With the amount of new subnets being added it can be hard to get up to date information across all subnets, so data may be slightly out of date from time to time
With the amount of new subnets being added it can be hard to get up to date information across all subnets, so data may be slightly out of date from time to time
Apex is a Bittensor subnet that’s pushing the boundaries of agentic reasoning by incentivizing miners to build workflows that actively reduce hallucinations and improve the inference quality of large language models. What’s compelling about their approach is how validators host an ongoing competitive arena—where LLMs are equipped with tools and function calls—and only the most capable earn TAO emissions.
What sets them apart is the dynamic and asymmetrical nature of their evaluations, which not only power miner rankings but also produce a high-volume, high-quality dataset. We’re talking millions of tokens per day, generated from real-world agentic tasks. That output becomes the training fuel for fine-tuning in Subnet 37, making Apex a key engine for both performance benchmarking and model improvement across the network.
Apex is a Bittensor subnet that’s pushing the boundaries of agentic reasoning by incentivizing miners to build workflows that actively reduce hallucinations and improve the inference quality of large language models. What’s compelling about their approach is how validators host an ongoing competitive arena—where LLMs are equipped with tools and function calls—and only the most capable earn TAO emissions.
What sets them apart is the dynamic and asymmetrical nature of their evaluations, which not only power miner rankings but also produce a high-volume, high-quality dataset. We’re talking millions of tokens per day, generated from real-world agentic tasks. That output becomes the training fuel for fine-tuning in Subnet 37, making Apex a key engine for both performance benchmarking and model improvement across the network.
Apex (Subnet 1) is where Bittensor’s most competitive, cutting-edge research in agentic reasoning unfolds. They’re building the kind of open-source intelligence that can rival and at times outperform centralized models on task-specific functions. This subnet isn’t just part of the network; it’s the crucible where innovation meets performance, shaping the trajectory of decentralized AI.
Leading Bittensor’s Race for Intelligence
Bittensor’s long-term viability depends on continuous breakthroughs that rival proprietary AI systems. Apex plays a central role in this mission. It’s the protocol’s flagship arena — the environment where validators and miners go head-to-head to build more capable agents, and where mechanism design is constantly being refined.
Since its rebuild in early 2024, Apex has evolved to incorporate advanced inference strategies like response ensembling and agentic workflows, adapting quickly to the demands of fast-moving LLM research. They’ve positioned themselves as the backbone for testing and scaling the very systems that will define decentralized AI’s future.
Beyond Centralized Benchmarks
What makes Apex so compelling is that they aren’t just chasing benchmarks; they’re surpassing them. By orchestrating workflows that combine LLMs with agentic reasoning, Apex has shown that open systems can outperform closed models at targeted tasks. This isn’t theoretical; it’s already being demonstrated across real-world use cases.
How Apex Incentivizes Intelligence
1. Transforming Raw Intelligence into User Products
At its core, Apex turns high-quality outputs into digital commodities. Whether it’s through chat interfaces, APIs, or enterprise tooling, users tap into a constantly evolving hivemind — one that’s trained and refined by competition, not central authority. Right now, they’re already powering four distinct products across the network.
2. Expanding the Incentive Landscape
They’ve pioneered mechanisms that reward high-quality, human-like responses — not just the ability to game synthetic prompts. By incorporating organic queries into the validation layer, Apex pushes miners to generate answers that are genuinely useful, grounded, and context-aware.
3. Fueling the Broader Bittensor Ecosystem
Apex isn’t operating in a vacuum. It’s deeply integrated with Subnet 9 for pretraining, Subnet 13 for data structuring and sentiment analysis, and Subnet 37 for fine-tuning. Together, they form a full intelligence pipeline — one that continuously creates, tests, and evolves open-source AI.
The Flagship of Open-Source AI
As the first subnet on Bittensor, Apex continues to be the standard-bearer, not just for its legacy but for what’s next. With each iteration, they’re not just refining competitive intelligence — they’re defining what decentralized AI can become.
Apex (Subnet 1) is where Bittensor’s most competitive, cutting-edge research in agentic reasoning unfolds. They’re building the kind of open-source intelligence that can rival and at times outperform centralized models on task-specific functions. This subnet isn’t just part of the network; it’s the crucible where innovation meets performance, shaping the trajectory of decentralized AI.
