Skip to content

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. Perceptron Mk1.5PerceptronRemove
  2. Muse Spark OpenMetaRemove
  3. mai-ds-r1:freeNot in the catalogueRemove
  4. Gemini 3.8 FlashGoogleRemove

4 is the maximum. Remove one to add another.

perceptron-mk1.5 vs muse-spark-open vs mai-ds-r1:free vs gemini-3.8-flash
AttributePerceptron Mk1.5perceptron-mk1.5Muse Spark Openmuse-spark-openmai-ds-r1:freeNot in the catalogueGemini 3.8 Flashgemini-3.8-flash
Pricing
Input$0.15 / 1M$1.25 / 1M—$0.75 / 1M
Output$1.50 / 1M$4.25 / 1M—$3.75 / 1M
Cache Write (5m)$0.15 / 1M$1.25 / 1M—$0.75 / 1M
Cache Write (1h)$0.15 / 1M$1.25 / 1M—$0.75 / 1M
Cache Read$0.15 / 1M$1.25 / 1M—$0.75 / 1M
Web Search$0 / 1M$0 / 1M—$0 / 1M
Context
Max context36.9K1M—1M
Max outputN/AN/A—N/A
Capabilities
VisionNoYes—Yes
Function CallingNoYes—Yes
JSON ModeNoYes—Yes
StreamingYesYes—Yes
Catalogue
ProviderPerceptronMeta—Google
Categorychatchat—chat
Charge typePay As You GoPay As You Go—Pay As You Go
Released2026-09-25———
Description
SummaryPerceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per 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.—Gemini 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.