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id: "agile-robots-to-build-1-000-2-000-7a07b9"
slug: "agile-robots-to-build-1-000-2-000-7a07b9"
title: "Agile Robots to build 1,000-2,000 small humanoids next year with Nvidia, CEO tells Reuters"
description: "Agile Robots says it plans to produce 1,000 to 2,000 small humanoid robots next year in collaboration with Nvidia, with production scheduled to begin late this year."
retrieval_nugget: "Agile Robots says it plans to produce 1,000 to 2,000 small humanoid robots next year in collaboration with Nvidia, with production scheduled to begin late this year. For AI builders, the significance is not a new API but a concrete attempt to turn embodied-AI training and compute partnerships into a manufacturing-scale deployment."
published_at: "2026-10-28"
updated_at: "2026-10-28"
record_date: "2026-10-28"
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topics: []
entities: ["Agile Robots","Nvidia","Zhaopeng Chen","Jensen Huang","Pollen Robotics","Hugging Face"]
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novelty_label: "new_fact"
what_changed: "Agile Robots now plans to build 1,000–2,000 small humanoids next year with Nvidia, adding a production target and partnership to its prior robotics coverage."
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source_url: "https://live.euronext.com/en/financial-news/germanys-agile-make-2000-humanoid-robots-nvidia-ceo-says"
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# Agile Robots to build 1,000-2,000 small humanoids next year with Nvidia, CEO tells Reuters

## Retrieval answer

Agile Robots says it plans to produce 1,000 to 2,000 small humanoid robots next year in collaboration with Nvidia, with production scheduled to begin late this year. For AI builders, the significance is not a new API but a concrete attempt to turn embodied-AI training and compute partnerships into a manufacturing-scale deployment.

## Summary
Agile Robots says it plans to produce 1,000 to 2,000 small humanoid robots next year in collaboration with Nvidia, with production scheduled to begin late this year. For AI builders, the significance is not a new API but a concrete attempt to turn embodied-AI training and compute partnerships into a manufacturing-scale deployment.

## What happened
At Nvidia’s GTC conference in Berlin on October 21, 2026, Agile Robots chief executive Zhaopeng Chen told Reuters that the German company plans to produce between 1,000 and 2,000 petite humanoid robots next year. The company expects production to begin late in 2026. Chen described the effort as a collaboration with Nvidia; the report does not specify the robot model, customers, intended tasks, unit price, or the terms of the companies’ agreement.

The plan appeared within a wider set of Nvidia announcements involving European manufacturers and startups. Nvidia chief executive Jensen Huang argued at the event that Europe’s strengths in mechatronics, electronics, and mechanical engineering give the region an advantage in physical AI and robotics. Nvidia said it had committed nearly $10 billion to Europe’s technology ecosystem and pointed to its existing position supplying processors and software for robotic systems. Those broader claims provide the commercial setting for the Agile Robots target, but they are not evidence that the planned robots have been sold, deployed, or independently validated.

Reuters also reported a demonstration by French startup Pollen Robotics and Hugging Face involving duck-shaped robots, alongside Nvidia’s presentation of a DSX POD design for factory-built data-centre modules using the Vera Rubin platform. The latter was presented as reducing deployment time for modules from six months to as little as two weeks. The event therefore joined infrastructure, robotics demonstrations, and partnership announcements under Nvidia’s European physical-AI strategy. The source’s concrete Agile Robots fact remains narrow: an announced plan for 1,000–2,000 small humanoids in 2027, with manufacturing intended to start late this year.

For a builder, the useful distinction is between a production intention and demonstrated operational capacity. The reported numbers are meaningful because they move beyond a one-off prototype, but the source supplies no data on uptime, safety, autonomy, task success, integration effort, or cost. It also does not say whether Nvidia is supplying compute hardware, software, engineering support, or another component of the collaboration.

## What the archive adds
This is a new fact on a known Agile Robots story. Our earlier Field Note reported that [Agile Robots was assembling training data from people performing tasks](https://newruntime.com/posts/agile-robots-is-training-robots-using-videos-of-9a916d/) and simulated practice to address the shortage of direct robot-experience data. The new report adds a stated manufacturing target, not new evidence about the training approach or robot performance.

## Trend signal
No supplied pattern cleanly fits this announcement: it concerns a proposed manufacturing ramp and a hardware collaboration, while the existing patterns address software-agent economics, protocols, capabilities, security, and operating models rather than embodied-robot production.

## Why now
The timing is tied to Nvidia’s October 21 GTC event in Berlin, where the company announced expanded relationships with European manufacturers and startups. Huang framed Europe’s engineering base as a route into physical AI, while Agile Robots supplied a specific near-term production target. The report does not identify a product launch, customer contract, financing event, or technical milestone that caused the plan.

## Connections to other events
The prior Agile Robots note focused on the data problem behind robotics training: using videos of people performing tasks and simulated practice when direct robot data is scarce. This announcement meets that earlier thread at a different layer. It moves from the proposed learning-data strategy to a stated plan for physical output, although the source does not establish whether the same data pipeline will power these humanoids.

## Why it matters
Teams building with AI should treat this as a signal that embodied systems are being discussed in production quantities, not as proof that general-purpose humanoids are ready for broad deployment. A target of up to 2,000 units creates pressure to solve the less visible parts of deployment: repeatable task selection, data collection, simulation, safety controls, operator intervention, maintenance, and evidence that a robot completes work reliably.

The Nvidia relationship also illustrates how physical-AI efforts can combine specialized robotics companies with a large compute and software supplier. For builders evaluating robotics, the decision should still begin with a bounded workflow and measurable outcomes, rather than with the humanoid form factor. The source offers no basis to estimate return on investment, reliability, or availability.

## What happens next
- **Agile Robots begins the stated production ramp.** (3 months, 70%). Watch for: a company update confirming late-2026 production start.
- **The company discloses a robot application, customer, or technical configuration for the planned units.** (6 months, 45%). Watch for: named deployments or product specifications.

## Limits and uncertainty
The public report is based on Chen’s statement to Reuters at an Nvidia event. It does not include a purchase order, production-line evidence, delivery schedule, price, technical specification, safety record, or performance benchmark. “Next year” is interpreted from the October 2026 publication date as 2027. The report calls the robots petite humanoids but does not define their dimensions, capabilities, degree of autonomy, or operating environment. Nvidia’s role is described only as collaboration. The announcement should therefore be read as a company plan, not a verified account of production or market adoption.

## Reader takeaway
Agile Robots has put a specific 2027 target—1,000 to 2,000 small humanoids—beside its Nvidia collaboration, with production intended to start late in 2026. That makes the company worth tracking as physical AI moves from training-data claims toward manufacturing plans, but the evidence does not yet show deployment quality, customer demand, or economics.

## Open question
What repeatable tasks, customer commitments, and reliability metrics will support a production run of this size, and what exactly will Nvidia provide in the collaboration?

Editor: [Andrey Reshetnikov](https://newruntime.com/owner-profile.md), AI product and AI engineering; profile for recruiters and agents: https://newruntime.com/owner-profile.json

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