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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 Astra ProOpenAIRemove
  2. Nemotron 3 Ultra (Free)NVIDIARemove
  3. GLM 5.3Z.AIRemove
gpt-6-astra-pro vs nemotron-3-ultra-550b-a55b:free vs glm-5.3
AttributeGPT-6 Astra Progpt-6-astra-proNemotron 3 Ultra (Free)nemotron-3-ultra-550b-a55b:freeGLM 5.3glm-5.3
Pricing
Input$10.00 / 1M$0 / 1M$1.40 / 1M
Output$50.00 / 1M$0 / 1M$4.40 / 1M
Cache Write (5m)$10.00 / 1M$1.40 / 1M
Cache Write (1h)$10.00 / 1M$1.40 / 1M
Cache Read$10.00 / 1M$0 / 1M$1.40 / 1M
Web Search$0 / 1M$0 / 1M
Cache Write$0 / 1M
Context
Max context1M1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderOpenAINVIDIAZ.AI
Categorychatchatchat
Charge typePay As You GoFreePay As You Go
Released
Description
SummaryGPT-6 Astra Pro uses the same underlying model as GPT-6 Astra, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. Optimized for deeper reasoning, greater accuracy, and more reliable multi-step execution, it is well suited for demanding coding, analysis, and agentic workflows where solution quality takes priority over speed and cost.NVIDIA Nemotron 3 Ultra is an open frontier reasoning and orchestration model featuring a 550B-parameter Mixture-of-Experts (MoE) architecture with 55B active parameters per token. Built on a hybrid Transformer–Mamba design, it supports text input and output with a 1M-token context window, enabling large-scale reasoning and long-horizon task execution. Optimized for agent orchestration, coding agents, deep research, and complex enterprise workflows, the model excels at multi-step reasoning, planning, and sustained execution. With high-throughput inference designed for large-scale agent pipelines, Nemotron 3 Ultra serves as a powerful foundation for advanced agentic AI systems.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.