Larry Jing

Grok Voice + Starlink Applied AI

[SpaceXAI @SpaceXAI]

Announcing Grok 4.5, our first model trained specifically for coding and agents. It was trained with Cursor and offers frontier intelligence at leading speeds and cost efficiency.

https://t.co/i8HpU7w64k

[Larry Jing @jingla]

Give them a listen!

[SpaceXAI @SpaceXAI]

Today, we're adding 21 new flagship voices to Grok via API.

https://t.co/566ZS2bv0L

[Larry Jing @jingla]

Today was my last day at @xai…

…and my first day at @SpaceXAI 🤠

[Larry Jing @jingla]

@runthenumberz Just hit “Add number” on the deployment screen!

[Larry Jing @jingla]

Try making a personal voice assistant for anything you can think of - it’s ridiculously quick and easy

[Umesh Khanna 🇨🇦🇺🇸 @forwarddeploy]

Built an entire voice clone of myself in around 3 mins!

Call my voice agent: [phone]

> downloaded granola notes (1 min)
> gave to grok to sanitize any sensitive info (30 sec)
> voice cloned my voice (1 min)
> setup my voice agent (30 sec)
> got a new phone number (5 seconds)

[Larry Jing @jingla]

Make your own voice agent today - free phone number on us!

[SpaceXAI @SpaceXAI]

Introducing Voice Agent Builder: a no-code platform to create human-like voice agents with Grok Voice.

Available today at $0.05 / min.

https://t.co/kUkF7zqvfR

[SpaceXAI @SpaceXAI]

Introducing Voice Agent Builder: a no-code platform to create human-like voice agents with Grok Voice.

Available today at $0.05 / min.

https://t.co/kUkF7zqvfR

[Andrew Milich @milichab]

Try SpaceXAI Voice models in the Vercel AI Gateway

[Parker Conrad @parker__conrad]

@xai Grok TTS is currently #1 on the @Vapi_AI Humanness Index and significantly more affordable than the competition.

See for yourself https://t.co/zIgW3QRWcR

[Nasdaq @Nasdaq]

.@SpaceX listing day is here. Watch live. $SPCX https://t.co/VTXg0N2TBc

[ServiceNow AI Research @ServiceNowRSRCH]

🚀 Grok Voice Think Fast 1.0 (@xAI) lands on the Pareto frontier on EVA-Bench — no system in the eval beats it on accuracy without sacrificing experience, or vice versa.

📊 Leaderboard: https://t.co/v4QJZwzUsd

@elonmusk #VoiceAgents #ServiceNowResearch #EVABench #GrokVoice #xAI

[Larry Jing @jingla]

This is what the future looks like!

[Larry Jing @jingla]

Hands-free shopping powered by Grok Voice!

[Gopuff @gopuff]

Meet Go. Gopuff's AI shopping genius, co-developed with SpaceXAI. Just say what you need. It's already on its way.

[SpaceX @SpaceX]

Starship flip and landing burn at the end of its twelfth flight test

[Elon Musk @elonmusk]

Congratulations @SpaceX team on an epic first Starship V3 launch & landing!

You scored a goal for humanity.

[Larry Jing @jingla]

Grok Voice is dominating on real-world performance!

[Artificial Analysis @ArtificialAnlys]

Announcing agentic performance benchmarking for Speech to Speech models on Artificial Analysis. We use 𝜏-Voice to measure tool calling and customer interaction voice agent capabilities in realistic customer service scenarios

Even the strongest Speech to Speech (S2S) models today resolve only about half of realistic customer service scenarios end-to-end - a meaningful gap relative to frontier text-based agents on the same tasks. Voice channels introduce significant complexity: challenging accents, background noise, and packet loss, all while requiring fast responses, consistency across long multi-turn conversations, and reliable tool use. Performance also varies considerably by audio condition: in clean audio some models perform notably better, but realistic conditions continue to pose a challenge. Conversation duration also varies meaningfully across models, with implications for both customer experience and operational cost.

About 𝜏-Voice:
Our Agentic Performance benchmark is based on 𝜏-Voice (Ray, Dhandhania, Barres & Narasimhan, 2026), which extends 𝜏²-bench into the voice modality to evaluate S2S models on realistic customer service tasks. It measures multi-turn instruction following, support of a simulated customer through a complete interaction, and tool use against simulated customer service systems. The simulated user combines an LLM-driven decision model with realistic audio synthesis: diverse accents, background noise, and packet loss modelled on real network conditions.

This complements our Big Bench Audio benchmark measuring intelligence and Conversational Dynamics (Full Duplex Bench subset) benchmark measuring conversational naturalness. Scores are the average of three independent pass@1 trials. We evaluate under realistic audio conditions using the 𝜏²-bench base task split across three domains:
➤ Airline (50 scenarios): e.g., changing a flight, rebooking under policy constraints
➤ Retail (114 scenarios): e.g., disputing a charge, processing a return
➤ Telecom (114 scenarios): e.g., resolving a billing issue, troubleshooting a service problem

Task success is determined by deterministic checks against expected actions and final database state, consistent with the 𝜏²-bench evaluator.

Key results:
xAI's Grok Voice Think Fast 1.0 is the clear leader at 52.1%, averaging 5.6 minutes per conversation, the second-longest overall. OpenAI's GPT-Realtime-2 (High) (39.8%, 3.0 min) and GPT-Realtime-1.5 (38.8%, 4.8 min) follow, with Gemini 3.1 Flash Live Preview - High close behind at 37.7% (3.8 min).

Speech to Speech is a fast evolving modality and we expect movement in rankings as we continue to add new models with these capabilities, and model robustness improves.

Congratulations @xAI @elonmusk! See below for further detail ⬇️

[Larry Jing @jingla]

@Starlink did it first!

[Elon Musk @elonmusk]

Try Grok Voice for your customer support

[Elon Musk @elonmusk]

Try Grok Voice for your customer support

[Larry Jing @jingla]

It’s getting scary good!

[SpaceXAI @SpaceXAI]

Two voices. One human. One AI. Can you guess the AI clone? 👇

Voice cloning, rich with natural emotion, is now live on the Grok Voice API.

https://t.co/EjxjXstoiL

[Elon Musk @elonmusk]

Grok Voice is used by Starlink right now