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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. Muse Spark 1.3MetaRemove
  3. Gemini 3.5 FlashGoogleRemove
claude-fable-5.1 vs muse-spark-1.3 vs gemini-3.5-flash
AttributeClaude Fable 5.1claude-fable-5.1Muse Spark 1.3muse-spark-1.3Gemini 3.5 Flashgemini-3.5-flash
Pricing
Input$10.00 / 1M$1.25 / 1M$1.50 / 1M
Output$50.00 / 1M$4.25 / 1M$9.00 / 1M
Cache Write (5m)$12.50 / 1M$1.25 / 1M$1.50 / 1M
Cache Write (1h)$20.00 / 1M$1.25 / 1M$1.50 / 1M
Cache Read$1.00 / 1M$1.25 / 1M$1.50 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderAnthropicMetaGoogle
Categorychatchatchat
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.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.Gemini 3.5 Flash is Google's high-efficiency multimodal model, delivering near-Pro level performance in coding and reasoning at Flash-tier speed and cost. It supports text, image, video, audio, and PDF inputs, making it well suited for diverse multimodal workflows. Optimized for coding proficiency and parallel agentic execution, the model defaults to medium thinking effort for faster, cost-efficient responses while supporting configurable thinking levels (minimal, low, medium, high) for fine-grained cost–performance control.