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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. Grok 4.5xAIRemove
  2. Gemini 3.1 Flash Image (Google Vertex AI)GoogleEnterprise & partner accessRemove
  3. Gemini 4 ArgonGoogleRemove
grok-4.5 vs gemini-3.1-flash-image-vertex vs gemini-4-argon
AttributeGrok 4.5grok-4.5Gemini 3.1 Flash Image (Google Vertex AI)gemini-3.1-flash-image-vertexGemini 4 Argongemini-4-argon
Pricing
Input$2.00 / 1M—$2.00 / 1M
Output$6.00 / 1M—$10.00 / 1M
Cache Write (5m)$2.00 / 1MNot applicable$2.00 / 1M
Cache Write (1h)$2.00 / 1MNot applicable$2.00 / 1M
Cache Read$2.00 / 1MNot applicable$2.00 / 1M
Web Search$0 / 1M—$0 / 1M
Request—$0.067 / request—
Billing—Pay Per Request—
Context
Max context500KN/A1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesNoYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderxAIGoogleGoogle
Categorychatimagechat
Charge typePay As You GoPay Per RequestPay As You Go
Released———
Description
SummaryGrok 4.5 is SpaceXAI’s flagship frontier model, delivering top-tier performance across coding, knowledge work, and STEM reasoning. Designed for demanding professional and technical workloads, it combines strong reasoning, accurate instruction following, and robust problem-solving capabilities. Optimized for software engineering, scientific analysis, and complex knowledge tasks, Grok 4.5 is well suited for advanced coding, research, and agent-driven workflows that require high accuracy and reliable long-horizon reasoning.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.