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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. Codex MiniOpenAIRemove
  2. Muse Spark 1.3MetaRemove
  3. GPT-6 Astra ProOpenAIRemove
codex-mini vs muse-spark-1.3 vs gpt-6-astra-pro
AttributeCodex Minicodex-miniMuse Spark 1.3muse-spark-1.3GPT-6 Astra Progpt-6-astra-pro
Pricing
Input$0.75 / 1M$1.25 / 1M$10.00 / 1M
Output$3.00 / 1M$4.25 / 1M$50.00 / 1M
Cache Write (5m)$0.75 / 1M$1.25 / 1M$10.00 / 1M
Cache Write (1h)$0.75 / 1M$1.25 / 1M$10.00 / 1M
Cache Read$0.75 / 1M$1.25 / 1M$10.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context200K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderOpenAIMetaOpenAI
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummaryCodex Mini is a fine-tuned o4-mini model made for the Codex CLI. For most direct API usage, it’s better to use gpt-4.1 instead.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.GPT-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.