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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. Gemini 3.1 Flash Image (Google Vertex AI)GoogleEnterprise & partner accessRemove
  2. Qwen3 Reranker 4BRerankerRemove
  3. Gemini 4 ArgonGoogleRemove
gemini-3.1-flash-image-vertex vs Qwen/Qwen3-Reranker-4B vs gemini-4-argon
AttributeGemini 3.1 Flash Image (Google Vertex AI)gemini-3.1-flash-image-vertexQwen3 Reranker 4BQwen/Qwen3-Reranker-4BGemini 4 Argongemini-4-argon
Pricing
Request$0.067 / request——
BillingPay Per Request——
Cache Write (5m)Not applicableNot applicable$2.00 / 1M
Cache Write (1h)Not applicableNot applicable$2.00 / 1M
Cache ReadNot applicableNot applicable$2.00 / 1M
Input—$0.28 / 1M$2.00 / 1M
Output—$0.28 / 1M$10.00 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max contextN/A8.2K1M
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingNoNoYes
JSON ModeNoNoYes
StreamingNoNoYes
Catalogue
ProviderGoogleRerankerGoogle
Categoryimagechatchat
Charge typePay Per RequestPay As You GoPay As You Go
Released———
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.—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.