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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. Gemini 3.5 TranscribeGoogleRemove
  2. Claude Fable 5.1AnthropicRemove
  3. Gemini 3.8 FlashGoogleRemove
gemini-3.5-transcribe vs claude-fable-5.1 vs gemini-3.8-flash
AttributeGemini 3.5 Transcribegemini-3.5-transcribeClaude Fable 5.1claude-fable-5.1Gemini 3.8 Flashgemini-3.8-flash
Pricing
Input— Not priced per input token$10.00 / 1M$0.75 / 1M
Output— Not priced per output token$50.00 / 1M$3.75 / 1M
Cache Write (5m)Not applicable$12.50 / 1M$0.75 / 1M
Cache Write (1h)Not applicable$20.00 / 1M$0.75 / 1M
Cache ReadNot applicable$0.25 / 1M$0.75 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context98.3K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderGoogleAnthropicGoogle
Categoryvoicechatchat
Charge typePay As You GoPay As You GoPay As You Go
Released2026-09-25——
Description
SummaryGoogle Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.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.