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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. Sonar ReasoningPerplexityRemove
  2. GPT-6 Astra ProOpenAIRemove
  3. GPT-6 AstraOpenAIRemove
  4. GLM 5.3Z.AIRemove

4 is the maximum. Remove one to add another.

sonar-reasoning vs gpt-6-astra-pro vs gpt-6-astra vs glm-5.3
AttributeSonar Reasoningsonar-reasoningGPT-6 Astra Progpt-6-astra-proGPT-6 Astragpt-6-astraGLM 5.3glm-5.3
Pricing
Input$1.00 / 1M$10.00 / 1M$10.00 / 1M$1.40 / 1M
Output$5.00 / 1M$50.00 / 1M$50.00 / 1M$4.40 / 1M
Cache Write (5m)$1.00 / 1M$10.00 / 1M$10.00 / 1M$1.40 / 1M
Cache Write (1h)$1.00 / 1M$10.00 / 1M$10.00 / 1M$1.40 / 1M
Cache Read$1.00 / 1M$10.00 / 1M$10.00 / 1M$1.40 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context127K1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesYesNo
Function CallingNoYesYesYes
JSON ModeNoYesYesYes
StreamingNoYesYesYes
Catalogue
ProviderPerplexityOpenAIOpenAIZ.AI
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay 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.GPT-6 Astra is OpenAI's flagship model for demanding end-to-end professional work, designed for advanced analysis, software engineering, deep research, scientific tasks, and document creation. It is particularly strong in long-horizon agentic workflows, including tasks that require sustained reasoning, tool orchestration, and computer and browser use, making it well suited for complex autonomous workflows and production-grade knowledge work.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.