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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 AstraOpenAIRemove
  2. mai-ds-r1:freeNot in the catalogueRemove
  3. GPT-6 LunaOpenAIRemove
  4. Muse WonderMetaRemove

4 is the maximum. Remove one to add another.

gpt-6-astra vs mai-ds-r1:free vs gpt-6-luna vs muse-wonder
AttributeGPT-6 Astragpt-6-astramai-ds-r1:freeNot in the catalogueGPT-6 Lunagpt-6-lunaMuse Wondermuse-wonder
Pricing
Input$10.00 / 1M—$0.10 / 1M$4.00 / 1M
Output$50.00 / 1M—$0.50 / 1M$20.00 / 1M
Cache Write (5m)$10.00 / 1M—$0.10 / 1M$4.00 / 1M
Cache Write (1h)$10.00 / 1M—$0.10 / 1M$4.00 / 1M
Cache Read$10.00 / 1M—$0.10 / 1M$4.00 / 1M
Web Search$0 / 1M—$0 / 1M$0 / 1M
Context
Max context1M—1.1M1M
Max outputN/A—N/AN/A
Capabilities
VisionYes—YesYes
Function CallingYes—YesYes
JSON ModeYes—YesYes
StreamingYes—YesYes
Catalogue
ProviderOpenAI—OpenAIMeta
Categorychat—chatchat
Charge typePay As You Go—Pay As You GoPay As You Go
Released————
Description
SummaryGPT-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.—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.Muse Wonder is Meta’s frontier multimodal reasoning model, designed for complex personal and professional agentic workflows. It supports text, image, video, audio, and PDF inputs with text output and features a 1M-token context window for sustained reasoning across long-running tasks. Optimized for autonomous execution and multi-agent orchestration, Muse Wonder can plan, delegate to subagents, coordinate parallel tool use, recover from errors, and operate browsers and applications across desktop and mobile environments. With cross-conversation context retrieval and its Active Focus training approach, it is well suited for complex software engineering, multi-file refactoring, computer use, and end-to-end workflows requiring persistence, adaptability, and minimal supervision.