MiniMax-M3 excels at extended, multi-step workflows rather than single-turn interactions. | Gemini 3.1 Flash Image served from Google Vertex AI. Billed per image at US$0.067. 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 2K. A request for a larger size, such as 4K or 4096x4096, returns a 2K 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, for example 4096x4096->2048x2048. |