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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. Claude Sonnet 5AnthropicRemove
  2. Gemini 4 ArgonGoogleRemove
  3. Gemini 3.1 Flash Image (Google Vertex AI)GoogleEnterprise & partner accessRemove
claude-sonnet-5 vs gemini-4-argon vs gemini-3.1-flash-image-vertex
AttributeClaude Sonnet 5claude-sonnet-5Gemini 4 Argongemini-4-argonGemini 3.1 Flash Image (Google Vertex AI)gemini-3.1-flash-image-vertex
Pricing
Input$2.00 / 1M$2.00 / 1M—
Output$10.00 / 1M$10.00 / 1M—
Cache Write (5m)$2.50 / 1M$2.00 / 1MNot applicable
Cache Write (1h)$4.00 / 1M$2.00 / 1MNot applicable
Cache Read$0.20 / 1M$2.00 / 1MNot applicable
Web Search$0 / 1M$0 / 1M—
Request——$0.067 / request
Billing——Pay Per Request
Context
Max context1M1MN/A
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingYesYesNo
Catalogue
ProviderAnthropicGoogleGoogle
Categorychatchatimage
Charge typePay As You GoPay As You GoPay Per Request
Released———
Description
SummarySonnet 5 is Anthropic's most capable Sonnet-class model, delivering frontier-level performance across coding, agentic workflows, and professional knowledge tasks. It supports text, image, and file inputs, features a 1M-token context window, and offers adaptive thinking with configurable reasoning levels (low, medium, high, max, and x-high) to balance speed, cost, and reasoning depth. Optimized for complex coding, long-horizon agent execution, and professional workflows, Sonnet 5 combines strong reasoning, robust instruction following, and enhanced safety features, including an updated tokenizer and real-time cyber safeguards for high-risk dual-use scenarios.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.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.