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 | Muse Spark 1.3muse-spark-1.3 |
|---|---|---|
| Pricing | ||
| Input | $0.125 / 1M | $1.25 / 1M |
| Output | $0 / 1M | $4.25 / 1M |
| Cache Write (5m) | $0.125 / 1M | $1.25 / 1M |
| Cache Write (1h) | $0.125 / 1M | $1.25 / 1M |
| Cache Read | $0.125 / 1M | $1.25 / 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 | Meta |
| 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. | Muse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows. |