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.

Qwen3 ASR 1.7BQwen Remove
Claude Opus 5.5Anthropic Remove
Muse Spark 1.3Meta Remove
S2 ProFish Audio Remove

4 is the maximum. Remove one to add another.

qwen3-asr-1.7b vs claude-opus-5.5 vs muse-spark-1.3 vs s2-pro
Attribute	Qwen3 ASR 1.7Bqwen3-asr-1.7b	Claude Opus 5.5claude-opus-5.5	Muse Spark 1.3muse-spark-1.3	S2 Pros2-pro
Pricing
Input	$0 / 1M	$4.00 / 1M	$1.25 / 1M	$0 / 1M
Output	$0 / 1M	$20.00 / 1M	$4.25 / 1M	$0 / 1M
Cache Write (5m)	Not applicable	$5.00 / 1M	$1.25 / 1M	Not applicable
Cache Write (1h)	Not applicable	$8.00 / 1M	$1.25 / 1M	Not applicable
Cache Read	Not applicable	$0.40 / 1M	$1.25 / 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	Qwen	Anthropic	Meta	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	2026-08-13	—	—	2026-07-29
Description
Summary	Qwen3-ASR 1.7B speech-to-text. Billed per second of audio.	Claude Opus 5.5 is Anthropic's flagship model for advanced reasoning, coding, and long-horizon agentic workflows, succeeding Opus 5. It excels at multi-step changes across large codebases, code review and bug detection, financial and scientific analysis, and understanding dense charts, diagrams, and screenshots, with stronger grounding when reporting figures and citing sources. Compared with Opus 5, it completes comparable tasks with fewer steps and lower token usage while providing clearer, more concise progress reporting. With adaptive thinking and configurable effort levels, Opus 5.5 can balance reasoning depth, latency, and cost, making it well suited for both demanding autonomous workflows and latency-sensitive professional tasks.	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.	Fish Audio S2 Pro text-to-speech. Billed per UTF-8 byte of input text.