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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. Perceptron Mk1.5PerceptronRemove
  2. MAI-Transcribe 2MicrosoftRemove
  3. Muse Spark 1.3MetaRemove
  4. DeepSeek V4.1 FlashDeepSeekRemove

4 is the maximum. Remove one to add another.

perceptron-mk1.5 vs mai-transcribe-2 vs muse-spark-1.3 vs deepseek-v4.1-flash
AttributePerceptron Mk1.5perceptron-mk1.5MAI-Transcribe 2mai-transcribe-2Muse Spark 1.3muse-spark-1.3DeepSeek V4.1 Flashdeepseek-v4.1-flash
Pricing
Input$0.15 / 1M$0 / 1M$1.25 / 1M$0.30 / 1M
Output$1.50 / 1M$0 / 1M$4.25 / 1M$1.20 / 1M
Cache Write (5m)$0.15 / 1MNot applicable$1.25 / 1M$0.30 / 1M
Cache Write (1h)$0.15 / 1MNot applicable$1.25 / 1M$0.30 / 1M
Cache Read$0.15 / 1MNot applicable$1.25 / 1M$0.30 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context36.9KN/A1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoNoYesYes
Function CallingNoNoYesYes
JSON ModeNoNoYesYes
StreamingYesNoYesYes
Catalogue
ProviderPerceptronMicrosoftMetaDeepSeek
Categorychatvoicechatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released2026-09-252026-09-03——
Description
SummaryPerceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.Microsoft MAI-Transcribe-2 speech-to-text. Billed per second of audio.Muse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.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.