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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. Gemini 3.7 FlashGoogleRemove
  3. Whisper Large V3OpenAIRemove
gpt-6-astra vs gemini-3.7-flash vs whisper-large-v3
AttributeGPT-6 Astragpt-6-astraGemini 3.7 Flashgemini-3.7-flashWhisper Large V3whisper-large-v3
Pricing
Input$10.00 / 1M$0.375 / 1M$9.25 / 1M
Output$50.00 / 1M$1.88 / 1M$0 / 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 context1M1MN/A
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 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 3.7 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.Whisper Large V3 is OpenAI's advanced open-source automatic speech recognition (ASR) model, supporting both audio transcription and translation across 99+ languages. It accepts common audio formats including mp3, mp4, wav, webm, flac, and ogg, and delivers strong performance in noisy, real-world conditions. With 1.55B parameters and a low 10.3% word error rate, it provides accurate, multilingual transcription with support for word- and segment-level timestamps, making it well suited for high-quality, noise-robust speech processing applications.