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

4 is the maximum. Remove one to add another.

gemini-4-argon vs muse-wonder vs glm-5.3 vs universal-3-5-pro
AttributeGemini 4 Argongemini-4-argonMuse Wondermuse-wonderGLM 5.3glm-5.3Universal-3.5 Prouniversal-3-5-pro
Pricing
Input$2.00 / 1M$4.00 / 1M$1.40 / 1M— Not priced per input token
Output$10.00 / 1M$20.00 / 1M$4.40 / 1M— Not priced per output token
Cache Write (5m)$2.00 / 1M$4.00 / 1M$1.40 / 1MNot applicable
Cache Write (1h)$2.00 / 1M$4.00 / 1M$1.40 / 1MNot applicable
Cache Read$2.00 / 1M$4.00 / 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 ModeYesYesYesNo
StreamingYesYesYesNo
Catalogue
ProviderGoogleMetaZ.AIAssemblyAI
Categorychatchatchatvoice
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released———2026-09-22
Description
SummaryGemini 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.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.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.AssemblyAI Universal-3.5 Pro speech-to-text. Billed per second of audio.