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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 3.5 Content Safety (Free)NVIDIARemove
  3. Muse Spark 1.3MetaRemove
gpt-6-astra-pro vs nemotron-3.5-content-safety:free vs muse-spark-1.3
AttributeGPT-6 Astra Progpt-6-astra-proNemotron 3.5 Content Safety (Free)nemotron-3.5-content-safety:freeMuse Spark 1.3muse-spark-1.3
Pricing
Input$10.00 / 1M$0 / 1M$1.25 / 1M
Output$50.00 / 1M$0 / 1M$4.25 / 1M
Cache Write (5m)$10.00 / 1M$1.25 / 1M
Cache Write (1h)$10.00 / 1M$1.25 / 1M
Cache Read$10.00 / 1M$0 / 1M$1.25 / 1M
Web Search$0 / 1M$0 / 1M
Cache Write$0 / 1M
Context
Max context1M128K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderOpenAINVIDIAMeta
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 3.5 Content Safety is a compact 4B-parameter multimodal guardrail model from NVIDIA, designed for content moderation, safety classification, and AI policy enforcement. Supporting text and image inputs with text output, it evaluates both user prompts and model responses, providing safe/unsafe classifications, safety category labels, and optional reasoning traces. Fine-tuned from Gemma-3-4B and supporting 12 languages with a 128K-token context window, the model is well suited for prompt moderation, response filtering, content classification, and enterprise safety pipelines. As part of the NVIDIA Nemotron family, it offers a configurable reasoning mode and integrates easily into agentic AI systems requiring robust guardrails and compliance controls.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.