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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. CommandCohereRemove
  3. Gemini 3.8 FlashGoogleRemove
  4. GLM 5.3Z.AIRemove

4 is the maximum. Remove one to add another.

gpt-6-astra vs command vs gemini-3.8-flash vs glm-5.3
AttributeGPT-6 Astragpt-6-astraCommandcommandGemini 3.8 Flashgemini-3.8-flashGLM 5.3glm-5.3
Pricing
Input$10.00 / 1M$0.95 / 1M$0.75 / 1M$1.40 / 1M
Output$50.00 / 1M$1.90 / 1M$3.75 / 1M$4.40 / 1M
Cache Write (5m)$10.00 / 1M$0.95 / 1M$0.75 / 1M$1.40 / 1M
Cache Write (1h)$10.00 / 1M$0.95 / 1M$0.75 / 1M$1.40 / 1M
Cache Read$10.00 / 1M$0.95 / 1M$0.75 / 1M$1.40 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M4.1K1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesNo
Function CallingYesNoYesYes
JSON ModeYesNoYesYes
StreamingYesNoYesYes
Catalogue
ProviderOpenAICohereGoogleZ.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.Gemini 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality.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.