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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 Lite Image (Google Vertex AI)GoogleRemove
  2. GPT TranscribeOpenAIRemove
  3. Gemini 4 ArgonGoogleRemove
gemini-3.1-flash-lite-image-vertex vs gpt-transcribe vs gemini-4-argon
AttributeGemini 3.1 Flash Lite Image (Google Vertex AI)gemini-3.1-flash-lite-image-vertexGPT Transcribegpt-transcribeGemini 4 Argongemini-4-argon
Pricing
Request$0.0336 / 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—— Not priced per input token$2.00 / 1M
Output—— Not priced per output token$10.00 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max contextN/AN/A1M
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingNoNoYes
JSON ModeNoNoYes
StreamingNoNoYes
Catalogue
ProviderGoogleOpenAIGoogle
Categoryimagevoicechat
Charge typePay Per RequestPay As You GoPay As You Go
Released—2026-08-05—
Description
SummaryGemini 3.1 Flash Lite Image served from Google Vertex AI. Billed per image at US$0.0336. 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 1K. A request for a larger size returns a 1K 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.OpenAI GPT Transcribe speech-to-text. Billed per second of audio.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.