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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. Muse Spark 1.3MetaRemove
  2. Claude Fable 5.1AnthropicRemove
  3. GPT-5.3-CodexOpenAIRemove
muse-spark-1.3 vs claude-fable-5.1 vs gpt-5.3-codex
AttributeMuse Spark 1.3muse-spark-1.3Claude Fable 5.1claude-fable-5.1GPT-5.3-Codexgpt-5.3-codex
Pricing
Input$1.25 / 1M$10.00 / 1M$1.75 / 1M
Output$4.25 / 1M$50.00 / 1M$14.00 / 1M
Cache Write (5m)$1.25 / 1M$12.50 / 1M$1.75 / 1M
Cache Write (1h)$1.25 / 1M$20.00 / 1M$1.75 / 1M
Cache Read$1.25 / 1M$1.00 / 1M$1.75 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M400K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderMetaAnthropicOpenAI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryMuse 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.Claude Fable 5.1 is an upgraded version of Fable 5, delivering broad improvements with particularly strong gains in agentic coding, long-running workflows, and professional knowledge work. It excels at large code refactors, front-end and visual code generation, financial analysis, and complex analytical tasks. Compared with Fable 5, it also produces more concise plans and summaries while maintaining strong performance across extended tasks, making it a natural upgrade for existing Fable workflows and a strong option alongside Opus 5 for reasoning-intensive applications.GPT-Codex-5.3 is OpenAI's most advanced agentic coding model, designed for software engineering workflows that extend beyond single prompts into long-running, tool-driven execution. It combines the frontier coding performance of earlier Codex models with stronger reasoning and professional knowledge capabilities, enabling reliable handling of complex refactors, multi-step debugging, research-driven development, and autonomous task execution. Optimized for developer productivity, GPT-Codex-5.3 supports interactive collaboration during execution, allowing users to steer tasks in real time without losing context. With improved agentic reliability, faster inference, and stronger performance on long-horizon engineering tasks, it is well suited for coding agents, IDE and CLI workflows, and end-to-end software development pipelines where persistence, tool use, and execution continuity are critical.