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 OpenMeta Remove
Gemini 4 CarbonGoogle Remove
Aura-2Deepgram Remove
Gemini 4 HydrogenGoogle Remove

4 is the maximum. Remove one to add another.

muse-spark-open vs gemini-4-carbon vs aura-2 vs gemini-4-hydrogen
Attribute	Muse Spark Openmuse-spark-open	Gemini 4 Carbongemini-4-carbon	Aura-2aura-2	Gemini 4 Hydrogengemini-4-hydrogen
Pricing
Input	$1.25 / 1M	$2.00 / 1M	— Not priced per input token	$1.50 / 1M
Output	$4.25 / 1M	$10.00 / 1M	— Not priced per output token	$7.50 / 1M
Cache Write (5m)	$1.25 / 1M	$2.00 / 1M	Not applicable	$1.50 / 1M
Cache Write (1h)	$1.25 / 1M	$2.00 / 1M	Not applicable	$1.50 / 1M
Cache Read	$1.25 / 1M	$2.00 / 1M	Not applicable	$1.50 / 1M
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	1M	1M	N/A	1M
Max output	N/A	N/A	N/A	N/A
Capabilities
Vision	Yes	Yes	No	Yes
Function Calling	Yes	Yes	No	Yes
JSON Mode	Yes	Yes	No	Yes
Streaming	Yes	Yes	No	Yes
Catalogue
Provider	Meta	Google	Deepgram	Google
Category	chat	chat	voice	chat
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	—	—	2026-07-16	—
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.	Gemini 4 Carbon is Google's frontier multimodal reasoning model, designed for advanced coding, agentic workflows, and complex multi-step problem solving. It supports text, image, audio, video, and file inputs, enabling integrated reasoning and analysis across diverse modalities. Optimized for long-horizon execution and demanding professional workloads, Gemini 4 Carbon supports up to 1M output tokens through continuation and configurable reasoning effort levels (low, medium, high) to balance reasoning depth, latency, and cost. It is well suited for autonomous agents, software engineering, multimodal analysis, and large-scale workflow automation.	Deepgram Aura-2 text-to-speech for real-time voice applications. Billed per input character.	Gemini 4 Hydrogen is Google's high-efficiency multimodal model in the Gemini 4 family, optimized for high-throughput agentic workflows, coding, and multi-model routing. It delivers strong performance at lower cost and latency than Gemini 4 Carbon, supporting text, image, audio, video, and file inputs for versatile multimodal applications. Designed for scalable production workloads and long-horizon execution, Gemini 4 Hydrogen supports up to 1M output tokens through continuation and configurable reasoning effort levels (low, medium, high, and xhigh) to balance reasoning depth, speed, and cost. It is well suited for coding assistants, autonomous agents, complex workflow automation, and large-scale AI systems.