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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 3.1 Flash Image (Google Vertex AI)GoogleEnterprise & partner accessRemove
  3. Gemini 4 ArgonGoogleRemove
perceptron-mk1.5 vs gemini-3.1-flash-image-vertex vs gemini-4-argon
AttributePerceptron Mk1.5perceptron-mk1.5Gemini 3.1 Flash Image (Google Vertex AI)gemini-3.1-flash-image-vertexGemini 4 Argongemini-4-argon
Pricing
Input$0.15 / 1M—$2.00 / 1M
Output$1.50 / 1M—$10.00 / 1M
Cache Write (5m)$0.15 / 1MNot applicable$2.00 / 1M
Cache Write (1h)$0.15 / 1MNot applicable$2.00 / 1M
Cache Read$0.15 / 1MNot applicable$2.00 / 1M
Web Search$0 / 1M—$0 / 1M
Request—$0.067 / request—
Billing—Pay Per Request—
Context
Max context36.9KN/A1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoNoYes
JSON ModeNoNoYes
StreamingYesNoYes
Catalogue
ProviderPerceptronGoogleGoogle
Categorychatimagechat
Charge typePay As You GoPay Per RequestPay 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 3.1 Flash Image served from Google Vertex AI. Billed per image at US$0.067. Call it through /v1/chat/completions with stream set to false; the image is returned in the message content as a base64 data URI. Maximum output resolution is 2K. A request for a larger size, such as 4K or 4096x4096, returns a 2K image with the same aspect ratio at the same price. When a size is reduced, the response carries an X-Image-Resolution-Capped header with the requested and delivered size, for example 4096x4096->2048x2048.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.