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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. Muse WonderMetaRemove
  2. Gemini 4 ArgonGoogleRemove
  3. Veo 3 FastGoogleRemove
  4. Claude Fable 5.2AnthropicRemove

4 is the maximum. Remove one to add another.

muse-wonder vs gemini-4-argon vs veo3-fast vs claude-fable-5.2
AttributeMuse Wondermuse-wonderGemini 4 Argongemini-4-argonVeo 3 Fastveo3-fastClaude Fable 5.2claude-fable-5.2
Pricing
Input$4.00 / 1M$2.00 / 1M—$8.00 / 1M
Output$20.00 / 1M$10.00 / 1M—$40.00 / 1M
Cache Write (5m)$4.00 / 1M$2.00 / 1MNot applicable$10.00 / 1M
Cache Write (1h)$4.00 / 1M$2.00 / 1MNot applicable$16.00 / 1M
Cache Read$4.00 / 1M$2.00 / 1MNot applicable$0.20 / 1M
Web Search$0 / 1M$0 / 1M—$0 / 1M
Request——$1.26 / request—
Billing——Pay Per Request—
Context
Max context1M1MN/A1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesNoYes
Function CallingYesYesNoYes
JSON ModeYesYesNoYes
StreamingYesYesNoYes
Catalogue
ProviderMetaGoogleGoogleAnthropic
Categorychatchatvideochat
Charge typePay As You GoPay As You GoPay Per RequestPay As You Go
Released————
Description
SummaryMuse 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.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.—Claude Fable 5.2 is Anthropic's most capable model for advanced technical work and open-ended problem solving, delivering significant improvements in coding, reasoning, and vision over Fable 5.1. It excels at exceptionally complex tasks, including large-scale software migrations, electronic system design, and advanced scientific and mathematical research. With up to 30% faster output generation, clearer communication, and always-on adaptive extended thinking, Fable 5.2 supports configurable reasoning effort from low to max (default high), with thinking preserved across turns. Designed for frontier engineering, scientific discovery, and ambitious long-horizon agentic workflows, it complements Opus 5.5 as a specialized option for the most demanding technical challenges.