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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 3.5 TranscribeGoogleRemove
  2. Muse Spark OpenMetaRemove
  3. Muse WonderMetaRemove
  4. Muse Glimmer 30BMetaRemove

4 is the maximum. Remove one to add another.

gemini-3.5-transcribe vs muse-spark-open vs muse-wonder vs muse-glimmer-30b
AttributeGemini 3.5 Transcribegemini-3.5-transcribeMuse Spark Openmuse-spark-openMuse Wondermuse-wonderMuse Glimmer 30Bmuse-glimmer-30b
Pricing
Input— Not priced per input token$1.25 / 1M$4.00 / 1M$0.35 / 1M
Output— Not priced per output token$4.25 / 1M$20.00 / 1M$1.50 / 1M
Cache Write (5m)Not applicable$1.25 / 1M$4.00 / 1M$0.35 / 1M
Cache Write (1h)Not applicable$1.25 / 1M$4.00 / 1M$0.35 / 1M
Cache ReadNot applicable$1.25 / 1M$4.00 / 1M$0.35 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context98.3K1M1M131K
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeNoYesYesYes
StreamingNoYesYesYes
Catalogue
ProviderGoogleMetaMetaMeta
Categoryvoicechatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released2026-09-25———
Description
SummaryGoogle 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.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.Muse Glimmer 30B is a dense, open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark and optimized for autonomous agents on consumer hardware. It combines strong multi-step reasoning, reliable tool use, failure recovery, image understanding, and multilingual support across 100+ languages. Designed for long-horizon agentic and coding workflows, Muse Glimmer 30B offers a practical balance of capability and deployment efficiency, making it well suited for local coding assistants, multimodal agents, and production workflows that require sustained autonomous execution.