Reflection AI Raises $2B, Challenging Global AI Landscape with Open-Source Approach

Reflection raises $2B to be America's open frontier AI lab, challenging DeepSeek | TechCrunch

Reflection, a startup founded just last year by two former Google DeepMind researchers, has raised $2 billion at an $8 billion valuation, a whopping 15x leap from its $545 million valuation just seven months ago. The company, which originally focused on autonomous coding agents, is now positioning itself as both an open-source alternative to closed frontier labs like OpenAI and Anthropic, and a Western equivalent to Chinese AI firms like DeepSeek. The startup was launched in March 2024 by Misha Laskin, who led reward modeling for DeepMind's Gemini project, and Ioannis Antonoglou, who co-created AlphaGo, the AI system that famously beat the world champion in the board game Go in 2016. Their background developing these very advanced AI systems is central to their pitch, which is that the right AI talent can build frontier models outside established tech giants. Along with its new round, Reflection announced that it has recruited a team of top talent from DeepMind and OpenAI, and built an advanced AI training stack that it promises will be open for all. Perhaps most importantly, Reflection says it has "identified a scalable commercial model that aligns with our open intelligence strategy." Reflection's team currently numbers about 60 people -- mostly AI researchers and engineers across infrastructure, data training, and algorithm development, per Laskin, the company's CEO. Reflection has secured a compute cluster and hopes to release a frontier language model next year that's trained on "tens of trillions of tokens," he told TechCrunch. "We built something once thought possible only inside the world's top labs: a large-scale LLM and reinforcement learning platform capable of training massive Mixture-of-Experts (MoEs) models at frontier scale," Reflection wrote in a post on X. "We saw the effectiveness of our approach first-hand when we applied it to the critical domain of autonomous coding. With this milestone unlocked, we're now bringing these methods to general agentic reasoning." MoE refers to a specific architecture that powers frontier LLMs -- systems that, previously, only large, closed AI labs were capable of training at scale. DeepSeek had a breakthrough moment when it figured out how to train these models at scale in an open way, followed by Qwen, Kimi, and other models in China. "DeepSeek and Qwen and all these models are our wake up call because if we don't do anything about it, then effectively, the global standard of intelligence will be built by someone else," Laskin said. "It won't be built by America." Laskin added that this puts the U.S. and its allies at a disadvantage because enterprises and sovereign states often won't use Chinese models due to potential legal repercussions. "So you can either choose to live at a competitive disadvantage or rise to the occasion," Laskin said. American technologists have largely celebrated Reflection's new mission. David Sacks, the White House AI and Crypto Czar, posted on X: "It's great to see more American open source AI models. A meaningful segment of the global market will prefer the cost, customizability, and control that open source offers. We want the U.S. to win this category too." Clem Delangue, co-founder and CEO of Hugging Face, an open and collaborative platform for AI builders, told TechCrunch of the round, "This is indeed great news for American open-source AI. Added Delangue, "Now the challenge will be to show high velocity of sharing of open AI models and datasets (similar to what we're seeing from the labs dominating in open-source AI)." Reflection's definition of being "open" seems to center on access rather than development, similar to strategies from Meta with Llama or Mistral. Laskin said Reflection would release model weights -- the core parameters that determine how an AI system works -- for public use while largely keeping datasets and full training pipelines proprietary. "In reality, the most impactful thing is the model weights, because the model weights anyone can use and start tinkering with them," Laskin said. "The infrastructure stack, only a select handful of companies can actually use that." That balance also underpins Reflection's business model. Researchers will be able to use the models freely, Laskin said, but revenue will come from large enterprises building products on top of Reflection's models and from governments developing "sovereign AI" systems, meaning AI models developed and controlled by individual nations. "Once you get into that territory where you're a large enterprise, by default you want an open model," Laskin said. "You want something you will have ownership over. You can run it on your infrastructure. You can control its costs. You can customize it for various workloads. Because you're paying some ungodly amount of money for AI, you want to be able to optimize it as much as much as possible, and really that's the market that we're serving." Reflection hasn't yet released its first model, which will be largely text-based, with multimodal capabilities in the future, according to Laskin. It will use the funds from this latest round to get the compute resources needed to train the new models, the first of which the company is aiming to release early next year. Investors in Reflection's latest round include Nvidia, Disruptive, DST, 1789, B Capital, Lightspeed, GIC, Eric Yuan, Eric Schmidt, Citi, Sequoia, CRV, and others.

