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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. Perceptron Mk1.5PerceptronRemove
  2. Claude Fable 5.1AnthropicRemove
  3. Gemini 4 ArgonGoogleRemove
perceptron-mk1.5 vs claude-fable-5.1 vs gemini-4-argon
AttributePerceptron Mk1.5perceptron-mk1.5Claude Fable 5.1claude-fable-5.1Gemini 4 Argongemini-4-argon
Pricing
Input$0.15 / 1M$10.00 / 1M$2.00 / 1M
Output$1.50 / 1M$50.00 / 1M$10.00 / 1M
Cache Write (5m)$0.15 / 1M$12.50 / 1M$2.00 / 1M
Cache Write (1h)$0.15 / 1M$20.00 / 1M$2.00 / 1M
Cache Read$0.15 / 1M$0.25 / 1M$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context36.9K1M1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingYesYesYes
Catalogue
ProviderPerceptronAnthropicGoogle
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released2026-09-25——
Description
SummaryPerceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per 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 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.