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.
4 is the maximum. Remove one to add another.
| Attribute | S1s1 | S2 Pros2-pro | GPT-6 Luna Progpt-6-luna-pro | Muse Spark 1.3muse-spark-1.3 |
|---|---|---|---|---|
| Pricing | ||||
| Input | $0 / 1M | $0 / 1M | $0.10 / 1M | $1.25 / 1M |
| Output | $0 / 1M | $0 / 1M | $0.50 / 1M | $4.25 / 1M |
| Cache Write (5m) | Not applicable | Not applicable | $0.10 / 1M | $1.25 / 1M |
| Cache Write (1h) | Not applicable | Not applicable | $0.10 / 1M | $1.25 / 1M |
| Cache Read | Not applicable | Not applicable | $0.10 / 1M | $1.25 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | ||||
| Max context | N/A | N/A | 1.1M | 1M |
| Max output | N/A | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | No | No | Yes | Yes |
| Function Calling | No | No | Yes | Yes |
| JSON Mode | No | No | Yes | Yes |
| Streaming | No | No | Yes | Yes |
| Catalogue | ||||
| Provider | Fish Audio | Fish Audio | OpenAI | Meta |
| Category | voice | voice | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | 2026-07-29 | 2026-07-29 | — | — |
| Description | ||||
| Summary | Fish Audio S1 text-to-speech. Billed per UTF-8 byte of input text. | Fish Audio S2 Pro text-to-speech. Billed per UTF-8 byte of input text. | GPT-6 Luna Pro uses the same underlying model as GPT-6 Luna, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. It combines Luna's speed and cost efficiency with deeper reasoning and more reliable multi-step execution, making it well suited for advanced coding, computer use, and agentic workflows where higher solution quality is needed without moving to a larger GPT-6 tier. | 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. |