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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. Claude Sonnet 5.5AnthropicRemove
  2. Gemini 3.1 Flash Image (Google Vertex AI)GoogleRemove
  3. GLM 5.3 FlashZ.AIRemove
claude-sonnet-5.5 vs gemini-3.1-flash-image-vertex vs glm-5.3-flash
AttributeClaude Sonnet 5.5claude-sonnet-5.5Gemini 3.1 Flash Image (Google Vertex AI)gemini-3.1-flash-image-vertexGLM 5.3 Flashglm-5.3-flash
Pricing
Input$2.00 / 1M—$0.075 / 1M
Output$10.00 / 1M—$0.25 / 1M
Cache Write (5m)$2.50 / 1MNot applicable$0.075 / 1M
Cache Write (1h)$4.00 / 1MNot applicable$0.075 / 1M
Cache Read$0.10 / 1MNot applicable$0.075 / 1M
Web Search$0 / 1M—$0 / 1M
Request—$0.067 / request—
Billing—Pay Per Request—
Context
Max context1MN/A1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesNoYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderAnthropicGoogleZ.AI
Categorychatimagechat
Charge typePay As You GoPay Per RequestPay As You Go
Released———
Description
SummaryClaude Sonnet 5.5 is Anthropic's Sonnet-class model for well-scoped everyday work, serving as a direct upgrade to Sonnet 5. It excels at feature development, bug fixing, and creating polished documents, presentations, and spreadsheets, while offering clearer writing and communication than its predecessor.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.GLM-5.3-Flash is Z.AI's efficient native multimodal model, designed for coding and long-horizon agentic workflows. It combines strong multimodal capabilities with an architecture optimized for responsive, cost-efficient task execution. Built on a hybrid sparse and linear attention architecture, GLM-5.3-Flash maintains accurate long-context behavior while reducing computational overhead, making it well suited for coding agents, extended multi-step tasks, and scalable production workloads.