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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 3.5 TranscribeGoogleRemove
  3. Muse Spark OpenMetaRemove
  4. GLM 5Z.AIRemove

4 is the maximum. Remove one to add another.

muse-wonder vs gemini-3.5-transcribe vs muse-spark-open vs glm-5
AttributeMuse Wondermuse-wonderGemini 3.5 Transcribegemini-3.5-transcribeMuse Spark Openmuse-spark-openGLM 5glm-5
Pricing
Input$4.00 / 1M— Not priced per input token$1.25 / 1M$0.60 / 1M
Output$20.00 / 1M— Not priced per output token$4.25 / 1M$2.20 / 1M
Cache Write (5m)$4.00 / 1MNot applicable$1.25 / 1M$0.60 / 1M
Cache Write (1h)$4.00 / 1MNot applicable$1.25 / 1M$0.60 / 1M
Cache Read$4.00 / 1MNot applicable$1.25 / 1M$0.60 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M98.3K1M202.8K
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesNoYesYes
StreamingYesNoYesYes
Catalogue
ProviderMetaGoogleMetaZ.AI
Categorychatvoicechatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released—2026-09-25——
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.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.Muse Spark Open is an open-weight, coding-optimized model designed for agentic software engineering workflows. It delivers strong first-attempt accuracy, reliable tool calling, and deep codebase understanding, enabling effective development across real-world repositories. Optimized for autonomous coding agents, complex code navigation, and tool-driven development, Muse Spark Open is well suited for software engineering automation, debugging, code generation, and multi-step coding workflows where accuracy and reliable execution are essential.GLM-5 is Z.AI's flagship open-source foundation model, engineered for complex systems design and long-horizon agent workflows. Built with expert developers in mind, it delivers production-grade performance on large-scale programming tasks, rivaling leading closed-source models. With strong agentic planning, deep backend reasoning, and iterative self-correction capabilities, GLM-5 extends beyond traditional code generation to support full-system construction and autonomous execution, making it well suited for advanced engineering and agent-driven development environments.