Holo3：突破桌面计算使用基准
Hugging Face发布Holo3，面向自治企业的生产级模型。Holo3-122B-A10B在OSWorld-Verified桌面使用基准上得分78.85%，以10B活跃参数（122B总参数）实现行业领先且更低成本的运行。模型通过“agentic learning”训练闭环强化感知与决策，能在合成企业环境中执行真实工作流，奠定自主代理在各类数字场景中运行的基础。所有模型可通过Inference API使用，Holo3-35B-A3B权重以Apache-2许可在Hugging Face开放并提供免费推理额度。
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Holo3: Breaking the Computer Use Frontier
Team
Article
Published
April 1, 2026
Upvote
–
Ramzi De Coster
ramzidecoster
Follow
Hcompany
Pierre-Louis Cedoz
plcedoz38
Follow
Hcompany
We are proud to unveil
Holo3
, the latest evolution of our vision for the Autonomous Enterprise. With a score of
78.85% on the OSWorld-Verified benchmark
, Holo3-122B-A10B establishes a new state of the art for the industry on the leading desktop computer use benchmark.
Holo3 is more than a benchmark leader; it is engineered for production. Built using our agentic flywheel, it has been trained to execute real-world workflows within synthetic enterprise environments. This not only ensures that Holo3 excels in today’s business scenarios, but establishes the foundation for a future where our agents can autonomously navigate virtually any digital landscape.
Best of all, Holo3 achieves this with only 10B active parameters (122B total), so at a fraction of the cost of large-scale proprietary models, such as GPT 5.4 or Opus 4.6. All models are available through our
Inference API
. Holo3-35B-A3B weights are openly accessible on
Hugging Face
under the Apache2 license and freely accessible through our inference API under a free tier.
The Agentic Learning Flywheel
What sets Holo3 apart is its specialized training pipeline—a continuous feedback loop designed to sharpen two core agentic pillars:
perception
and
decision-making
.
Our training flywheel is about teaching our model from annotated examples how to execute specific tasks, all while developing generalist skills across a virtually infinite variety of user interfaces. Here is how we build world-class computer use models:
Synthetic Navigation Data:
using human and generated instructions, we generate scenario-specific navigation examples.
Out-of-Domain Augmentation:
we programmatically extend the scenarios and augment the data to ensure Holo3 can handle the unexpected.
Curated Reinforcement Learning:
every data sample is careful
Holo3: Breaking the Computer Use Frontier
Team
Article
Published
April 1, 2026
Upvote
–
Ramzi De Coster
ramzidecoster
Follow
Hcompany
Pierre-Louis Cedoz
plcedoz38
Follow
Hcompany
We are proud to unveil
Holo3
, the latest evolution of our vision for the Autonomous Enterprise. With a score of
78.85% on the OSWorld-Verified benchmark
, Holo3-122B-A10B establishes a new state of the art for the industry on the leading desktop computer use benchmark.
Holo3 is more than a benchmark leader; it is engineered for production. Built using our agentic flywheel, it has been trained to execute real-world workflows within synthetic enterprise environments. This not only ensures that Holo3 excels in today’s business scenarios, but establishes the foundation for a future where our agents can autonomously navigate virtually any digital landscape.
Best of all, Holo3 achieves this with only 10B active parameters (122B total), so at a fraction of the cost of large-scale proprietary models, such as GPT 5.4 or Opus 4.6. All models are available through our
Inference API
. Holo3-35B-A3B weights are openly accessible on
Hugging Face
under the Apache2 license and freely accessible through our inference API under a free tier.
The Agentic Learning Flywheel
What sets Holo3 apart is its specialized training pipeline—a continuous feedback loop designed to sharpen two core agentic pillars:
perception
and
decision-making
.
Our training flywheel is about teaching our model from annotated examples how to execute specific tasks, all while developing generalist skills across a virtually infinite variety of user interfaces. Here is how we build world-class computer use models:
Synthetic Navigation Data:
using human and generated instructions, we generate scenario-specific navigation examples.
Out-of-Domain Augmentation:
we programmatically extend the scenarios and augment the data to ensure Holo3 can handle the unexpected.
Curated Reinforcement Learning:
every data sample is careful