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 | Mistral Embed 2312mistral-embed-2312 | Nemotron 3.5 Super VLnemotron-3.5-super-vl |
|---|---|---|
| Pricing | ||
| Input | $0.125 / 1M | $0.10 / 1M |
| Output | — Not priced per output token | $0.40 / 1M |
| Cache Write (5m) | $0.125 / 1M | $0.10 / 1M |
| Cache Write (1h) | $0.125 / 1M | $0.10 / 1M |
| Cache Read | $0.125 / 1M | $0.10 / 1M |
| Web Search | — | $0 / 1M |
| Context | ||
| Max context | 8.2K | 1M |
| Max output | N/A | N/A |
| Capabilities | ||
| Vision | No | Yes |
| Function Calling | No | Yes |
| JSON Mode | No | Yes |
| Streaming | No | Yes |
| Catalogue | ||
| Provider | Mistral AI | NVIDIA |
| Category | embedding | chat |
| Charge type | Pay As You Go | Pay As You Go |
| Released | — | — |
| Description | ||
| Summary | Mistral Embed is Mistral AI's text embedding model, built for semantic search and RAG workflows. It generates 1024-dimensional vectors that capture meaningful relationships between pieces of text. | 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. |