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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. Veo 3GoogleRemove
  2. Gemini 3.8 FlashGoogleRemove
  3. GPT-6 Astra ProOpenAIRemove
  4. GLM 5.3Z.AIRemove

4 is the maximum. Remove one to add another.

veo3 vs gemini-3.8-flash vs gpt-6-astra-pro vs glm-5.3
AttributeVeo 3veo3Gemini 3.8 Flashgemini-3.8-flashGPT-6 Astra Progpt-6-astra-proGLM 5.3glm-5.3
Pricing
Request$1.26 / request
BillingPay Per Request
Cache Write (5m)Not applicable$0.75 / 1M$10.00 / 1M$1.40 / 1M
Cache Write (1h)Not applicable$0.75 / 1M$10.00 / 1M$1.40 / 1M
Cache ReadNot applicable$0.75 / 1M$10.00 / 1M$1.40 / 1M
Input$0.75 / 1M$10.00 / 1M$1.40 / 1M
Output$3.75 / 1M$50.00 / 1M$4.40 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max contextN/A1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesYesNo
Function CallingNoYesYesYes
JSON ModeNoYesYesYes
StreamingNoYesYesYes
Catalogue
ProviderGoogleGoogleOpenAIZ.AI
Categoryvideochatchatchat
Charge typePay Per RequestPay As You GoPay As You GoPay As You Go
Released
Description
SummaryGemini 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality.GPT-6 Astra Pro uses the same underlying model as GPT-6 Astra, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. Optimized for deeper reasoning, greater accuracy, and more reliable multi-step execution, it is well suited for demanding coding, analysis, and agentic workflows where solution quality takes priority over speed and cost.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.