Ginkgo Bioworks Holdings, Inc. (DNA) Earnings
Ginkgo Bioworks Holdings, Inc. is expected to report next earnings on August 6, 2026 (in NaN days), with a consensus EPS estimate of $-1.05. DNA has beaten EPS estimates in 2 of its last 11 reported quarters (average surprise +0.2% over the last four).
| Report date | EPS est | EPS actual | Surprise | Revenue | Rev. surprise |
|---|---|---|---|---|---|
| May 7, 2026 | $-1.21 | $-1.28 | -5.7% | $19M | -54.6% |
| Nov 6, 2025 | $-1.24 | $-1.45 | -16.9% | $39M | +3.4% |
| Aug 7, 2025 | $-1.44 | $-1.10 | +23.6% | $50M | +27.4% |
| Aug 8, 2024 | $-3.20 | $-3.20 | +0.0% | $56M | +24.9% |
| May 9, 2024 | $-3.20 | $-3.20 | +0.0% | $38M | -13.2% |
| Feb 29, 2024 | $-3.60 | $-3.60 | +0.0% | $35M | -24.5% |
| Mar 1, 2023 | $-12.00 | $-1.60 | +86.7% | $98M | +37.1% |
| Nov 14, 2022 | $-10.00 | $-16.00 | -60.0% | $66M | +10.0% |
| Aug 15, 2022 | $-2.00 | $-16.40 | -720.0% | $145M | +83.4% |
| May 16, 2022 | $-1.60 | $-2.00 | -25.0% | $168M | +59.4% |
| Nov 15, 2021 | $-1.60 | $-2.80 | -75.0% | $78M | +40.6% |
| Sep 20, 2021 | — | $-1.67 | — | $44M | — |
Source: company filings + earnings calendar. For informational purposes only — not investment advice.
Earnings call summary
Q1 FY2026 · May 7, 2026
AI summary of management’s prepared remarks and analyst Q&A. For informational purposes only — not investment advice.
Management highlights
Jason mentioned that in 2026, the focus is on investing to win the autonomous labs category. Two ways are taking services, solutions, data points, cloud lab on Nebula in Boston and getting early adopters to buy autonomous lab systems like with Pacific Northwest National Labs. Also, the spinoff of biosecurity unit into Perimeter was closed. Steve talked about the change in presenting results due to biosecurity divestiture being reported as discontinued operations. Jason gave an analogy of autonomous labs to the transportation industry's autonomous cars, explaining the need for flexibility and automation in labs. Discussed the value prop of autonomous labs like cost savings, increased research productivity, and enabling AI - scientist - run experiments. Showcased Nebula's hardware like rack carts, running unique protocols, having a complex scheduler, and seeing interest from scientists and government. Also talked about cloud lab service, data points, and solutions business.
Guidance
Reaffirming overall cash burn guidance for 2026 totaling $125 to $150 million, reflecting a balance among cost efficiency, continuing services and tools, and investments in autonomous labs.
Segment performance
In Q1 2026, revenue was $19 million, down 49% from Q1 2025 (excluding non - cash revenue of $7.5 million in Q1 2025, revenue was down 37% from prior year). R&D expense decreased from $49 million in Q1 2025 to $30 million in Q1 2026. G&A expense decreased from $20 million in Q1 2025 to $13 million in Q1 2026. Net loss from continuing operations was $76 million in Q1 2026, compared to $83 million in the prior year. Adjusted EBITDA in Q1 2026 was negative $42 million, down from negative $44 million in Q1 2025. Cash burn in Q1 2026 was $48 million, down from $58 million in Q1 2025. Now operating as a single segment as biosecurity business is discontinued operations.
Analyst Q&A
Q: How should we think about the potential impact to revenues this year from the AWS and BenchLink announcements? How have the launches gone thus far and what is baked into your assumptions for the rest of 2026 for these new platforms?
A: Jason is excited about these announcements, seeing them as new cloud layers talking directly to labs as sales channels, starting around antibodies but excited to fan out.
Q: What are you hearing on data points and the collective AI - driven offerings with Ginkgo as especially attractive for customers as biotech and pharma companies continue to roll out their own AI capabilities? In other words, what kind of demand dynamics are you seeing here? And are there any potential revenue funnel unlocks we should watch for over the coming quarters from this part of the business?
A: Brendan says DataPoint has 10 top pharma company customers, with revenue unlock being repeat business as customers build in - house models.
Q: How much efficiency improvements after using GPT 5.5? Any idea for space left for improvement? Will this be a transitional factor?
A: Jason talks about the project with OpenAI showing 40% improvement, excited to do more with OpenAI and think it's an open terrain for reasoning models in experimental design and analysis.
Q: How does the use of Ginkgo's automated lab affect overall costs? Are there meaningful differences in speed, for example, turnaround time for experiments? And have you observed improvements in success rates, reproducibility, or scalability since moving to the autonomous lab?
A: Jason says about threefold reduction in space utilization and fourfold increase in time, speed can be improved by starting experiments at non - traditional times, reproducibility is advantaged due to audit trail, and throughput will explode.
Q: When do you actually expect to get to 100 racks?
A: Jason says they've been installing racks, adding 50 new ones in three weeks, and the connection between systems will be turned on soon, expecting to be at 100 racks soon.