Microsoft (MSFT) has taken a bold step in the race for artificial intelligence (AI) infrastructure. The company signed a deal with Nebius, an AI-focused infrastructure provider, valued between $17.4 billion and $19.4 billion over five years. This agreement, one of the largest of its kind, shows how fast demand for AI computing is growing and highlights Nvidia as a major beneficiary.
A Deal That Turns Heads
The contract between Microsoft and Nebius will supply Microsoft with advanced GPU-powered computing infrastructure. Deliveries will begin in late 2025 and are expected to continue for at least five years. The deal includes an option for Microsoft to expand capacity, raising the value from $17.4 billion to as much as $19.4 billion.
This agreement reflects the massive appetite for computing power created by AI models and applications. Training and running these systems requires huge numbers of high-performance GPUs. By choosing Nebius as a supplier, Microsoft ensures it has what it needs to compete with Amazon and Google in the cloud and AI markets.
The announcement had an immediate impact on financial markets. Nebius’ shares soared over 40% after the news, and it is the highest since the company’s founding. This shows how excited investors are about its role in the booming AI ecosystem.

Nebius: A Rising Infrastructure Player
Nebius is a relatively new name in the global AI infrastructure market. Based in Amsterdam, it emerged from a spin-off of Yandex’s international operations. The company calls itself a “neocloud” provider. This means it offers GPU-focused infrastructure tailored for AI workloads.
The Microsoft deal transforms Nebius almost overnight into one of the most important players in this space. The agreement not only guarantees billions in revenue but also enhances Nebius’ profile with future partners.
The company plans to raise $3 billion more. They will use financing tools like convertible notes and stock offerings. These funds will help expand data centers and strengthen infrastructure. They aim to meet the demand from the new partnership with Microsoft.
This expansion is critical. AI adoption continues to accelerate, and the world’s largest companies are competing to secure reliable access to GPUs. Nebius, with Microsoft as a customer, has demonstrated its ability to deliver capacity on a massive scale.

Nvidia: The Silent Winner
While Microsoft and Nebius signed the contract, Nvidia also emerged as a big winner. Nebius’ infrastructure relies heavily on Nvidia’s GPUs, which are the most widely used chips for training and running AI models.
For Nvidia, this deal means billions of dollars in new demand for its products. Nebius will need to scale up its GPU purchases significantly to meet the contract requirements. In addition, Nvidia already owns a stake in Nebius, giving it a direct interest in the company’s success.
This development strengthens Nvidia’s dominance in the AI chip market. Despite competition from rivals such as AMD and Intel, Nvidia remains the go-to choice for large-scale AI infrastructure. The Microsoft–Nebius deal is another sign that Nvidia’s chips will remain central to AI growth for years to come.
Microsoft’s Strategy: Growth Without Heavy Spending
One of the most interesting aspects of this deal is what it says about Microsoft’s strategy. Rather than building all the data centers it needs on its own, the giant tech is turning to specialized providers like Nebius. This approach allows the company to expand its AI infrastructure faster and at a lower upfront cost.
Microsoft lowers financial risk by outsourcing a lot of capital expenses to Nebius. This way, they still get vital GPU capacity. Nebius will handle the heavy lifting of financing, building, and managing new data centers.
Microsoft, in turn, locks in the resources it needs to scale AI services such as Azure OpenAI without waiting years for in-house construction.
Shaking Up the AI Infrastructure Game
The agreement between Microsoft and Nebius reflects a larger shift in the way AI infrastructure is being built. Instead of relying solely on in-house resources, tech giants are increasingly forming partnerships with focused infrastructure providers. This approach has several implications:
- Faster scaling: Partnerships help companies like Microsoft quickly boost AI capacity. This method avoids the delays of constructing new facilities from the ground up.
- Capital efficiency: Outsourcing big projects saves resources. Companies can then invest in software, apps, and customer services.
- Industry growth: Deals of this size validate the role of new players like Nebius and give them the financial backing to expand further.
The AI Gold Rush: Billions Flowing Into GPUs
The Microsoft–Nebius deal fits into a fast-growing AI infrastructure market. Global spending on AI chips and cloud capacity is projected to exceed $200 billion by 2030, up from about $45 billion in 2024. One report even forecasted it to grow up to $400 billion by the decade’s end.

Demand for GPUs is expected to grow at an annual rate of 25–30%, driven by generative AI adoption. Analysts forecast that “neocloud” providers like Nebius could capture up to 15% of AI infrastructure contracts by 2030.
