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 | GPT-6.1 Terragpt-6.1-terra | Claude Opus 4.8claude-opus-4-8 | Muse Spark Openmuse-spark-open |
|---|---|---|---|
| Pricing | |||
| Input | $1.00 / 1M | $5.00 / 1M | $1.25 / 1M |
| Output | $5.00 / 1M | $25.00 / 1M | $4.25 / 1M |
| Cache Write (5m) | $1.00 / 1M | $6.25 / 1M | $1.25 / 1M |
| Cache Write (1h) | $1.00 / 1M | $10.00 / 1M | $1.25 / 1M |
| Cache Read | $1.00 / 1M | $0.50 / 1M | $1.25 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | 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 | No | Yes | Yes |
| Catalogue | |||
| Provider | OpenAI | Anthropic | Meta |
| Category | chat | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | — |
| Description | |||
| Summary | GPT-6.1 Terra is OpenAI’s mid-tier model in the GPT-6.1 series, designed to balance capability, speed, and cost efficiency. Positioned below GPT-6.1 Sol, it delivers strong performance across everyday agentic workflows, coding, and professional writing, with particular strengths in screenshot understanding and on-screen content analysis. Optimized for high-volume production workloads, GPT-6.1 Terra is well suited for coding assistants, visual interface analysis, workflow automation, and scalable agentic applications that require reliable performance at an accessible cost. | Claude Opus 4.8 is Anthropic's most capable generally available model in the Opus family, designed for highly autonomous agents, long-horizon workflows, and advanced knowledge work. It supports text, image, and file inputs with text output, includes reasoning capabilities, and features a 1M-token context window for maintaining coherence across extended tasks and sessions. The model excels at multi-step reasoning, complex coding, and end-to-end project orchestration, including large codebases, multi-stage debugging, and long-running asynchronous agent pipelines. Beyond software engineering, it is highly effective for document drafting, presentation creation, data analysis, and memory-driven workflows, delivering consistent quality across very long outputs and complex projects. | Muse Spark Open is an open-weight, coding-optimized model designed for agentic software engineering workflows. It delivers strong first-attempt accuracy, reliable tool calling, and deep codebase understanding, enabling effective development across real-world repositories. Optimized for autonomous coding agents, complex code navigation, and tool-driven development, Muse Spark Open is well suited for software engineering automation, debugging, code generation, and multi-step coding workflows where accuracy and reliable execution are essential. |