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.
- GPT-6 LunaOpenAIRemove
- Muse WonderMetaRemove
- Muse Spark 1.3MetaRemove
- mai-ds-r1:freeNot in the catalogueRemove
4 is the maximum. Remove one to add another.
| Attribute | GPT-6 Lunagpt-6-luna | Muse Wondermuse-wonder | Muse Spark 1.3muse-spark-1.3 | mai-ds-r1:freeNot in the catalogue |
|---|---|---|---|---|
| Pricing | ||||
| Input | $0.10 / 1M | $4.00 / 1M | $1.25 / 1M | — |
| Output | $0.50 / 1M | $20.00 / 1M | $4.25 / 1M | — |
| Cache Write (5m) | $0.10 / 1M | $4.00 / 1M | $1.25 / 1M | — |
| Cache Write (1h) | $0.10 / 1M | $4.00 / 1M | $1.25 / 1M | — |
| Cache Read | $0.10 / 1M | $4.00 / 1M | $1.25 / 1M | — |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M | — |
| Context | ||||
| Max context | 1.1M | 1M | 1M | — |
| Max output | N/A | N/A | N/A | — |
| Capabilities | ||||
| Vision | Yes | Yes | Yes | — |
| Function Calling | Yes | Yes | Yes | — |
| JSON Mode | Yes | Yes | Yes | — |
| Streaming | Yes | Yes | Yes | — |
| Catalogue | ||||
| Provider | OpenAI | Meta | Meta | — |
| Category | chat | chat | chat | — |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go | — |
| Released | — | — | — | — |
| Description | ||||
| Summary | GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, optimized for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic tasks. It combines low-cost, responsive inference with the GPT-6 family’s improvements in factual reliability and clear, concise communication. At higher reasoning effort, GPT-6 Luna can also handle complex software engineering and computer-use workflows that previously required a Sol-tier model, making it a versatile choice for scalable production applications that need to balance speed, cost, and capability. | Muse Wonder is Meta’s frontier multimodal reasoning model, designed for complex personal and professional agentic workflows. It supports text, image, video, audio, and PDF inputs with text output and features a 1M-token context window for sustained reasoning across long-running tasks. Optimized for autonomous execution and multi-agent orchestration, Muse Wonder can plan, delegate to subagents, coordinate parallel tool use, recover from errors, and operate browsers and applications across desktop and mobile environments. With cross-conversation context retrieval and its Active Focus training approach, it is well suited for complex software engineering, multi-file refactoring, computer use, and end-to-end workflows requiring persistence, adaptability, and minimal supervision. | 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. | — |