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.

MAI-Transcribe 2Microsoft Remove
Muse Spark 1.3Meta Remove
DeepSeek V4.1 FlashDeepSeek Remove
S1Fish Audio Remove

4 is the maximum. Remove one to add another.

mai-transcribe-2 vs muse-spark-1.3 vs deepseek-v4.1-flash vs s1
Attribute	MAI-Transcribe 2mai-transcribe-2	Muse Spark 1.3muse-spark-1.3	DeepSeek V4.1 Flashdeepseek-v4.1-flash	S1s1
Pricing
Input	$0 / 1M	$1.25 / 1M	$0.30 / 1M	$0 / 1M
Output	$0 / 1M	$4.25 / 1M	$1.20 / 1M	$0 / 1M
Cache Write (5m)	Not applicable	$1.25 / 1M	$0.30 / 1M	Not applicable
Cache Write (1h)	Not applicable	$1.25 / 1M	$0.30 / 1M	Not applicable
Cache Read	Not applicable	$1.25 / 1M	$0.30 / 1M	Not applicable
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	N/A	1M	1M	N/A
Max output	N/A	N/A	N/A	N/A
Capabilities
Vision	No	Yes	Yes	No
Function Calling	No	Yes	Yes	No
JSON Mode	No	Yes	Yes	No
Streaming	No	Yes	Yes	No
Catalogue
Provider	Microsoft	Meta	DeepSeek	Fish Audio
Category	voice	chat	chat	voice
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	2026-09-03	—	—	2026-07-29
Description
Summary	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.	Fish Audio S1 text-to-speech. Billed per UTF-8 byte of input text.