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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. o3 Deep ResearchOpenAIRemove
  2. Claude Fable 5.1AnthropicRemove
  3. Gemini 3.8 FlashGoogleRemove
o3-deep-research vs claude-fable-5.1 vs gemini-3.8-flash
Attributeo3 Deep Researcho3-deep-researchClaude Fable 5.1claude-fable-5.1Gemini 3.8 Flashgemini-3.8-flash
Pricing
Input$10.00 / 1M$10.00 / 1M$0.75 / 1M
Output$40.00 / 1M$50.00 / 1M$3.75 / 1M
Cache Write (5m)$10.00 / 1M$12.50 / 1M$0.75 / 1M
Cache Write (1h)$10.00 / 1M$20.00 / 1M$0.75 / 1M
Cache Read$10.00 / 1M$1.00 / 1M$0.75 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context200K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderOpenAIAnthropicGoogle
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
Summaryo3-deep-research is OpenAI's advanced research model, built for complex, multi-step investigation and analysis. It automatically performs web searches to gather and synthesize information — but this always incurs additional cost since web_search is used by default.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.Gemini 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality.