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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. Gemini 3.8 FlashGoogleRemove
  2. Muse Spark OpenMetaRemove
  3. Gemini 3.5 TranscribeGoogleRemove
gemini-3.8-flash vs muse-spark-open vs gemini-3.5-transcribe
AttributeGemini 3.8 Flashgemini-3.8-flashMuse Spark Openmuse-spark-openGemini 3.5 Transcribegemini-3.5-transcribe
Pricing
Input$0.75 / 1M$1.25 / 1M— Not priced per input token
Output$3.75 / 1M$4.25 / 1M— Not priced per output token
Cache Write (5m)$0.75 / 1M$1.25 / 1MNot applicable
Cache Write (1h)$0.75 / 1M$1.25 / 1MNot applicable
Cache Read$0.75 / 1M$1.25 / 1MNot applicable
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M98.3K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesNo
StreamingYesYesNo
Catalogue
ProviderGoogleMetaGoogle
Categorychatchatvoice
Charge typePay As You GoPay As You GoPay As You Go
Released——2026-09-25
Description
SummaryGemini 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality.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.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.