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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. mai-ds-r1:freeNot in the catalogueRemove
  2. Gemini 3.8 FlashGoogleRemove
  3. Perceptron Mk1.5PerceptronRemove
  4. Gemini 4 ArgonGoogleRemove

4 is the maximum. Remove one to add another.

mai-ds-r1:free vs gemini-3.8-flash vs perceptron-mk1.5 vs gemini-4-argon
Attributemai-ds-r1:freeNot in the catalogueGemini 3.8 Flashgemini-3.8-flashPerceptron Mk1.5perceptron-mk1.5Gemini 4 Argongemini-4-argon
Pricing
Input—$0.75 / 1M$0.15 / 1M$2.00 / 1M
Output—$3.75 / 1M$1.50 / 1M$10.00 / 1M
Cache Write (5m)—$0.75 / 1M$0.15 / 1M$2.00 / 1M
Cache Write (1h)—$0.75 / 1M$0.15 / 1M$2.00 / 1M
Cache Read—$0.75 / 1M$0.15 / 1M$2.00 / 1M
Web Search—$0 / 1M$0 / 1M$0 / 1M
Context
Max context—1M36.9K1M
Max output—N/AN/AN/A
Capabilities
Vision—YesNoYes
Function Calling—YesNoYes
JSON Mode—YesNoYes
Streaming—YesYesYes
Catalogue
Provider—GooglePerceptronGoogle
Category—chatchatchat
Charge type—Pay As You GoPay As You GoPay As You Go
Released——2026-09-25—
Description
Summary—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.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.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.