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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. GLM 5.3Z.AIRemove
  3. Gemini 4 ArgonGoogleRemove
  4. Universal-3.5 ProAssemblyAIRemove

4 is the maximum. Remove one to add another.

hy4-preview vs glm-5.3 vs gemini-4-argon vs universal-3-5-pro
AttributeHy4 previewhy4-previewGLM 5.3glm-5.3Gemini 4 Argongemini-4-argonUniversal-3.5 Prouniversal-3-5-pro
Pricing
Input$0.834 / 1M$1.40 / 1M$2.00 / 1M— Not priced per input token
Output$2.50 / 1M$4.40 / 1M$10.00 / 1M— Not priced per output token
Cache Write (5m)$0.834 / 1M$1.40 / 1M$2.00 / 1MNot applicable
Cache Write (1h)$0.834 / 1M$1.40 / 1M$2.00 / 1MNot applicable
Cache Read$0.834 / 1M$1.40 / 1M$2.00 / 1MNot applicable
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M1MN/A
Max outputN/AN/AN/AN/A
Capabilities
VisionYesNoYesNo
Function CallingYesYesYesNo
JSON ModeYesYesYesNo
StreamingYesYesYesNo
Catalogue
ProviderTencentZ.AIGoogleAssemblyAI
Categorychatchatchatvoice
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.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.Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.AssemblyAI Universal-3.5 Pro speech-to-text. Billed per second of audio.