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 | Muse Spark 1.3muse-spark-1.3 | Veo 3 Fastveo3-fast | Qwen3.8 27Bqwen3.8-27b |
|---|---|---|---|
| Pricing | |||
| Input | $1.25 / 1M | — | $0.45 / 1M |
| Output | $4.25 / 1M | — | $3.20 / 1M |
| Cache Write (5m) | $1.25 / 1M | Not applicable | $0.45 / 1M |
| Cache Write (1h) | $1.25 / 1M | Not applicable | $0.45 / 1M |
| Cache Read | $1.25 / 1M | Not applicable | $0.45 / 1M |
| Web Search | $0 / 1M | — | $0 / 1M |
| Request | — | $1.26 / request | — |
| Billing | — | Pay Per Request | — |
| Context | |||
| Max context | 1M | N/A | 262K |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | Yes | No | Yes |
| Function Calling | Yes | No | Yes |
| JSON Mode | Yes | No | Yes |
| Streaming | Yes | No | Yes |
| Catalogue | |||
| Provider | Meta | Alibaba | |
| Category | chat | video | chat |
| Charge type | Pay As You Go | Pay Per Request | Pay As You Go |
| Released | — | — | — |
| Description | |||
| Summary | 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. | — | Qwen3.8 27B is an open-weight dense vision-language model from Qwen, designed for coding, professional knowledge work, research, and multimodal interaction. It combines strong text and visual understanding with capabilities optimized for sustained, real-world agentic tasks. The model supports flexible thinking modes that can be enabled for deeper reasoning or disabled for faster execution, making it well suited for long-running agents, multimodal workflows, coding assistants, and cost-conscious self-hosted deployments. |