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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 Spark OpenMetaRemove
  2. Gemini 3.5 TranscribeGoogleRemove
  3. Gemini 3.7 FlashGoogleRemove
muse-spark-open vs gemini-3.5-transcribe vs gemini-3.7-flash
AttributeMuse Spark Openmuse-spark-openGemini 3.5 Transcribegemini-3.5-transcribeGemini 3.7 Flashgemini-3.7-flash
Pricing
Input$1.25 / 1M— Not priced per input token$0.375 / 1M
Output$4.25 / 1M— Not priced per output token$1.88 / 1M
Cache Write (5m)$1.25 / 1MNot applicable$0.375 / 1M
Cache Write (1h)$1.25 / 1MNot applicable$0.375 / 1M
Cache Read$1.25 / 1MNot applicable$0.375 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M98.3K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderMetaGoogleGoogle
Categorychatvoicechat
Charge typePay As You GoPay As You GoPay As You Go
Released—2026-09-25—
Description
SummaryMuse 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.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.Gemini 3.7 Flash is Google's fast multimodal model designed for agentic workflows, coding, and complex multi-step reasoning. It combines responsive inference with reliable problem-solving capabilities, making it well suited for interactive and production-scale applications. Optimized for speed and dependable multi-step execution, Gemini 3.7 Flash is a strong choice for coding assistants, autonomous agents, and high-throughput workflows that require both low latency and capable reasoning.