Nvidia, already holding more than 80% of the AI GPU market, is likely to remain the dominant supplier as demand surges worldwide.
At What Cost? AI’s Carbon and Energy Footprint
While the $19B Microsoft–Nebius deal reflects rapid AI growth, it also raises questions about sustainability. Training and running AI models need a lot of computing power. This means they also use a lot of energy.
Recent studies estimate that training a single large language model can emit over 500 metric tons of CO₂—equivalent to the lifetime emissions of several cars. Below is a comparison of the energy use and carbon footprint of the top LLMs used today.

Data centers powering AI workloads already account for about 1.5% of global electricity use, and this could rise to 4% by 2030 as AI adoption surges. Much of this demand comes from GPUs, which consume far more power than traditional processors. Companies like Microsoft are under pressure to balance growth with environmental responsibility.
This means:
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Investing in renewable energy
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Improving data center efficiency
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Exploring low-carbon infrastructure solutions
If the sector keeps going as it is, AI might turn into a big source of carbon emissions in tech. Major energy efficiency breakthroughs are needed to change this.
- INTERESTING READ: ChatGPT, Gemini, and DeepSeek Are on an AI Race – But at What Climate Cost? A Comparison
Why Everyone Wins in This AI Mega-Deal
The $19 billion deal between Microsoft and Nebius marks a turning point in the AI infrastructure market. It gives Microsoft the capacity it needs to compete in the fast-moving AI race. It elevates Nebius from a growing player to a global force in cloud infrastructure. And it confirms Nvidia’s role as the backbone of AI computing, benefiting directly from the demand for GPUs.
As demand for AI continues to rise, more deals like this are likely. Microsoft’s partnership with Nebius may be one of the biggest so far, but it is unlikely to be the last. The AI race is just beginning, and infrastructure providers, chipmakers, and cloud giants will all play critical roles in shaping its future.
- FURTHER READING: Study Shows How AI Can Cut Over 5 Billion Tons of Carbon Emissions in 3 Key Sectors
The post Microsoft Signs $19 Billion AI Deal With Nebius: Nvidia Scores Big as GPU King appeared first on Carbon Credits.
Carbon Footprint
Designing an Insetting Program: A Step-by-Step Playbook for Procurement
Insetting program design starts with your supplier map. The carbon claim comes much later.
Consider a coffee procurement team that funds a farm intervention before checking its sourcing data. The supplier aggregates coffee lots from several regions. The buyer lacks farm-level traceability. Another purchaser expects to report the same outcome. A more attractive project brochure solves none of these problems.
If the distinction between a value-chain intervention and a purchased credit is still open, read CCC’s Insetting vs Offsetting guide before you set the brief.
Insetting program design begins with the purchasing relationship and works outward. You need to decide 1) where an intervention belongs, 2) what business problem it addresses, 3) who pays for it, 4) how results will be measured, and 5) what the evidence will let you say about them. This five-step playbook turns that sequence into a procurement plan.
Step 1: Insetting program design starts with supplier mapping
Start with the commodities that matter most to your Scope 3 inventory and sourcing continuity. Ask finance for spend by supplier, sustainability for the emissions baseline, and category managers for origin and volume records. Then identify which suppliers can trace material to a jurisdiction, sourcing region, producer group, or individual land-management unit.
The level of traceability affects what you can account for. Under the GHG Protocol Land Sector and Removals Standard, the spatial boundary for purchased land-based products depends on the traceability associated with each volume. Farm-specific factors or removals require physical traceability through an acceptable chain-of-custody model. A contract with a tier-one trader, by itself, does not establish a link to the farms behind its deliveries.[1]
Build a first-pass table with five columns: commodity and annual volume; supplier and origin; current traceability level; land-use and production risks; and the business owner who can change the purchasing terms. Mark missing data plainly. A blank cell is cheaper to fix before a program starts than after a claim is drafted.
If your company sets an SBTi Forest, Land and Agriculture target (FLAG), keep its land-related target boundary separate from energy and industry emissions. The current FLAG guidance also requires relevant companies to assess primary deforestation-linked commodities in their value chains.[2]
Step 2: Choose a commodity and jurisdiction for a pilot
Select one supply corridor where the sourcing connection can be established and procurement has a reason to stay. A useful pilot has repeat purchases, suppliers willing to share records, an intervention matched to a diagnosed problem, and a defined plan to measure the result. Carbon potential alone is a poor selection rule if the supplier cannot deliver the crop your business needs.
