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 | Claude Opus 5.5claude-opus-5.5 | Muse Spark 1.3muse-spark-1.3 | Hy4 previewhy4-preview |
|---|---|---|---|
| Pricing | |||
| Input | $4.00 / 1M | $1.25 / 1M | $0.834 / 1M |
| Output | $20.00 / 1M | $4.25 / 1M | $2.50 / 1M |
| Cache Write (5m) | $5.00 / 1M | $1.25 / 1M | $0.834 / 1M |
| Cache Write (1h) | $8.00 / 1M | $1.25 / 1M | $0.834 / 1M |
| Cache Read | $0.40 / 1M | $1.25 / 1M | $0.834 / 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 | Yes | Yes | Yes |
| Catalogue | |||
| Provider | Anthropic | Meta | Tencent |
| Category | chat | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | — |
| Description | |||
| Summary | Claude Opus 5.5 is Anthropic's flagship model for advanced reasoning, coding, and long-horizon agentic workflows, succeeding Opus 5. It excels at multi-step changes across large codebases, code review and bug detection, financial and scientific analysis, and understanding dense charts, diagrams, and screenshots, with stronger grounding when reporting figures and citing sources. Compared with Opus 5, it completes comparable tasks with fewer steps and lower token usage while providing clearer, more concise progress reporting. With adaptive thinking and configurable effort levels, Opus 5.5 can balance reasoning depth, latency, and cost, making it well suited for both demanding autonomous workflows and latency-sensitive professional tasks. | 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. | Tencent Hy4 Preview is a Mixture-of-Experts (MoE) model from Tencent, featuring 770B total parameters with 49B activated per token. It is designed for coding agents, complex tool-driven workflows, and professional productivity tasks that require strong planning and reliable execution. Optimized for context continuity and sustained multi-step work, Hy4 Preview is well suited for long-horizon coding, agentic automation, tool orchestration, and complex real-world workflows. |