Skip to content

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.

  1. Claude Opus 5.5AnthropicRemove
  2. S1Fish AudioRemove
  3. Muse Spark 1.3MetaRemove
  4. GPT-6 Luna ProOpenAIRemove

4 is the maximum. Remove one to add another.

claude-opus-5.5 vs s1 vs muse-spark-1.3 vs gpt-6-luna-pro
AttributeClaude Opus 5.5claude-opus-5.5S1s1Muse Spark 1.3muse-spark-1.3GPT-6 Luna Progpt-6-luna-pro
Pricing
Input$4.00 / 1M$0 / 1M$1.25 / 1M$0.10 / 1M
Output$20.00 / 1M$0 / 1M$4.25 / 1M$0.50 / 1M
Cache Write (5m)$5.00 / 1MNot applicable$1.25 / 1M$0.10 / 1M
Cache Write (1h)$8.00 / 1MNot applicable$1.25 / 1M$0.10 / 1M
Cache Read$0.40 / 1MNot applicable$1.25 / 1M$0.10 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1MN/A1M1.1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesYes
Function CallingYesNoYesYes
JSON ModeYesNoYesYes
StreamingYesNoYesYes
Catalogue
ProviderAnthropicFish AudioMetaOpenAI
Categorychatvoicechatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released—2026-07-29——
Description
SummaryClaude 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.Fish Audio S1 text-to-speech. Billed per UTF-8 byte of input text.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.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.