Skip to content

Compare models

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 3.1 Flash Image (Google Vertex AI)GoogleEnterprise & partner accessRemove
  2. Perceptron Mk1.5PerceptronRemove
  3. Gemini 4 ArgonGoogleRemove
gemini-3.1-flash-image-vertex vs perceptron-mk1.5 vs gemini-4-argon
AttributeGemini 3.1 Flash Image (Google Vertex AI)gemini-3.1-flash-image-vertexPerceptron Mk1.5perceptron-mk1.5Gemini 4 Argongemini-4-argon
Pricing
Request$0.067 / request——
BillingPay Per Request——
Cache Write (5m)Not applicable$0.15 / 1M$2.00 / 1M
Cache Write (1h)Not applicable$0.15 / 1M$2.00 / 1M
Cache ReadNot applicable$0.15 / 1M$2.00 / 1M
Input—$0.15 / 1M$2.00 / 1M
Output—$1.50 / 1M$10.00 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max contextN/A36.9K1M
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingNoNoYes
JSON ModeNoNoYes
StreamingNoYesYes
Catalogue
ProviderGooglePerceptronGoogle
Categoryimagechatchat
Charge typePay Per RequestPay As You GoPay As You Go
Released—2026-09-25—
Description
SummaryGemini 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.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.