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. mai-ds-r1:freeNot in the catalogueRemove
  2. Muse Spark OpenMetaRemove
  3. Perceptron Mk1.5PerceptronRemove
  4. DeepSeek V4.1 FlashDeepSeekRemove

4 is the maximum. Remove one to add another.

mai-ds-r1:free vs muse-spark-open vs perceptron-mk1.5 vs deepseek-v4.1-flash
Attributemai-ds-r1:freeNot in the catalogueMuse Spark Openmuse-spark-openPerceptron Mk1.5perceptron-mk1.5DeepSeek V4.1 Flashdeepseek-v4.1-flash
Pricing
Input—$1.25 / 1M$0.15 / 1M$0.30 / 1M
Output—$4.25 / 1M$1.50 / 1M$1.20 / 1M
Cache Write (5m)—$1.25 / 1M$0.15 / 1M$0.30 / 1M
Cache Write (1h)—$1.25 / 1M$0.15 / 1M$0.30 / 1M
Cache Read—$1.25 / 1M$0.15 / 1M$0.30 / 1M
Web Search—$0 / 1M$0 / 1M$0 / 1M
Context
Max context—1M36.9K1M
Max output—N/AN/AN/A
Capabilities
Vision—YesNoYes
Function Calling—YesNoYes
JSON Mode—YesNoYes
Streaming—YesYesYes
Catalogue
Provider—MetaPerceptronDeepSeek
Category—chatchatchat
Charge type—Pay As You GoPay As You GoPay As You Go
Released——2026-09-25—
Description
Summary—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.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.DeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion.