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.

Claude Sonnet 5.5Anthropic Remove
Gemini 3.5 TranscribeGoogle Remove
Nova-3Deepgram Remove
Muse Spark 1.3Meta Remove

4 is the maximum. Remove one to add another.

claude-sonnet-5.5 vs gemini-3.5-transcribe vs nova-3 vs muse-spark-1.3
Attribute	Claude Sonnet 5.5claude-sonnet-5.5	Gemini 3.5 Transcribegemini-3.5-transcribe	Nova-3nova-3	Muse Spark 1.3muse-spark-1.3
Pricing
Input	$2.00 / 1M	$0 / 1M	$0 / 1M	$1.25 / 1M
Output	$10.00 / 1M	$0 / 1M	$0 / 1M	$4.25 / 1M
Cache Write (5m)	$2.50 / 1M	Not applicable	Not applicable	$1.25 / 1M
Cache Write (1h)	$4.00 / 1M	Not applicable	Not applicable	$1.25 / 1M
Cache Read	$0.20 / 1M	Not applicable	Not applicable	$1.25 / 1M
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	1M	98.3K	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	No	No	Yes
Streaming	Yes	No	No	Yes
Catalogue
Provider	Anthropic	Google	Deepgram	Meta
Category	chat	voice	voice	chat
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	—	2026-09-25	2026-07-15	—
Description
Summary	Claude Sonnet 5.5 is Anthropic's Sonnet-class model for well-scoped everyday work, serving as a direct upgrade to Sonnet 5. It excels at feature development, bug fixing, and creating polished documents, presentations, and spreadsheets, while offering clearer writing and communication than its predecessor.	Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.	Deepgram Nova-3 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.