Leading Bittensor’s Race for Intelligence
Bittensor’s long-term viability depends on continuous breakthroughs that rival proprietary AI systems. Apex plays a central role in this mission. It’s the protocol’s flagship arena — the environment where validators and miners go head-to-head to build more capable agents, and where mechanism design is constantly being refined.
Since its rebuild in early 2024, Apex has evolved to incorporate advanced inference strategies like response ensembling and agentic workflows, adapting quickly to the demands of fast-moving LLM research. They’ve positioned themselves as the backbone for testing and scaling the very systems that will define decentralized AI’s future.
Beyond Centralized Benchmarks
What makes Apex so compelling is that they aren’t just chasing benchmarks; they’re surpassing them. By orchestrating workflows that combine LLMs with agentic reasoning, Apex has shown that open systems can outperform closed models at targeted tasks. This isn’t theoretical; it’s already being demonstrated across real-world use cases.
How Apex Incentivizes Intelligence
1. Transforming Raw Intelligence into User Products
At its core, Apex turns high-quality outputs into digital commodities. Whether it’s through chat interfaces, APIs, or enterprise tooling, users tap into a constantly evolving hivemind — one that’s trained and refined by competition, not central authority. Right now, they’re already powering four distinct products across the network.
2. Expanding the Incentive Landscape
They’ve pioneered mechanisms that reward high-quality, human-like responses — not just the ability to game synthetic prompts. By incorporating organic queries into the validation layer, Apex pushes miners to generate answers that are genuinely useful, grounded, and context-aware.
3. Fueling the Broader Bittensor Ecosystem
Apex isn’t operating in a vacuum. It’s deeply integrated with Subnet 9 for pretraining, Subnet 13 for data structuring and sentiment analysis, and Subnet 37 for fine-tuning. Together, they form a full intelligence pipeline — one that continuously creates, tests, and evolves open-source AI.
The Flagship of Open-Source AI
As the first subnet on Bittensor, Apex continues to be the standard-bearer, not just for its legacy but for what’s next. With each iteration, they’re not just refining competitive intelligence — they’re defining what decentralized AI can become.
Will Squires – CEO and Co-Founder
Will has dedicated his career to navigating complexity, spanning from designing and constructing significant infrastructure to spearheading the establishment of an AI accelerator. With a background in engineering, he made notable contributions to transport projects such as Crossrail and HS2. Will’s expertise led to an invitation to serve on the Mayor of London’s infrastructure advisory panel and to lecture at UCL’s Centre for Advanced Spatial Analysis (CASA). He was appointed by AtkinsRéalis to develop an AI accelerator, which expanded to encompass over 60 staff members globally. At XYZ Reality, a company specializing in augmented reality headsets, Will played a pivotal role in product and software development, focusing on holographic technology. Since 2023, Will has provided advisory services for the Opentensor Foundation, contributing to the launch of Revolution.
Steffen Cruz – CTO and Co-Founder
Steffen earned his PhD in subatomic physics from the University of British Columbia, Canada, focusing on developing software to enhance the detection of extremely rare events (10^-7). His groundbreaking research contributed to the identification of novel exotic states of nuclear matter and has been published in prestigious scientific journals. As the founding engineer of SolidState AI, he pioneered innovative techniques for physics-informed machine learning (PIML). Steffen was subsequently appointed as the Chief Technology Officer of the Opentensor Foundation, where he played a pivotal role as a core developer of Subnet 1, the foundation’s flagship subnet. In this capacity, he enhanced the adoption and accessibility of Bittensor by authoring technical documentation, tutorials, and collaborating on the development of the subnet template.
Michael Bunting – CFO
Before joining Macrocosmos, Mike spent 12 years in investment banking, where he guided clients through major strategic and financial transitions across more than £1 billion in international M&A and capital raising deals. Most recently serving as a Director at Piper Sandler, he brings deep experience in advising high-growth startups on strategy, business planning, funding pathways, and corporate governance. Mike has also worked closely with multinational corporations and prominent financial investors throughout his career.
