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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 5.1AnthropicRemove
  2. Gemini Embedding 2GoogleRemove
  3. Muse Spark 1.3MetaRemove
claude-fable-5.1 vs gemini-embedding-2-preview vs muse-spark-1.3
AttributeClaude Fable 5.1claude-fable-5.1Gemini Embedding 2gemini-embedding-2-previewMuse Spark 1.3muse-spark-1.3
Pricing
Input$10.00 / 1M$0.60 / 1M$1.25 / 1M
Output$50.00 / 1M$2.40 / 1M$4.25 / 1M
Cache Write (5m)$12.50 / 1M$0.60 / 1M$1.25 / 1M
Cache Write (1h)$20.00 / 1M$0.60 / 1M$1.25 / 1M
Cache Read$1.00 / 1M$0.60 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context1M8.2K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderAnthropicGoogleMeta
Categorychatembeddingchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryClaude 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.Gemini Embedding 2 is Google's advanced text embedding model designed for high-accuracy semantic representation across large-scale retrieval and understanding tasks. It converts text into dense vector embeddings optimized for semantic search, retrieval-augmented generation (RAG), clustering, classification, and recommendation systems. Built for production use, it offers strong multilingual support, improved semantic similarity accuracy, and efficient embedding generation, making it well suited for large knowledge indexing pipelines and enterprise-scale retrieval applications.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.