Compare candidate regions on land-use risk, supplier concentration, local rights and tenure, the availability of baseline data, and exposure to drought, erosion, or forest conversion. Check the relevant legal requirements separately. A nature project does not satisfy a due-diligence obligation merely because it has a carbon method attached.
Consider a coffee buyer sourcing from two districts. In the first, producer-group records identify the farms, while recent dry seasons have increased rejected green coffee lots. In the second, deliveries pass through several intermediaries and farm origins are unknown. Pilot shade management in the first district, with local agronomic advice and quality checks built into the plan. The buyer can trace purchases there and test the intervention against a defined sourcing problem.
Use a short decision memo to record why the selected corridor beats the alternatives, what remains uncertain, and what would stop the pilot. That memo is the first control against a project drifting toward whatever happens to photograph well.
Step 3: Design the supplier engagement and commercial model
The intervention needs an owner on each side of the contract. Decide who supplies planting material or training, who maintains the practice, who bears the cost if a harvest disappoints, and how long the buyer expects to purchase from participating suppliers. Where smallholders participate, budget cash flow and technical support for practices that offer a later return.
Put these terms in a supplier agreement or pilot addendum. It should cover eligible farms and volumes, consent to data collection, access for monitoring, any land or carbon rights that matter, benefit sharing, and what happens if the purchasing relationship ends. Ask local counsel and producer representatives to review the arrangement. The Accountability Framework is a useful reference for supply-chain work involving forests, ecosystems, and human rights.[3]
Avoid assigning an automatic carbon benefit to the buyer. The contract should say which party has the right to report each outcome, how overlapping claims will be checked, and how any issued credits will be handled. A reduction reported in a buyer’s inventory cannot simply be sold for someone else’s offset claim without an accounting review. SBTi FLAG guidance excludes purchased credits used as offsets from near-term FLAG target achievement.[2]
Set commercial measures beside environmental ones: delivered volume, rejection rate, supplier retention, and procurement cost. They tell you whether the program works as a supply-chain investment, even if carbon accounting takes longer to resolve.
Step 4: Build monitoring, reporting, and verification before rollout
Agree on the baseline and data flow before paying for a full rollout. Identify the land units or sourcing regions in scope, the practices that change, the records suppliers already keep, and the additional measurements the program requires. Decide which data can come from field visits, transaction records, or remote sensing, and who checks each source.
For carbon, separate three questions. Did the practice happen? Did emissions or removals change under an applicable method? Can the buyer attribute a defensible share to its purchased goods without double counting? The GHG Protocol’s 2026 guidance includes dedicated chapters on spatial boundaries, data and methods, evaluating actions, credited outcomes, and assurance.[1] These are distinct jobs. A photograph of a planted tree answers only part of the first.
CCC’s MRV and Additionality article explains the separate evidence questions a project reviewer will ask.
Create an evidence file for every reporting period: dated supplier and farm records, purchase volumes, methods and emission factors, uncertainty, quality checks, and changes from the baseline. Specify who can challenge the data and how corrections are recorded. If a project also seeks credit certification, keep project accounting and corporate inventory accounting separate. The GHG Protocol says its land standard focuses on entity-level inventories and does not set the rules for credit certification.[4]
Start with the minimum viable measurement design that can survive review. Add complexity when the pilot tells you which data actually changes a decision.
Step 5: Decide what can be reported and claimed
Insetting program design needs reporting rules before the marketing copy. Procurement, sustainability, finance, and legal should agree on four distinct outputs: operational performance; observed land or nature outcomes; inventory effects, if the accounting criteria are met; and any separately issued credits. One dashboard can display them, but they should not share a single unqualified headline.
SBTi FLAG guidance allows certain land-based removals within a company’s operations or supply chain to contribute to FLAG pathways, subject to criteria including permanence, traceability, data quality, and allocation. It does not allow purchased offsets to meet near-term FLAG targets.[2] Eligibility therefore depends on evidence and the applicable target rules, not on calling an activity “insetting.”
Draft a claims register. For each proposed sentence, record the period, boundary, data owner, calculation method, reviewer, and whether the result is measured, estimated, or still a goal. If the evidence supports only “we funded a pilot with 200 farms,” say that. Do not turn a funding fact into a verified emissions reduction.
