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.

Gemini 3.5 TranscribeGoogle Remove
Claude Sonnet 5.5Anthropic Remove
S2 ProFish Audio Remove
Muse Spark 1.3Meta Remove

4 is the maximum. Remove one to add another.

gemini-3.5-transcribe vs claude-sonnet-5.5 vs s2-pro vs muse-spark-1.3
Attribute	Gemini 3.5 Transcribegemini-3.5-transcribe	Claude Sonnet 5.5claude-sonnet-5.5	S2 Pros2-pro	Muse Spark 1.3muse-spark-1.3
Pricing
Input	$0 / 1M	$2.00 / 1M	$0 / 1M	$1.25 / 1M
Output	$0 / 1M	$10.00 / 1M	$0 / 1M	$4.25 / 1M
Cache Write (5m)	Not applicable	$2.50 / 1M	Not applicable	$1.25 / 1M
Cache Write (1h)	Not applicable	$4.00 / 1M	Not applicable	$1.25 / 1M
Cache Read	Not applicable	$0.20 / 1M	Not applicable	$1.25 / 1M
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	98.3K	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	No	Yes	No	Yes
Streaming	No	Yes	No	Yes
Catalogue
Provider	Google	Anthropic	Fish Audio	Meta
Category	voice	chat	voice	chat
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	2026-09-25	—	2026-07-29	—
Description
Summary	Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.	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.	Fish Audio S2 Pro text-to-speech. Billed per UTF-8 byte of input text.	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.