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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 Astra ProOpenAIRemove
  2. Gemini 3.7 FlashGoogleRemove
  3. GPT-4o Mini TranscribeOpenAIRemove
gpt-6-astra-pro vs gemini-3.7-flash vs gpt-4o-mini-transcribe
AttributeGPT-6 Astra Progpt-6-astra-proGemini 3.7 Flashgemini-3.7-flashGPT-4o Mini Transcribegpt-4o-mini-transcribe
Pricing
Input$10.00 / 1M$0.375 / 1M$0.625 / 1M
Output$50.00 / 1M$1.88 / 1M$0.625 / 1M
Cache Write (5m)$10.00 / 1M$0.375 / 1MNot applicable
Cache Write (1h)$10.00 / 1M$0.375 / 1MNot applicable
Cache Read$10.00 / 1M$0.375 / 1MNot applicable
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M128K
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesNo
JSON ModeYesYesYes
StreamingYesYesNo
Catalogue
ProviderOpenAIGoogleOpenAI
Categorychatchatvoice
Charge typePay As You GoPay As You GoPay 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.Gemini 3.7 Flash is Google's fast multimodal model designed for agentic workflows, coding, and complex multi-step reasoning. It combines responsive inference with reliable problem-solving capabilities, making it well suited for interactive and production-scale applications. Optimized for speed and dependable multi-step execution, Gemini 3.7 Flash is a strong choice for coding assistants, autonomous agents, and high-throughput workflows that require both low latency and capable reasoning.GPT-4o Mini Transcribe is a smaller, cost-efficient speech-to-text model built on GPT-4o Mini's audio capabilities. It is designed for high-volume transcription workloads, delivering reliable performance with lower cost and latency. Priced per token (input and output), it provides transparent, fine-grained billing, making it well suited for scalable transcription pipelines, real-time applications, and cost-sensitive deployments.