What good looks like by year three
Treat year three as a review point, not a promised payback date. A mature pilot should have mapped participating supply volumes, a stable supplier agreement, a repeatable data collection process, and a comparison of commercial and environmental results against the baseline. It should also have a documented answer for outcomes that cannot be included in the buyer’s inventory.
Scale only where the pilot improves a sourcing decision and the evidence can follow the product. If neither condition holds, redesign the intervention or change the corridor. A disciplined program can conclude that a site is unsuitable. That is useful procurement intelligence.
Discuss your insetting program with CCC
Carbon Credit Capital designs nature-based supply chain investments around sourcing needs and measurable sustainability outcomes. Schedule a consultation with our carbon and sustainability experts to map your tier-one supplier network, FLAG exposure, and first pilot decision.
Sources
[1] GHG Protocol, Land Sector and Removals Standard, version 1.1, and companion Guidance, June 2026: https://ghgprotocol.org/land-sector-and-removals-standard ; https://ghgprotocol.org/land-sector-and-removals-guidance
[2] Science Based Targets initiative, Forest, Land and Agriculture Science-Based Target-Setting Guidance, version 1.2, March 2026, especially pp. 16–17, 37, and 41: https://sciencebasedtargets.org/resources/files/SBTiFLAGGuidance.pdf
[3] Accountability Framework initiative, Accountability Framework and guidance for companies: https://accountability-framework.org/
[4] GHG Protocol, Frequently Asked Questions: Land Sector and Removals Standard, questions 10 and 18: https://ghgprotocol.org/blog/frequently-asked-questions-land-sector-and-removals-lsr-standard
Carbon Footprint
The Strategic Case for Nature-Based Carbon Investments
Nature-based carbon investments deserve consideration when they address a specific business dependency and produce outcomes you can measure. Imagine Moonbucks, a global coffee roaster planning next season’s espresso blend. It is considering natural Grade 4 coffee from Jimma, in southwestern Oromia, Ethiopia. Its sourcing decisions affect the roasting schedule and the cash tied up in coffee purchases. Moonbucks needs to understand which measures could protect that supply, what they would cost and how it would judge the results.
1. Define the sourcing problem before choosing a project
Moonbucks needs a dependable component for its espresso blend. Its procurement team wants continuity of volume and an agreed cup profile. Replacing a shipment at short notice could require new sample approval and changes to the blend, and given the schedules for cultivation, processing, and freight delivery, is practically impossible. Moonbucks needs to get this right, and its initial concern is inconsistent deliveries. It commissions an assessment of the supplying farms and post-harvest chain. The questions cover land condition, harvest availability and whether drying or storage problems are affecting saleable lots.
This distinction changes the investment brief. A tree-planting proposal cannot be assumed to fix drying problems. Better storage cannot restore eroded land. The team must establish which problem exists before selecting the response.
CCC’s guide to finding nature-based solutions in your supply chain explains where to look. Here, the next task is to turn a broad concern into a testable proposal.
2. Develop nature-based carbon investments around the actual supply chain
The assessment would trace Moonbucks’ purchases back through the exporter and supplying producer groups. Which farms supply the contracted lots? Who controls land-management decisions? How long does the buyer expect to maintain the purchasing relationship?
Furthermore, Jimma natural Grade 4 cannot be treated as interchangeable with every Ethiopian coffee. Moonbucks would need to test any substitute against its own blend and quality requirements.
Suppose Moonbucks’ assessment identifies an opportunity to maintain shade trees and restore vegetation along exposed streambanks. The IPCC describes agroforestry as a way to store carbon in vegetation and soil, with potential benefits for erosion control and water quality.1 Moonbucks would need local advice on species, growing conditions and maintenance before deciding how these measures fit its sourcing plan.
The proposal now has a defined sourcing connection and a candidate intervention. The next steps are to test its effect on production, assess carbon eligibility and build the financial case.
3. Compare the proposal with other ways to protect supply
WBCSD’s Nature-based Solutions Blueprint recommends comparing nature-based options with other responses across their benefits and costs.2 For Moonbucks, that means evaluating the landscape proposal alongside drying improvements, storage controls and alternative sourcing arrangements.
The product’s natural-process designation matters. Moonbucks should examine the drying and dry-milling chain alongside land conditions. Its team would check storage practices, contamination risks and incoming-lot quality to see whether problems arise before or after the coffee leaves the farms.
