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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 Luna ProOpenAIRemove
  2. GPT-6 LunaOpenAIRemove
  3. GLM 5 TurboZ.AIRemove
gpt-6-luna-pro vs gpt-6-luna vs glm-5-turbo
AttributeGPT-6 Luna Progpt-6-luna-proGPT-6 Lunagpt-6-lunaGLM 5 Turboglm-5-turbo
Pricing
Input$0.10 / 1M$0.10 / 1M$0.96 / 1M
Output$0.50 / 1M$0.50 / 1M$3.20 / 1M
Cache Write (5m)$0.10 / 1M$0.10 / 1M$0.96 / 1M
Cache Write (1h)$0.10 / 1M$0.10 / 1M$0.96 / 1M
Cache Read$0.10 / 1M$0.10 / 1M$0.96 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1.1M1.1M202.8K
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 Luna Pro uses the same underlying model as GPT-6 Luna, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. It combines Luna's speed and cost efficiency with deeper reasoning and more reliable multi-step execution, making it well suited for advanced coding, computer use, and agentic workflows where higher solution quality is needed without moving to a larger GPT-6 tier.GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, optimized for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic tasks. It combines low-cost, responsive inference with the GPT-6 family’s improvements in factual reliability and clear, concise communication. At higher reasoning effort, GPT-6 Luna can also handle complex software engineering and computer-use workflows that previously required a Sol-tier model, making it a versatile choice for scalable production applications that need to balance speed, cost, and capability.GLM-5 Turbo is a high-performance model from Z.ai optimized for fast inference and agent-driven workflows. Designed for real-world environments such as OpenClaw scenarios, it delivers strong performance across long execution chains and complex task pipelines. The model features improved instruction decomposition, tool integration, scheduled and persistent execution, and enhanced stability for extended multi-step tasks, making it well suited for autonomous agents and production automation workflows.