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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. Hy4 previewTencentRemove
  3. Whisper Large V3 TurboOpenAIRemove
gpt-6-astra vs hy4-preview vs whisper-large-v3-turbo
AttributeGPT-6 Astragpt-6-astraHy4 previewhy4-previewWhisper Large V3 Turbowhisper-large-v3-turbo
Pricing
Input$10.00 / 1M$0.834 / 1M$3.33 / 1M
Output$50.00 / 1M$2.50 / 1M$0 / 1M
Cache Write (5m)$10.00 / 1M$0.834 / 1MNot applicable
Cache Write (1h)$10.00 / 1M$0.834 / 1MNot applicable
Cache Read$10.00 / 1M$0.834 / 1MNot applicable
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1MN/A
Max outputN/AN/AN/A
Capabilities
VisionYesYesNo
Function CallingYesYesNo
JSON ModeYesYesNo
StreamingYesYesNo
Catalogue
ProviderOpenAITencentOpenAI
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.Tencent Hy4 Preview is a Mixture-of-Experts (MoE) model from Tencent, featuring 770B total parameters with 49B activated per token. It is designed for coding agents, complex tool-driven workflows, and professional productivity tasks that require strong planning and reliable execution. Optimized for context continuity and sustained multi-step work, Hy4 Preview is well suited for long-horizon coding, agentic automation, tool orchestration, and complex real-world workflows.Whisper Large V3 Turbo is an optimized version of OpenAI's Whisper Large V3 speech recognition model, designed for high-speed and cost-efficient transcription. It supports 99+ languages and accepts common audio formats including mp3, mp4, wav, webm, flac, and ogg. With a ~12% word error rate and real-time speed factors up to 216×, it delivers fast, scalable performance for latency-sensitive and high-throughput transcription workloads, making it ideal for real-time and large-scale speech processing applications.