Reflection AI, Explained: What the Company Is and What It Has Actually Shipped

Reflection AI is a US artificial intelligence company building open-weight frontier models. It was founded in 2024 by two former Google DeepMind researchers and has raised billions of dollars, with Nvidia among its investors.

It has not yet publicly released a frontier foundation model or a set of open weights. That fact is the most important thing on this page, and most coverage of the company buries it.

This guide sets out what is confirmed, what is only reported, and what is genuinely unknown. Where a number or a date has not been confirmed by the company, this page says so instead of guessing.

What Is Reflection AI?

Reflection AI is a private US AI company whose stated mission is to "build the future of open intelligence." On its own site it says it builds "open models that let anyone control their intelligence and help shape the future of AI."

The positioning is explicitly geopolitical. The company presents itself as an American open-weight counterweight to Chinese open-weight leaders such as DeepSeek, which currently dominate the downloadable-model market.

Reflection publishes three commitments on its about page: release open weights for its models, publish the research behind them as papers, and open-source software so organizations can customize deployments.

• Type — private US AI company, founded 2024.
• Stated mission — "Build the future of open intelligence" and "make intelligence open and accessible to all."
• Stated commitments — open weights, published research papers, open-sourced software.
• Named partners on its own site — Dell, the U.S. Department of Energy, and Shinsegae Group.
• Status as of August 2026 — no frontier foundation model or weights checkpoint has been publicly released.

Who Founded Reflection AI?

Reflection AI was founded in 2024 by Misha Laskin and Ioannis Antonoglou. Both came from Google DeepMind.

Laskin is co-founder and CEO. Antonoglou is co-founder and is widely credited as a co-creator of AlphaGo, DeepMind's Go-playing system.

The wider team has been described as researchers and engineers who worked on DeepMind projects including Gemini, AlphaGo, AlphaCode, and AlphaProof. Reflection does not publish individual staff attributions on its site, so treat specific project credits as reported rather than company-confirmed.

• Misha Laskin — co-founder and CEO, formerly of Google DeepMind.
• Ioannis Antonoglou — co-founder, formerly of Google DeepMind, credited as an AlphaGo co-creator.
• Founding year — 2024, with reports placing the launch in March of that year.
• Team background — reported to include people who worked on Gemini, AlphaCode, and AlphaProof.
• Unconfirmed — the company does not publish a per-person project history.

How Much Has Reflection AI Raised, and From Whom?

Reflection AI confirmed on its own blog that it raised $2 billion to build frontier open intelligence. That announcement is the strongest primary source on the round.

The company names its investors directly: B Capital, Citi, CRV, Disruptive, DST, Eric Schmidt, Zoom Ventures, Nvidia, Sequoia, 1789, "and others." Nvidia is the investor most often attached to the company in press coverage.

Valuation figures come from outside the company blog and should be read accordingly. Reflection's own news page links a CNBC segment dated April 23, 2026, in which the CEO confirms a round closed at a $25 billion pre-money valuation.

• Confirmed by Reflection — a $2 billion raise, announced on the company's own blog.
• Confirmed investor list (company-published) — B Capital, Citi, CRV, Disruptive, DST, Eric Schmidt, Zoom Ventures, Nvidia, Sequoia, and 1789.
• Confirmed by the CEO on the record — a round closed at a $25 billion pre-money valuation (CNBC, April 23, 2026, linked from Reflection's own news page).
• Reported, not company-confirmed — an $8 billion valuation on the October 2025 round, and roughly $800 million of that round coming from Nvidia.
• Reported, not company-confirmed — an earlier $130 million total across a seed and Series A, disclosed when the company emerged from stealth in March 2025.

The Compute Deals Behind the Model

Reflection has signed unusually large compute agreements for a company with no released model. Its own news page links the coverage of each one.

The largest is with SpaceX. CNBC reported on June 22, 2026 that SpaceX signed a computing-power deal with Reflection worth up to $6.3 billion.

Bloomberg reported on July 14, 2026 that Nebius would sell $1 billion in AI capacity to Reflection. The Wall Street Journal reported in March 2026 that the company planned to spend billions on a data center in South Korea.

