G.F MUSK

[Elon Musk @elonmusk]

🎯

[Elon Musk @elonmusk]

The most important thing about Grok Build and the 4.5 release is that it is genuinely so useful for real-world work

[Andrew Milich @milichab]

Built with two prompts and /goal!

[Elon Musk @elonmusk]

Anyone can visit the Starship factory and launch site in Texas, as it is right next to on the public highway. It is incredibly inspiring to see!

[Elon Musk @elonmusk]

Background on the Starship story

[Tesla Megapack @Tesla_Megapack]

10 GWh of our industrial energy storage products are now operating across Australia!

That's equivalent to 160,000 Model Ys. And we're just getting started

[Tesla Manufacturing @gigafactories]

End of an era: Decommissioning the original Model S & X assembly line in just 46 days

[Elon Musk @elonmusk]

Try Grok 4.5 in Perplexity

[Elon Musk @elonmusk]

Grok is closing the loop on real-world use cases

[Elon Musk @elonmusk]

True

[Elon Musk @elonmusk]

Grok Build

[Elon Musk @elonmusk]

Try @grok

[Elon Musk @elonmusk]

Grok 4.5 has the best real-world ROI

[Elon Musk @elonmusk]

😂

[ben hylak @benhylak]

i tried tesla full self driving over the weekend.

it’s magical. can’t believe it got that good without it being a bigger deal.

[Chief Nerd @TheChiefNerd]

GAVIN BAKER: “Tesla and Elon have done more to decarbonize the world than all environmental activists combined.”

[Artificial Analysis @ArtificialAnlys]

SpaceXAI's Grok 4.5 takes the #1 spot on AutomationBench-AA with a score of 51%, ahead of Claude Fable 5 (49%) and Claude Opus 4.8 (48%) at roughly a quarter of their cost per task - the first model to complete more than half of workflow objectives without breaking any business rules

AutomationBench-AA, our independent leaderboard for @zapier’s AutomationBench, tests whether AI agents can automate real SaaS workflows while adhering to business rules. The test set is private to prevent contamination.

Models complete 657 tasks across 40 simulated app environments including Gmail, Google Sheets, Slack, Salesforce, and HubSpot, and the headline score is the share of objectives completed without violating any guardrails.

Key takeaways:

➤ Grok 4.5 completes more objectives than any other model: It completes 79.9% of task objectives and strictly passes 21.9% of tasks. This is the highest we’ve measured on both outcomes, exceeding Claude Fable 5’s 73.3% objective completion and Claude Opus 4.8’s 19.3% of fully-completed tasks

➤ Grok 4.5 pushes out the Pareto frontier of score vs. cost per task: At $0.34 per task, it is both cheaper and higher-scoring than every other leading model - Claude Fable 5 ($1.35 per task), Claude Opus 4.8 ($1.46), GPT-5.5 (xhigh, $1.28), and Gemini 3.5 Flash (high, $0.49)

➤ It is extremely token-efficient: Grok 4.5 uses ~8k output tokens per task, the fewest of any leading model - less than a quarter of Claude Opus 4.8 (32k) and a third of Gemini 3.5 Flash (24k). Its total token usage of 0.44M per task is among the lowest on the leaderboard. Low cost is driven by this efficiency as well as low token pricing

➤ Grok 4.5 uses fewer turns with many parallel tool use: Grok 4.5 resolves tasks in ~16 turns, fewer than GPT-5.5 (xhigh, 25) and less than half of Gemini 3.5 Flash (high, 35), while making the most tool calls per task of any leading model (52.5). It batches 3.3 tool calls per turn, compared to ~2.5 for Claude Opus 4.8 and ~2.0 for GPT-5.5 (xhigh)

➤ Guardrails still get broken: Grok 4.5 triggers 0.63 violations per task, above Claude Opus 4.8 (0.55) and Gemini 3.5 Flash (0.46). At 13.0 objectives completed per violation, it trails Gemini 3.5 Flash (15.0) and Claude Opus 4.8 (13.5)

➤ Its strongest lead is in the hardest domain: Grok 4.5 completes 71% of Finance objectives, the domain with the lowest average score, ahead of Claude Fable 5 (64%) and Claude Opus 4.8 (62%)

Congratulations to @SpaceXAI and @elonmusk on topping the leaderboard!

[Elon Musk @elonmusk]

Grok Imagine

[SimWorld @simworld_ai]

Built from scratch by Grok 4.5 + Grok Build in UE5.8: a cyberpunk L-corner street with neon facades, rain, signs, and crowds walking through the scene.

End-to-end, the run took 10.75M tokens, 36.5 minutes, and only ~$12.4 at API pricing.

What impressed me most is not just the final render, but the process: the coding agent built it in many small steps, saved 30+ map checkpoints, verified the scene, and iteratively fixed issues autonomously.

Congrats to the @SpaceXAI team for building such an impressive coding model and harness. This feels like a real step toward agentic 3D world creation. @elonmusk @milichab @skcd42 @yunta_tsai

#UnrealEngine