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.

Muse Spark 1.3Meta Remove
GPT-6 Sol ProOpenAI Remove
Perceptron Mk1.5Perceptron Remove
Aura-2Deepgram Remove

4 is the maximum. Remove one to add another.

muse-spark-1.3 vs gpt-6-sol-pro vs perceptron-mk1.5 vs aura-2
Attribute	Muse Spark 1.3muse-spark-1.3	GPT-6 Sol Progpt-6-sol-pro	Perceptron Mk1.5perceptron-mk1.5	Aura-2aura-2
Pricing
Input	$1.25 / 1M	$2.00 / 1M	$0.15 / 1M	$0 / 1M
Output	$4.25 / 1M	$10.00 / 1M	$1.50 / 1M	$0 / 1M
Cache Write (5m)	$1.25 / 1M	$2.00 / 1M	$0.15 / 1M	Not applicable
Cache Write (1h)	$1.25 / 1M	$2.00 / 1M	$0.15 / 1M	Not applicable
Cache Read	$1.25 / 1M	$2.00 / 1M	$0.15 / 1M	Not applicable
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	1M	1.1M	36.9K	N/A
Max output	N/A	N/A	N/A	N/A
Capabilities
Vision	Yes	Yes	No	No
Function Calling	Yes	Yes	No	No
JSON Mode	Yes	Yes	No	No
Streaming	Yes	Yes	Yes	No
Catalogue
Provider	Meta	OpenAI	Perceptron	Deepgram
Category	chat	chat	chat	voice
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	—	—	2026-09-25	2026-07-16
Description
Summary	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.	GPT-6 Sol Pro uses the same underlying model as GPT-6 Sol, but runs with reasoning.mode set to pro for higher-quality responses on complex and demanding tasks. Optimized for deeper reasoning, greater accuracy, and more reliable multi-step execution, it is particularly well suited for agentic coding, long-horizon software engineering, professional analysis, and complex automated workflows where solution quality takes priority over latency and cost.	Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.	Deepgram Aura-2 text-to-speech for real-time voice applications. Billed per input character.