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.
- DeepSeek V4.1 Flash 1017
- Nemotron 3.5 Super VL (Free)
- Nemotron 3.5 Super VL
- Muse Spark Open
- Gemini 4 Argon
- Muse Wonder
- Gemini 3.1 Flash Lite Image (Google AI Studio)Enterprise & partner access
- Gemini 3.1 Flash Image (Google Vertex AI)Enterprise & partner access
| Attribute | Gemini 3.1 Flash Lite Image (Google Vertex AI)gemini-3.1-flash-lite-image-vertex | Nemotron 3.5 Lightning (Free)nemotron-3.5-lightning:free |
|---|---|---|
| Pricing | ||
| Request | $0.0336 / request | — |
| Billing | Pay Per Request | — |
| Cache Write (5m) | Not applicable | — |
| Cache Write (1h) | Not applicable | — |
| Cache Read | Not applicable | $0 / 1M |
| Input | — | $0 / 1M |
| Output | — | $0 / 1M |
| Cache Write | — | $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 | Free |
| 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. | NVIDIA Nemotron 3.5 Lightning is an open Mixture-of-Experts (MoE) model with 30B total parameters and 3B active per token, optimized for high-throughput agentic workloads and efficient inference. Its lightweight active compute and open design make it well suited for specialized agents, domain-specific customization, and scalable production deployments where speed, cost efficiency, and adaptability are key. |