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.

MAI-Transcribe 2Microsoft Remove
Aura-2Deepgram Remove
GPT-6 LunaOpenAI Remove
Qwen3 ASR 1.7BQwen Remove

4 is the maximum. Remove one to add another.

mai-transcribe-2 vs aura-2 vs gpt-6-luna vs qwen3-asr-1.7b
Attribute	MAI-Transcribe 2mai-transcribe-2	Aura-2aura-2	GPT-6 Lunagpt-6-luna	Qwen3 ASR 1.7Bqwen3-asr-1.7b
Pricing
Input	$0 / 1M	$0 / 1M	$0.10 / 1M	$0 / 1M
Output	$0 / 1M	$0 / 1M	$0.50 / 1M	$0 / 1M
Cache Write (5m)	Not applicable	Not applicable	$0.10 / 1M	Not applicable
Cache Write (1h)	Not applicable	Not applicable	$0.10 / 1M	Not applicable
Cache Read	Not applicable	Not applicable	$0.10 / 1M	Not applicable
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	N/A	N/A	1.1M	N/A
Max output	N/A	N/A	N/A	N/A
Capabilities
Vision	No	No	Yes	No
Function Calling	No	No	Yes	No
JSON Mode	No	No	Yes	No
Streaming	No	No	Yes	No
Catalogue
Provider	Microsoft	Deepgram	OpenAI	Qwen
Category	voice	voice	chat	voice
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	2026-09-03	2026-07-16	—	2026-08-13
Description
Summary	Microsoft MAI-Transcribe-2 speech-to-text. Billed per second of audio.	Deepgram Aura-2 text-to-speech for real-time voice applications. Billed per input character.	GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, optimized for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic tasks. It combines low-cost, responsive inference with the GPT-6 family’s improvements in factual reliability and clear, concise communication. At higher reasoning effort, GPT-6 Luna can also handle complex software engineering and computer-use workflows that previously required a Sol-tier model, making it a versatile choice for scalable production applications that need to balance speed, cost, and capability.	Qwen3-ASR 1.7B speech-to-text. Billed per second of audio.