Reflection AI lands $2B at $8B valuation to expand frontier AI infrastructure and safety research - SiliconANGLE

Reflection AI lands $2B at $8B valuation to expand frontier AI infrastructure and safety research Artificial intelligence startup Reflection AI Inc. revealed today that it had raised $2 billion in new funding to scale its open-source frontier AI models, expand global infrastructure and research teams and invest in safety, evaluation, and responsible deployment. According to The New York Times, the round was raised on a valuation of $8 billion, significantly up from the $545 million the company was valued it in March when it launched with $130 million in funding. Founded in 2024, Reflection AI was created by ex-Google DeepMind researchers Misha Laskin and Ioannis Antonoglou with a mission to build super intelligent, autonomous systems starting from AI agents that can write, debug and optimize code. Reflection AI is developing autonomous coding agents rather than simple "copilot" tools, systems that not only suggest code but also reason over entire software systems, iterate, test, refactor and even manage infrastructure. The company's first autonomous coding agent, called Asimov, launched in July and is designed and built with a view to achieving "super intelligence" much faster. Asimov is trained to understand how software is created by ingesting not only code but the entirety of a business' data to try to piece together why an application or system does what it does. To power the agents, Reflection AI is building and maintaining a training stack combining large language models with reinforcement learning and specialized architectures such as mixture-of-experts models to scale agentic reasoning at frontier levels. The company emphasizes openness, transparency and safety with an approach that frontier intelligence should not be locked behind closed labs but accessible, auditable and governed by community norms, with investment in capability evaluation, security research and responsible deployment. Reflection AI views autonomous coding as a "root node" in that by mastering software itself, users can bootstrap higher forms of automation and intelligence. In other words, Reflection sees tools that build tools as an essential stepping stone toward more general, self-improving AI. Nvidia Corp. led the round, with Lightspeed Venture Partners LP, Sequoia Capital Operations, DST Global LP, former Google LLC chief executive Eric Schmidt and 1789 Capital also participating. "We've raised significant capital and identified a scalable commercial model that aligns with our open intelligence strategy, ensuring we can continue building and releasing frontier models sustainably," Reflection AI said in a blog post. "We are now scaling up to build open models that bring together large-scale pretraining and advanced reinforcement learning from the ground up."

Ex-DeepMind stars raise $2B for a new US open-source AI giant

The company's core mission is to establish a U.S.-based open-source frontier AI lab to challenge closed-access labs like OpenAI and foreign competitors. Reflection, a startup founded by former Google DeepMind researchers, has raised $2 billion at an $8 billion valuation. The company aims to establish an open-source frontier AI lab in the U.S. to challenge closed and foreign competitors. The company was established in March 2024 by co-founders Misha Laskin and Ioannis Antonoglou. Laskin previously led reward modeling for the Gemini project at Google DeepMind, while Antonoglou was a co-creator of AlphaGo, the AI system that defeated the world Go champion in 2016. This experience informs their strategy to build frontier models outside established tech giants. Reflection initially concentrated on creating autonomous coding agents before broadening its mission to serve as an open-source alternative to labs such as OpenAI and Anthropic. The new $2 billion funding round elevates Reflection's valuation to $8 billion, a 15-fold increase from its $545 million valuation recorded seven months prior. Along with the new capital, Reflection announced the recruitment of top AI talent from DeepMind and OpenAI. The company also stated it has developed an advanced AI training stack to be made open for all and has "identified a scalable commercial model that aligns with our open intelligence strategy." Reflection's team, led by CEO Misha Laskin, numbers about 60 people. This staff is primarily comprised of AI researchers and engineers working on infrastructure, data training, and algorithm development. The startup has secured a compute cluster and, according to Laskin, plans to release a frontier language model next year. This model is expected to be trained on a dataset of "tens of trillions of tokens." In a post on the social media platform X, Reflection detailed its technical achievements. "We built something once thought possible only inside the world's top labs: a large-scale LLM and reinforcement learning platform capable of training massive Mixture-of-Experts (MoEs) models at frontier scale," the company stated. "We saw the effectiveness of our approach first-hand when we applied it to the critical domain of autonomous coding. With this milestone unlocked, we're now bringing these methods to general agentic reasoning." The Mixture-of-Experts (MoE) model is a specific system architecture that underpins frontier-level large language models. The ability to train these complex models at scale was, until recently, primarily confined to large, closed-access AI laboratories. Chinese firms, including DeepSeek, made a significant advance by developing methods to train MoE models in an open-source manner. This development was subsequently followed by similar achievements from other China-based models like Qwen and Kimi. The emergence of these powerful open-source models from China serves as a primary motivator for Reflection's mission. "DeepSeek and Qwen and all these models are our wake-up call because if we don't do anything about it, then effectively, the global standard of intelligence will be built by someone else," Laskin said. He added, "It won't be built by America."

