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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. Gemini 3.7 FlashGoogleRemove
  3. Gemini 4 ArgonGoogleRemove
perceptron-mk1.5 vs gemini-3.7-flash vs gemini-4-argon
AttributePerceptron Mk1.5perceptron-mk1.5Gemini 3.7 Flashgemini-3.7-flashGemini 4 Argongemini-4-argon
Pricing
Input$0.15 / 1M$0.375 / 1M$2.00 / 1M
Output$1.50 / 1M$1.88 / 1M$10.00 / 1M
Cache Write (5m)$0.15 / 1M$0.375 / 1M$2.00 / 1M
Cache Write (1h)$0.15 / 1M$0.375 / 1M$2.00 / 1M
Cache Read$0.15 / 1M$0.375 / 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
ProviderPerceptronGoogleGoogle
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.Gemini 3.7 Flash is Google's fast multimodal model designed for agentic workflows, coding, and complex multi-step reasoning. It combines responsive inference with reliable problem-solving capabilities, making it well suited for interactive and production-scale applications. Optimized for speed and dependable multi-step execution, Gemini 3.7 Flash is a strong choice for coding assistants, autonomous agents, and high-throughput workflows that require both low latency and capable reasoning.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.