Elena Nesterova – Head of Delivery
Volodymyr Truba – Senior Machine Learning Engineer
Alma Schalèn – Head of Product Design
Felix Quinque – Machine Learning Lead
Dmytro Bobrenko – Machine Learning/AI Lead
Alan Aboudib – Machine Learning Lead
Alex Williams – People & Talent Manager
Chris Zacharia – Communications Lead
Brian McCrindle – Senior Machine Learning Engineer
Lawrence Hunt – Frontend Engineer
Nicholas Miller – Senior Software Engineer
Kalei Brady – Data Scientist
Szymon Fonau – Machine Learning Engineer
Monika Stankiewicz – Executive Assistant
Amy Chai – Junior Machine Learning Engineer
Giannis Evagorou – Senior Software Engineer
Richard Wardle – Junior Software Engineer
Kai Morris – Content & Community specialist
Lewis Sword – Junior Software Engineer
Will Squires – CEO and Co-Founder
Will has dedicated his career to navigating complexity, spanning from designing and constructing significant infrastructure to spearheading the establishment of an AI accelerator. With a background in engineering, he made notable contributions to transport projects such as Crossrail and HS2. Will’s expertise led to an invitation to serve on the Mayor of London’s infrastructure advisory panel and to lecture at UCL’s Centre for Advanced Spatial Analysis (CASA). He was appointed by AtkinsRéalis to develop an AI accelerator, which expanded to encompass over 60 staff members globally. At XYZ Reality, a company specializing in augmented reality headsets, Will played a pivotal role in product and software development, focusing on holographic technology. Since 2023, Will has provided advisory services for the Opentensor Foundation, contributing to the launch of Revolution.
Steffen Cruz – CTO and Co-Founder
Steffen earned his PhD in subatomic physics from the University of British Columbia, Canada, focusing on developing software to enhance the detection of extremely rare events (10^-7). His groundbreaking research contributed to the identification of novel exotic states of nuclear matter and has been published in prestigious scientific journals. As the founding engineer of SolidState AI, he pioneered innovative techniques for physics-informed machine learning (PIML). Steffen was subsequently appointed as the Chief Technology Officer of the Opentensor Foundation, where he played a pivotal role as a core developer of Subnet 1, the foundation’s flagship subnet. In this capacity, he enhanced the adoption and accessibility of Bittensor by authoring technical documentation, tutorials, and collaborating on the development of the subnet template.
Michael Bunting – CFO
Before joining Macrocosmos, Mike spent 12 years in investment banking, where he guided clients through major strategic and financial transitions across more than £1 billion in international M&A and capital raising deals. Most recently serving as a Director at Piper Sandler, he brings deep experience in advising high-growth startups on strategy, business planning, funding pathways, and corporate governance. Mike has also worked closely with multinational corporations and prominent financial investors throughout his career.
Elena Nesterova – Head of Delivery
Volodymyr Truba – Senior Machine Learning Engineer
Alma Schalèn – Head of Product Design
Felix Quinque – Machine Learning Lead
Dmytro Bobrenko – Machine Learning/AI Lead
Alan Aboudib – Machine Learning Lead
Alex Williams – People & Talent Manager
Chris Zacharia – Communications Lead
Brian McCrindle – Senior Machine Learning Engineer
Lawrence Hunt – Frontend Engineer
Nicholas Miller – Senior Software Engineer
Kalei Brady – Data Scientist
Szymon Fonau – Machine Learning Engineer
Monika Stankiewicz – Executive Assistant
Amy Chai – Junior Machine Learning Engineer
Giannis Evagorou – Senior Software Engineer
Richard Wardle – Junior Software Engineer
Kai Morris – Content & Community specialist
Lewis Sword – Junior Software Engineer
Huge thanks to Keith Singery (aka Bittensor Guru) for all of his fantastic work in the Bittensor community. Make sure to check out his other video/audio interviews by clicking HERE.
Steffen Cruz, previously the CTO of the Opentensor Foundation, has joined forces with his longtime friend Will Squires to establish Macrocosmos. Leading subnets 1, 9, 13, 25 and 37, this team is actively shaping the future of Bittensor and stands as one of the most influential entities within the ecosystem.
In this second video, they spend much of the episode covering Subnet 13’s rebranding to “Gravity” and the team’s prediction of a Trump victory along with how this has managed to build a team of PHDs and machine learning professionals around Bittensor.
Keep ahead of the Bittensor exponential development curve…
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