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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. Claude Fable 5.2AnthropicRemove
  2. GPT-4o TranscribeOpenAIRemove
  3. Muse Spark OpenMetaRemove
claude-fable-5.2 vs gpt-4o-transcribe vs muse-spark-open
AttributeClaude Fable 5.2claude-fable-5.2GPT-4o Transcribegpt-4o-transcribeMuse Spark Openmuse-spark-open
Pricing
Input$8.00 / 1M$1.25 / 1M$1.25 / 1M
Output$40.00 / 1M— Not priced per output token$4.25 / 1M
Cache Write (5m)$10.00 / 1MNot applicable$1.25 / 1M
Cache Write (1h)$16.00 / 1MNot applicable$1.25 / 1M
Cache Read$0.20 / 1MNot applicable$1.25 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M128K1M
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingYesNoYes
JSON ModeYesYesYes
StreamingYesNoYes
Catalogue
ProviderAnthropicOpenAIMeta
Categorychatvoicechat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummaryClaude Fable 5.2 is Anthropic's most capable model for advanced technical work and open-ended problem solving, delivering significant improvements in coding, reasoning, and vision over Fable 5.1. It excels at exceptionally complex tasks, including large-scale software migrations, electronic system design, and advanced scientific and mathematical research. With up to 30% faster output generation, clearer communication, and always-on adaptive extended thinking, Fable 5.2 supports configurable reasoning effort from low to max (default high), with thinking preserved across turns. Designed for frontier engineering, scientific discovery, and ambitious long-horizon agentic workflows, it complements Opus 5.5 as a specialized option for the most demanding technical challenges.GPT-4o Transcribe is OpenAI's high-quality speech-to-text model built on GPT-4o's audio capabilities. It delivers accurate transcription with strong language understanding, making it suitable for a wide range of audio processing tasks. Priced per token (input and output), it offers transparent, fine-grained billing, making it well suited for workflows that require scalable transcription, integration with LLM pipelines, and cost-aware processing.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.