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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. GPT-5.1-Codex-MaxOpenAIRemove
  3. GLM 5.3 FlashZ.AIRemove
gpt-6-astra-pro vs gpt-5.1-codex-max vs glm-5.3-flash
AttributeGPT-6 Astra Progpt-6-astra-proGPT-5.1-Codex-Maxgpt-5.1-codex-maxGLM 5.3 Flashglm-5.3-flash
Pricing
Input$10.00 / 1M$0.375 / 1M$0.075 / 1M
Output$50.00 / 1M$3.00 / 1M$0.25 / 1M
Cache Write (5m)$10.00 / 1M$0.375 / 1M$0.075 / 1M
Cache Write (1h)$10.00 / 1M$0.375 / 1M$0.075 / 1M
Cache Read$10.00 / 1M$0.375 / 1M$0.075 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M400K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderOpenAIOpenAIZ.AI
Categorychatchatchat
Charge typePay 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-5.1 Codex Max is OpenAI's advanced agentic coding model, built for long-running, high-context development work. Using an upgraded 5.1 reasoning stack and training on real engineering workflows, it delivers faster performance, stronger reasoning, and better token efficiency across the full software lifecycle.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.