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
- Nemotron 3.5 Super VLNVIDIARemove
- Nemotron 3.5 Super VL (Free)
- Muse Spark Open
- Gemini 4 Argon
- Muse Wonder
- Gemini 3.1 Flash Lite Image (Google Vertex AI)
- Gemini 3.1 Flash Image (Google Vertex AI)Enterprise & partner access
- Gemini 3.1 Flash Image (Google AI Studio)Enterprise & partner access
- Gemini 3 Pro Image (Google Vertex AI)Enterprise & partner access
| Attribute | Gemini 3.1 Flash Lite Image (Google AI Studio)gemini-3.1-flash-lite-image-aistudio | Nemotron 3.5 Super VLnemotron-3.5-super-vl |
|---|---|---|
| Pricing | ||
| Request | $0.0336 / request | — |
| Billing | Pay Per Request | — |
| Cache Write (5m) | Not applicable | $0.10 / 1M |
| Cache Write (1h) | Not applicable | $0.10 / 1M |
| Cache Read | Not applicable | $0.10 / 1M |
| Input | — | $0.10 / 1M |
| Output | — | $0.40 / 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 | NVIDIA | |
| 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. | 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. |