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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-6 Astra ProOpenAIRemove
  2. Seedream 5.0 LiteByteDanceRemove
  3. GLM 5.3Z.AIRemove
gpt-6-astra-pro vs doubao-seedream-5-0-260128 vs glm-5.3
AttributeGPT-6 Astra Progpt-6-astra-proSeedream 5.0 Litedoubao-seedream-5-0-260128GLM 5.3glm-5.3
Pricing
Input$10.00 / 1M$1.40 / 1M
Output$50.00 / 1M$4.40 / 1M
Cache Write (5m)$10.00 / 1MNot applicable$1.40 / 1M
Cache Write (1h)$10.00 / 1MNot applicable$1.40 / 1M
Cache Read$10.00 / 1MNot applicable$1.40 / 1M
Web Search$0 / 1M$0 / 1M
Request$0.235 / request
BillingPay Per Request
Context
Max context1M128K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesNoYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderOpenAIByteDanceZ.AI
Categorychatimagechat
Charge typePay As You GoPay Per RequestPay As You Go
Released
Description
SummaryGPT-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.Doubao-Seedream 5.0 Lite is ByteDance's optimized text-to-image generation model designed for fast, cost-efficient visual creation while retaining strong visual quality. It offers improved prompt understanding and rendering performance over previous "Lite" variants, making it suitable for real-time applications and interactive creative workflows. With a focus on speed, responsiveness, and lightweight deployment, Seedream 5.0-Lite enables rapid generation of visually appealing images across a wide range of styles and scenarios, making it ideal for user-facing creative tools and large-scale content pipelines.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.