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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. Gemini 3.7 FlashGoogleRemove
  2. GPT Image 2OpenAIRemove
  3. GLM 5.3 FlashZ.AIRemove
gemini-3.7-flash vs gpt-image-2 vs glm-5.3-flash
AttributeGemini 3.7 Flashgemini-3.7-flashGPT Image 2gpt-image-2GLM 5.3 Flashglm-5.3-flash
Pricing
Input$0.375 / 1M$0.075 / 1M
Output$1.88 / 1M$0.25 / 1M
Cache Write (5m)$0.375 / 1MNot applicable$0.075 / 1M
Cache Write (1h)$0.375 / 1MNot applicable$0.075 / 1M
Cache Read$0.375 / 1MNot applicable$0.075 / 1M
Web Search$0 / 1M$0 / 1M
Request$0.04 / request
BillingPay Per Request
Context
Max context1M272K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesNoYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderGoogleOpenAIZ.AI
Categorychatimagechat
Charge typePay As You GoPay Per RequestPay As You Go
Released
Description
SummaryGemini 3.7 Flash is Google's fast multimodal model designed for agentic workflows, coding, and complex multi-step reasoning. It combines responsive inference with reliable problem-solving capabilities, making it well suited for interactive and production-scale applications. Optimized for speed and dependable multi-step execution, Gemini 3.7 Flash is a strong choice for coding assistants, autonomous agents, and high-throughput workflows that require both low latency and capable reasoning.GPT 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-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.