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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. Qwen3.8 MaxAlibabaRemove
  2. GPT-6 Astra ProOpenAIRemove
  3. GLM 5.3 FlashZ.AIRemove
qwen3.8-max vs gpt-6-astra-pro vs glm-5.3-flash
AttributeQwen3.8 Maxqwen3.8-maxGPT-6 Astra Progpt-6-astra-proGLM 5.3 Flashglm-5.3-flash
Pricing
Input$2.00 / 1M$10.00 / 1M$0.075 / 1M
Output$6.00 / 1M$50.00 / 1M$0.25 / 1M
Cache Write (5m)$2.00 / 1M$10.00 / 1M$0.075 / 1M
Cache Write (1h)$2.00 / 1M$10.00 / 1M$0.075 / 1M
Cache Read$2.00 / 1M$10.00 / 1M$0.075 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderAlibabaOpenAIZ.AI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryQwen3.8 Max is the flagship model in Alibaba's Qwen3.8 series and the general-availability successor to Qwen3.8 Max Preview. It is a multimodal reasoning model designed for complex tasks across reasoning, visual understanding, coding, and agentic workflows. As the production-ready top tier of the Qwen3.8 family, it is well suited for advanced problem solving, multimodal analysis, software engineering, and long-running tool-driven applications.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-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.