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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. GPT Image 2OpenAIRemove
  2. GLM 5.3Z.AIRemove
  3. GLM 5.3 FlashZ.AIRemove
gpt-image-2 vs glm-5.3 vs glm-5.3-flash
AttributeGPT Image 2gpt-image-2GLM 5.3glm-5.3GLM 5.3 Flashglm-5.3-flash
Pricing
Request$0.04 / request
BillingPay Per Request
Cache Write (5m)Not applicable$1.40 / 1M$0.075 / 1M
Cache Write (1h)Not applicable$1.40 / 1M$0.075 / 1M
Cache ReadNot applicable$1.40 / 1M$0.075 / 1M
Input$1.40 / 1M$0.075 / 1M
Output$4.40 / 1M$0.25 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context272K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderOpenAIZ.AIZ.AI
Categoryimagechatchat
Charge typePay Per RequestPay As You GoPay As You Go
Released
Description
SummaryGPT Image 2 combines OpenAI's GPT-5.4 with advanced image generation capabilities from GPT Image 2, enabling fully integrated multimodal workflows. It allows users to seamlessly transition between reasoning, coding, and visual generation within a single interaction, making it well suited for creative, development, and agent-driven applications that require both intelligence and visual output.GLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution.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.