• SpaceX — a computing-power deal worth up to $6.3 billion (CNBC, June 22, 2026).
• Nebius — $1 billion in AI capacity (Bloomberg, July 14, 2026).
• South Korea — a reported multi-billion-dollar data center plan (Wall Street Journal, March 16, 2026).
• Public sector — Reflection was reported by Axios on May 22, 2026 to be powering the Genesis Mission.
• Why it matters to a buyer — compute commitments signal intent and scale. They are not evidence of model quality.

What Has Reflection AI Actually Released?

As of August 2026, Reflection AI has not publicly released a frontier foundation model or an open-weights checkpoint. This is the single fact that should drive any buying decision about the company.

It has shipped a product. Asimov is a code-comprehension agent that reads source code and surrounding context — documentation, project updates, internal messages — to answer questions about how a software system is built.

So the company has a product in market and a stated commitment to open weights, but no downloadable model. Anyone telling you otherwise is describing a plan, not a release.

• Released — Asimov, a code-comprehension agent.
• Not released — any frontier foundation model.
• Not released — any open-weights checkpoint you can download and run.
• Not published — model specifications, benchmark scores, context windows, or per-token prices, because no model exists to describe.
• Committed to — releasing open weights and publishing research papers, per the company's about page.

When Will Reflection AI Release Its First Open Model?

No release date has been announced. Reflection has not published a launch date, a public beta date, or a waitlist for its first frontier open model.

The company has signaled urgency without committing to a date. Its funding announcement says there is "a window of opportunity today to build frontier open intelligence, but it is closing."

Press coverage through mid-2026 consistently reports that Reflection hopes to ship during 2026, while noting that no date has been given. Treat any specific date you see elsewhere as unconfirmed.

• Announced release date — none.
• Announced model name — none.
• Announced license — none, though the company commits in principle to open weights.
• Company signal — "a window of opportunity today to build frontier open intelligence, but it is closing."
• Reported expectation — a 2026 release, which the company has not confirmed with a date.

How Big Is Reflection AI?

Reflection does not publish a current headcount. The most reliable public figure is dated.

TechCrunch reported in October 2025 that the team numbered about 60 people, mostly AI researchers and engineers. That number is nearly a year old as of this writing.

Third-party company-data trackers publish 2026 estimates that disagree with each other by a wide margin. Those estimates are scraped, not disclosed, so this page does not repeat them as fact.

• Last credible reported figure — about 60 people (TechCrunch, October 2025).
• Current headcount — not published by the company.
• Third-party estimates — inconsistent across trackers; treat them as unconfirmed.
• What is clear — the company is hiring, and the compute commitments imply substantial growth in research staff.

What Should a Business Buyer Do About Reflection AI Today?

Nothing yet. There is no model to evaluate, no license to review, and no price to plan against, so there is no decision available to make.

Layer3 Labs advises businesses on model selection and self-hosting tradeoffs, and this question comes up in a specific form: should we hold a slot in the roadmap for a lab that has not shipped? Our answer has consistently been no. Every shortlist we build is made only of models a client can download or call today, because a model you cannot test is not a candidate — it is a hypothesis.

What you can do is set a trigger. Decide now what would make Reflection worth evaluating, so you are not reacting to a launch-day press cycle.

• Do not budget for it. There is no price and no availability date.
• Do not design an architecture around it. Build on a model you can download or call today.
• Do watch the license. The company promises open weights; the specific license terms will decide whether it is usable in your environment.
• Do watch for a technical report. Reflection has committed to publishing research papers alongside models, which is the first real signal of what the model can do.
• Do check independent benchmarks at launch, not vendor slides. Compare against open-weight models you already run.

We Will Update This Page When Reflection's Models Ship

Layer3 Labs will update this page once Reflection AI's first open model is live. This is a commitment, not a placeholder line.

When weights are published, we will add the model name, the parameter count, the context window, the exact license, the access paths, and any published pricing — sourced to Reflection's own pages. We will also add independent benchmark results as they become available, rather than repeating vendor claims.

Until that happens, this page will keep saying that no model has shipped. We will not fill the gap with speculation about specifications or dates.

• What gets added at launch — model name, parameters, context window, license, access paths, published pricing.
• What gets added after launch — independent benchmark results and a practical fit assessment.
• What will never be added — invented specifications, estimated prices, or predicted release dates.
• How to be sure — check this page's updated date, or ask us directly.