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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. GPT-5 CodexOpenAIRemove
  3. Muse Spark 1.3MetaRemove
  4. Hy4 previewTencentRemove

4 is the maximum. Remove one to add another.

gpt-6-astra vs gpt-5-codex vs muse-spark-1.3 vs hy4-preview
AttributeGPT-6 Astragpt-6-astraGPT-5 Codexgpt-5-codexMuse Spark 1.3muse-spark-1.3Hy4 previewhy4-preview
Pricing
Input$10.00 / 1M$0.625 / 1M$1.25 / 1M$0.834 / 1M
Output$50.00 / 1M$5.00 / 1M$4.25 / 1M$2.50 / 1M
Cache Write (5m)$10.00 / 1M$0.625 / 1M$1.25 / 1M$0.834 / 1M
Cache Write (1h)$10.00 / 1M$0.625 / 1M$1.25 / 1M$0.834 / 1M
Cache Read$10.00 / 1M$0.625 / 1M$1.25 / 1M$0.834 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M400K1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderOpenAIOpenAIMetaTencent
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay 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-5 Codex is a coding-focused version of GPT-5 built for both interactive development and long autonomous engineering tasks. It can create projects, add features, debug, refactor, and review code, producing cleaner and more controllable outputs than GPT-5. It integrates with developer tools (CLI, IDEs, GitHub, cloud), supports adjustable reasoning effort, handles multimodal inputs, and uses tools for search and environment setup — making it purpose-built for agentic coding workflows.Muse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.Tencent Hy4 Preview is a Mixture-of-Experts (MoE) model from Tencent, featuring 770B total parameters with 49B activated per token. It is designed for coding agents, complex tool-driven workflows, and professional productivity tasks that require strong planning and reliable execution. Optimized for context continuity and sustained multi-step work, Hy4 Preview is well suited for long-horizon coding, agentic automation, tool orchestration, and complex real-world workflows.