This DeepSeek Rival Founded By DeepMind Alum Raises $2B, Hits $8B Valuation

Backed by the likes of Nvidia, Reflection AI is looking to build open-source models that can compete with Chinese competitors. At the start of the year, Chinese A.I. startup DeepSeek jolted Silicon Valley with a powerful open-source model that rivaled Western systems at a fraction of the cost. Out of that shockwave came Reflection AI, a New York-based startup founded by top A.I. researchers that has just raised $2 billion to build similarly accessible technology. The funding round valued the company at a staggering $8 billion, according to The New York Times. Sign Up For Our Daily Newsletter Sign Up Thank you for signing up! By clicking submit, you agree to our <a href="http://observermedia.com/terms">terms of service</a> and acknowledge we may use your information to send you emails, product samples, and promotions on this website and other properties. You can opt out anytime. See all of our newsletters Returning investors include Nvidia, Lightspeed Venture Partners and Sequoia Capital, while new participants include former Google CEO Eric Schmidt and 1789 Capital, the venture capital firm linked to Donald Trump Jr. Reflection previously raised about $130 million from backers like LinkedIn co-founder Reid Hoffman and Meta executive Alexandr Wang, according to Crunchbase, and was last valued at around $550 million in March. Reflection AI emerged from stealth earlier this year, co-founded by former Google DeepMind researchers Misha Laskin and Ioannis Antonoglou. Laskin previously founded Claire AI, a startup focused on predicting retailer product demand. Antonoglou, DeepMind's sixth-ever researcher, worked on the lab's breakthrough AlphaGo model. Reflection AI is currently hiring for eight open roles across New York, San Francisco and London. Its growing staff includes former employees of OpenAI, Meta, Character.AI and Anthropic. Like many of its rivals, Reflection aims to build superintelligence and is focused on autonomous coding tools. It recently released an A.I. coding agent called Asimov. Central to its mission, however, is the belief that open-source A.I. should be widely available to developers, researchers and individual users. Reflection's ambitious goal was spurred by the shock of DeepSeek's emergence -- an event many in the tech world likened to the Soviet Union's 1957 launch of Sputnik 1, which spurred the U.S. space race. "The reason for our existence is we are living through a modern day Sputnik moment," Laskin, who also serves as Reflection's CEO, told CNBC SquawkBox today (Oct. 8). "When you think about what we're competing against today, it's the incredible open models that are coming from China." As A.I. becomes increasingly embedded in science, education, energy and supply chains, Reflection warns that concentrating such power in a few closed systems could stifle innovation and exclude other players. The company also argues that openness promotes safety, enabling a broader range of researchers -- rather than a handful of private labs -- to identify and address potential risks in A.I. systems. Reflection is the latest A.I. model builder to benefit from surging investor enthusiasm for the field. According to Crunchbase, global venture capital funding during the third quarter of 2025 totaled $97 billion, representing a 38 percent increase compared to the same time period last year. Nearly half of that total, about 46 percent, went to A.I. firms, with the three largest rounds of the quarter raised by foundation model companies Anthropic, xAI and Mistral AI.

Nvidia-backed Reflection AI raises $2 billion in funding, boosts valuation to $8 billion

The funding round, led by Nvidia, saw participation from prominent investors, including former Google CEO Eric Schmidt, Citi, and Donald Trump Jr-backed private equity firm 1789 Capital, as well as existing investors Lightspeed and Sequoia. Reflection AI, a startup backed by Nvidia, said on Thursday it has raised $2 billion in a new funding round that values the company at $8 billion, as investor interest in artificial intelligence remains unabated. The funding round, led by Nvidia, saw participation from prominent investors, including former Google CEO Eric Schmidt, Citi, and Donald Trump Jr-backed private equity firm 1789 Capital, as well as existing investors Lightspeed and Sequoia. Founded in 2024 by former DeepMind researchers Misha Laskin and Ioannis Antonoglou, Reflection develops tools that automate software development, a fast-growing use case for AI. The investment comes as the AI sector continues to attract significant interest from venture capital firms and investors. Global venture funding in the third quarter of 2025 rose 38% from a year earlier to $97 billion, with around 46% of the total invested in AI firms. Reflection's new valuation marks a sharp step up from its previous round, when it raised $130 million at a $545 million valuation, according to PitchBook data. The company's peers in the AI market include OpenAI and China's DeepSeek, among others.

Nvidia-backed Reflection AI raises $2 billion in funding, boosts valuation to $8 billion

(Corrects to remove reference to Nvidia being a lead investor in the funding round in paragraph 2) (Reuters) -Reflection AI, a startup backed by Nvidia, said on Thursday it has raised $2 billion in a new funding round that values the company at $8 billion, as investor interest in artificial intelligence remains unabated. The funding round saw participation from prominent investors, including former Google CEO Eric Schmidt, Citi and Donald Trump Jr.-backed private equity firm 1789 Capital, as well as existing investors Lightspeed and Sequoia. Founded in 2024 by former DeepMind researchers Misha Laskin and Ioannis Antonoglou, Reflection develops tools that automate software development, a fast-growing use case for AI. The investment comes as the AI sector continues to attract significant interest from venture capital firms and investors. Global venture funding in the third quarter of 2025 rose 38% from a year earlier to $97 billion, with around 46% of the total invested in AI firms. Reflection's new valuation marks a sharp step up from its previous round, when it raised $130 million at a $545 million valuation, according to PitchBook data. The company's peers in the AI market include OpenAI and China's DeepSeek, among others. (Reporting by Pritam Biswas in Bengaluru; Editing by Tasim Zahid)