Meta’s Superintelligence Labs launched Muse Voice Transcribe, a real-time speech recognition model that performs ahead of comparable streaming competitors on reported benchmarks. Its AA-WER Streaming word error rate is 3.1%, versus Cartesia Ink-2 at 3.4%, ElevenLabs’ Scribe v2 Realtime at 3.6%, GPT Live Transcribe at 3.9%, and Gemini 3.5 Transcribe Live at 4.0%. The model becomes available via the Meta Model API, Meta AI for Mac, and Muse Code, while Meta keeps it closed-weight rather than releasing open weights.
Phonely launched Alma, a voice-focused AI model trained on more than 10 million real phone conversations. Alma delivers sub-185-millisecond response time to the first token and is priced at 55 cents per blended million tokens, described as 84% cheaper than GPT-4.1. This aims to reduce unnatural pauses and ongoing prompt-tuning needs by improving how voice agents handle conversational flow and self-improve from live call traffic.
Phonely launched Alma, a voice AI model trained on over 10 million real phone conversations. Alma delivers sub-185-millisecond response time to the first token, and is priced at 55 cents per million blended tokens versus GPT-4.1 at $3.50. This shifts voice-agent development toward faster, more phone-conversation-aligned responses with cheaper inference and self-improvement from live call traffic.
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