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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. DeepSeek R1DeepSeekRemove
  2. GPT-6 AstraOpenAIRemove
  3. Muse Spark 1.3MetaRemove
  4. GLM 5.3Z.AIRemove

4 is the maximum. Remove one to add another.

deepseek-r1 vs gpt-6-astra vs muse-spark-1.3 vs glm-5.3
AttributeDeepSeek R1deepseek-r1GPT-6 Astragpt-6-astraMuse Spark 1.3muse-spark-1.3GLM 5.3glm-5.3
Pricing
Input$0.50 / 1M$10.00 / 1M$1.25 / 1M$1.40 / 1M
Output$2.18 / 1M$50.00 / 1M$4.25 / 1M$4.40 / 1M
Cache Write (5m)$0.50 / 1M$10.00 / 1M$1.25 / 1M$1.40 / 1M
Cache Write (1h)$0.50 / 1M$10.00 / 1M$1.25 / 1M$1.40 / 1M
Cache Read$0.50 / 1M$10.00 / 1M$1.25 / 1M$1.40 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context163.8K1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesYesNo
Function CallingNoYesYesYes
JSON ModeNoYesYesYes
StreamingNoYesYesYes
Catalogue
ProviderDeepSeekOpenAIMetaZ.AI
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.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.GLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution.