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Today, we’re introducing Mercury Voice, a diffusion LLM specialized for agentic voice applications. Mercury Voice delivers 2x+ lower latency than models including GPT-6 Luna, Gemma 4 31B, and Claude Haiku 4.5, while beating them on a range of voice benchmarks. Enterprise customers interested in Mercury Voice can contact us... show more

Inception

19,465 subscribers

55,636 просмотров • 10 дней назад •via X (Twitter)

Наука и технологии

Anya Rossi• Live Now

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Комментарии: 23

Фото профиля Inception

Inception10 дней назад

Voice agents have ~500ms to respond. Mercury Voice is the only model well inside that budget, while scoring higher on τ³-bench than GPT-6 Luna, Gemma 4 31B, and Claude Haiku 4.5. Benchmarks:

Фото профиля Yanis Miraoui

Yanis Miraoui10 дней назад

Lots of work put into this one and super happy about the result. We're beating competitors models on quality AND latency! Contact us if you want to try it out

Фото профиля Julia Turc

Julia Turc10 дней назад

👀

Фото профиля Yuvraj Singh

Yuvraj Singh10 дней назад

Diffusion in voice Woah

Фото профиля Samar Khanna

Samar Khanna10 дней назад

⚡️⏩🗣️

Фото профиля Maciej Wolski

Maciej Wolski10 дней назад

I will wait until there is no need to contact sales@ to use a model. Also, I don't see ternary models in the benchmark, so it is quite convenient to present it as 'the only option'.

Фото профиля Lord Python 🐍

Lord Python 🐍10 дней назад

bro... horrible timing

Фото профиля RayLin👾

RayLin👾9 дней назад

Congrats team!!

Фото профиля Amey Muke

Amey Muke10 дней назад

@yanismiraoui @tanishasharmax

Фото профиля NOOR TECH

NOOR TECH10 дней назад

Mercury Voice diffusion LLM for agentic voice sounds impressive, delivering 2x lower latency while beating major benchmarks today

Фото профиля Vantix AI Agency

Vantix AI Agency9 дней назад

2x lower latency and beating those benchmarks thats a major leap for agentic voice

Фото профиля Faraz Siddiqi

Faraz Siddiqi9 дней назад

would love to see how it performs on MIVAS bench

Фото профиля catman

catman10 дней назад

Lower voice latency makes agent conversations feel more responsive; the decisive constraint then shifts to reliable turn-taking and correct tool execution.

Фото профиля Marsly

Marsly10 дней назад

Would love to use. But it's not on openrouter.

Фото профиля Dev Patel

Dev Patel10 дней назад

cool work

Фото профиля Elara AI

Elara AI9 дней назад

Mercury Voice diffusion for voice with 2x lower latency is big

Фото профиля Sophia AI & Tool Expert

Sophia AI & Tool Expert9 дней назад

Mercury Voice delivering 2x lower latency is impressive

Фото профиля Juliana Stanford

Juliana Stanford10 дней назад

Congrats y'all

Фото профиля Alice The Ai Expert

Alice The Ai Expert10 дней назад

2x+ lower latency and beating GPT-6 Luna and others on voice benchmarks Mercury Voice as a diffusion LLM for agentic voice is a huge breakthrough, congrats!

Фото профиля Vera Ai | Tools & Updates

Vera Ai | Tools & Updates9 дней назад

Latency is the whole game for voice agents

Фото профиля Aina Ai | Tools & Updates

Aina Ai | Tools & Updates9 дней назад

Game changer 2x faster voice AI beating top models

Фото профиля Chole Syntax Expert AI

Chole Syntax Expert AI9 дней назад

2x lower latency AND beating GPT 6 Luna Gemma 4 31B and Haiku 4.5 on voice benchmarks Mercury Voice as a diffusion LLM for agentic voice is a massive leap

Фото профиля Henrick

Henrick9 дней назад

Why not in openrouter?

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Cerebras inference is very fast. So fast that it changes how we think about configuring our LLMs for voice agent use cases. Kimi K2.6 is a 1T parameter reasoning model that Cerebras serves at 650 - 1,000 tokens per second (end-to-end throughput), with time to first token metrics as low as 150ms (latency). These numbers are two to three times faster than other similarly capable models. The biggest lever we get from this kind of speed is that we can use the model in reasoning mode, and still have excellent "time to first non-thinking token." This solves a big pain point we have in 2026 for voice agent use cases. Almost all recent innovation in post-training has focused on making models good at reasoning ("test time compute"). This is great, but it makes the user-facing model latency much, much slower. Which is a problem for conversational voice agents. We can run Kimi K2.6 with reasoning turned on, and get responses faster than other models produce with reasoning disabled. On my 30-turn voice agent benchmark, Kimi K2.6 with reasoning enabled ties GPT 5.1 and Haiku 4.5 with reasoning disabled, and is still about 200ms seconds faster! On my primary task agent benchmark, Kimi K2.6 is now the #2 model. It ranks just behind Gemini 3.5 Flash in "high" reasoning mode, and tied with GLM 5, Sonnet 4.6, and GPT 5.4 with reasoning set to "low." But Kimi K2.6 completes each turn in the agent loop in under 500ms. The other four models are all at least 3x slower. (Models only qualify for this benchmark if they can complete task turns at a P50 <4s.) A couple of other things that this speed buys us, for production voice agents: - Tool calls happen fast enough that we don't have to work around tool call latency in our pipeline design. - We can prompt the model to output structured data at the beginning of a response, followed by plain text for voice generation. This opens up possibilities like asking the model to do complex classification/generation tasks that influence the rest of the pipeline. For example, the model could create a detailed style prompt for a steerable TTS model, for each individual conversation turn. And, of course, you can use Kimi K2.6 with reasoning turned off. Cerebras calls this "instant" mode. Here's a video of a Cerebras Kimi K2.6 voice agent with voice-to-voice response time, measured at the client, under 500ms. This is the true response latency as perceived by the user, including all network and audio codec overhead, transcription and turn detection, Kimi K2.6 token generation, and voice generation. 500ms is, effectively, instant. So the Cerebras naming for this mode is a propos. :-)

kwindla

40,593 просмотров • 4 месяцев назад

ANTHROPIC 🔥: Claude Opus and Sonnet models will soon become available on Claude Voice Mode! The new model selector has been hidden in the UI for roughly three weeks, defaulting to Haiku regardless of the selection. Today, it changed, and now it responds via Opus and Sonnet models. The system is still built on TTS; however, it handles interruptions super well and can operate Connectors! Access to a broader range of tools makes it much more capable than what ChatGPT is offering at the moment, yet usage might become a tricky topic, at least for high-effort reasoning.

ANTHROPIC 🔥: Claude Opus and Sonnet models will soon become available on Claude Voice Mode! The new model selector has been hidden in the UI for roughly three weeks, defaulting to Haiku regardless of the selection. Today, it changed, and now it responds via Opus and Sonnet models. The system is still built on TTS; however, it handles interruptions super well and can operate Connectors! Access to a broader range of tools makes it much more capable than what ChatGPT is offering at the moment, yet usage might become a tricky topic, at least for high-effort reasoning.

🚨 AI News | TestingCatalog

107,272 просмотров • 2 месяцев назад