The revised proposal might combine land stewardship with separate post-harvest controls. Each component needs its own purpose and budget. A sustainability label should not obscure which activity is expected to solve which problem.
The project develops as the evidence improves. Its scope should follow the diagnosis rather than preserve the first idea unchanged.
4. Establish what the carbon outcome could count toward
Moonbucks’ sustainability team now tests the proposed carbon case separately from the sourcing case. Is the objective a measurable change in Moonbucks’ value-chain emissions, verified credits for separate voluntary use, or distinct outcomes under carefully defined arrangements?
Scope 3 covers value-chain emissions. A purchasing relationship alone does not prove that a farm intervention can be included in Moonbucks’ inventory. The team needs an applicable accounting method, defensible boundaries and evidence supporting attribution.
SBTi’s FLAG Guidance (forest, land and agriculture), version 1.2, says purchased credits used as offsets cannot meet near-term FLAG or energy and industry targets. Eligible land-based removals are subject to accounting requirements.3 Moonbucks needs to test its proposal against those rules before including an outcome in its targets.
For Moonbucks’ Jimma proposal, maintaining existing trees and establishing new vegetation could involve different carbon questions. Specialists must examine the baseline and additionality, meaning what changes because the project proceeds. They must also assess measurement and the risk that stored carbon is lost. CCC’s MRV and additionality article introduces those tests.
Until that work is complete, Moonbucks should not budget an assumed Scope 3 reduction or credit-sale receipt. Direct emissions reductions remain the priority.
5. Build a financial case that survives weaker assumptions
Moonbucks’ finance team would now build a multi-year budget. UNEP’s State of Finance for Nature 2023 compares current finance with the investment needed to meet climate, biodiversity and land-restoration goals.4 The company would cost its proposed activities, farmer participation and ongoing monitoring. Verification, where required, is a separate expense. Maintenance and responsibility for replacing failed plantings must remain visible after the initial establishment budget ends.
Operational benefits need equally careful treatment. If fewer rejected lots reduce emergency purchasing, count that saving once. Do not add “supply resilience” as another financial benefit when it represents the same avoided cost.
Moonbucks should compare a base case with slower benefits, higher implementation costs and no carbon revenue. It should also distinguish production outcomes from quality and shipment outcomes. A single good harvest would not prove that the landscape intervention caused better delivery performance.
A project can remain worth funding even when its carbon case needs more work. That decision must rest on the operational evidence and the company’s objectives, without unsupported environmental claims.
6. Fund a pilot with a clear expansion decision
Moonbucks’ first approval would fund a bounded pilot, rather than commit the entire sourcing program. Before spending, Moonbucks would agree on participating farms, responsibilities and the evidence needed at review.
Its scorecard could track farmer participation, implementation costs and plant survival, alongside accepted coffee volumes and lot-quality results. Carbon measurements would follow the selected method. Farm-level traceability must connect the intervention to the actual sourcing relationship.
Suppose Moonbucks’ review later finds that storage changes explain most quality improvements, while the land measures need longer observation. Those findings would shape the next decision: expand the proven component, adjust the landscape work or pause further spending. They would not justify crediting all improvements to tree planting.
This gives nature-based carbon investments a practical place in a multi-year strategy. Funding increases as the evidence supports it, and the project can change direction before a larger commitment.
Discuss a sourcing opportunity with CCC
Carbon Credit Capital’s nature-based supply-chain investment service uses its Dual-Value Model to examine supply-chain economics alongside potential sustainability outcomes.
Schedule a consultation to discuss your sourcing exposure and the questions to resolve before allocating capital.
Sources
- Intergovernmental Panel on Climate Change (IPCC), Climate Change 2022: Mitigation of Climate Change, Chapter 7, Agriculture, Forestry and Other Land Uses, section 7.4.3.3 (Agroforestry).
- World Business Council for Sustainable Development (WBCSD), Nature-based Solutions Blueprint, 5 June 2024.
- Science Based Targets initiative (SBTi), Forest, Land and Agriculture Science-Based Target-Setting Guidance, version 1.2, March 2026, section 3.1.4, pp. 37–38.
- United Nations Environment Programme (UNEP), State of Finance for Nature 2023, 2023.
Carbon Footprint
How to buy plastic credits, and what to check before you do
A plastic credit funds the collection of plastic waste in places where no formal system exists to collect it. Each credit represents a measured, independently audited quantity of plastic taken out of the environment or returned to use, tracked on a public registry.
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