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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. Muse WonderMetaRemove
  3. Universal-3.5 ProAssemblyAIRemove
  4. GLM 5.3Z.AIRemove

4 is the maximum. Remove one to add another.

hy4-preview vs muse-wonder vs universal-3-5-pro vs glm-5.3
AttributeHy4 previewhy4-previewMuse Wondermuse-wonderUniversal-3.5 Prouniversal-3-5-proGLM 5.3glm-5.3
Pricing
Input$0.834 / 1M$4.00 / 1M— Not priced per input token$1.40 / 1M
Output$2.50 / 1M$20.00 / 1M— Not priced per output token$4.40 / 1M
Cache Write (5m)$0.834 / 1M$4.00 / 1MNot applicable$1.40 / 1M
Cache Write (1h)$0.834 / 1M$4.00 / 1MNot applicable$1.40 / 1M
Cache Read$0.834 / 1M$4.00 / 1MNot applicable$1.40 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1MN/A1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesNoNo
Function CallingYesYesNoYes
JSON ModeYesYesNoYes
StreamingYesYesNoYes
Catalogue
ProviderTencentMetaAssemblyAIZ.AI
Categorychatchatvoicechat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released——2026-09-22—
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.Muse Wonder is Meta’s frontier multimodal reasoning model, designed for complex personal and professional agentic workflows. It supports text, image, video, audio, and PDF inputs with text output and features a 1M-token context window for sustained reasoning across long-running tasks. Optimized for autonomous execution and multi-agent orchestration, Muse Wonder can plan, delegate to subagents, coordinate parallel tool use, recover from errors, and operate browsers and applications across desktop and mobile environments. With cross-conversation context retrieval and its Active Focus training approach, it is well suited for complex software engineering, multi-file refactoring, computer use, and end-to-end workflows requiring persistence, adaptability, and minimal supervision.AssemblyAI Universal-3.5 Pro speech-to-text. Billed per second of audio.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.