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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. Hy4 previewTencentRemove
  2. GPT-6 Astra ProOpenAIRemove
  3. GLM 5.3Z.AIRemove
  4. Whisper Large V3OpenAIRemove

4 is the maximum. Remove one to add another.

hy4-preview vs gpt-6-astra-pro vs glm-5.3 vs whisper-large-v3
AttributeHy4 previewhy4-previewGPT-6 Astra Progpt-6-astra-proGLM 5.3glm-5.3Whisper Large V3whisper-large-v3
Pricing
Input$0.834 / 1M$10.00 / 1M$1.40 / 1M$9.25 / 1M
Output$2.50 / 1M$50.00 / 1M$4.40 / 1M$0 / 1M
Cache Write (5m)$0.834 / 1M$10.00 / 1M$1.40 / 1MNot applicable
Cache Write (1h)$0.834 / 1M$10.00 / 1M$1.40 / 1MNot applicable
Cache Read$0.834 / 1M$10.00 / 1M$1.40 / 1MNot applicable
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1MN/A
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesNoNo
Function CallingYesYesYesNo
JSON ModeYesYesYesYes
StreamingYesYesYesNo
Catalogue
ProviderTencentOpenAIZ.AIOpenAI
Categorychatchatchatvoice
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryTencent 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.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.GLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution.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.