Comparison — updated 14 July 2026
Two labs, two bets
OpenAI or Anthropic? The history, philosophy, API platforms, ecosystems and business models of both labs, compared by a partner of each.
In brief
OpenAI and Anthropic are not two versions of the same product: they are two theses about what AI ought to be. OpenAI aims for the widest possible reach, with a consumer ecosystem and a deep alliance with Microsoft. Anthropic builds first for the enterprise and for engineering, with safety as a design argument and open standards such as MCP. This choice commits you well beyond a single product.
OpenAI vs Anthropic: two visions of enterprise AI
Comparing ChatGPT and Claude means comparing two products. Comparing OpenAI and Anthropic means comparing two companies, two trajectories and two bets on the future of AI — a different exercise, and often a more useful one when you are about to commit an organisation for several years. A platform can be swapped in six months; a strategic dependency unwinds far more slowly.
This page therefore does not replay the duel of the assistants: we covered that elsewhere, in our ChatGPT versus Claude comparison. It looks instead at the two labs themselves: where they come from, what they believe, what they build for developers, whom they are allied with, and how they make a living. Hunter BI belongs to both partner networks: we take no side, but we do hold one conviction — companies that choose an AI provider without understanding its thesis wake up, two years later, with an architecture that was never theirs.
OpenAI and Anthropic: two origins, one family
The two labs share a root. Anthropic was founded in 2021 by former OpenAI executives and researchers, including Dario and Daniela Amodei, around a fundamental disagreement over how to develop powerful AI systems — a disagreement about method and pace more than about the goal. This lineage explains a great deal: the two houses share a vocabulary, research standards and the same conviction about the trajectory of capabilities.
OpenAI, founded in 2015, has followed one of the fastest trajectories in the history of software: from a research lab to a platform used worldwide after the launch of ChatGPT in late 2022. Its structure — a capped-profit entity placed under a non-profit organisation, since reworked — reflects that permanent tension between mission and scale.
Anthropic made a different choice: a public benefit corporation, governance fitted with a mechanism dedicated to the public interest, and a much later and much quieter entry into the consumer market. Where OpenAI won over the general public and then the enterprise, Anthropic won over developers and the enterprise, and only then the general public. That reversal of order can still be read in their products.
Two philosophies: mass diffusion against safety by design
OpenAI owns a thesis of diffusion: put powerful capabilities into as many hands as possible, as fast as possible, correcting along the way. This produces a catalogue of remarkable breadth — text, image, voice, video, agents, web search —, integration into everyday tools, and a launch cadence that unsettles its competitors. The underlying bet: safety is learned through contact with the real world, and legitimacy comes from usage.
Anthropic owns a thesis of safety by design. Its public research on interpretability and alignment is not a communications extra: it feeds the design of the models, notably through the "constitution" that frames their behaviour, and a responsible scaling policy that conditions deployments on assessed risk thresholds. The underlying bet: the trust of enterprises and regulators will be the decisive factor, and it is built before the incident, not after.
These two theses are not marketing postures: they produce observable differences. They explain the pace of feature additions at one, the editorial caution and traceability at the other, and even the tone of the models. For a company, the question is not who is right — both approaches have merit — but which of the two resonates with your sector, your regulators and your risk tolerance.
The API platforms: what each offers developers
On the fundamentals, parity is real: official SDKs in the common languages, tool calls, structured outputs, batch processing at a reduced price, caching of repeated contexts, logging. An engineer moves from one to the other in a day. The differences lie in the architectural philosophy.
OpenAI builds an integrated platform: an API that exposes not only models but ready-made building blocks — web search, code execution, interpreter, agents, image and voice generation — designed so that a developer can quickly assemble a complete product without leaving the ecosystem. It is powerful and it is sticky: the more building blocks you consume, the more migration costs.
Anthropic pushes an open-standard logic. The Model Context Protocol (MCP), which it published and which has taken hold well beyond its own perimeter — competing tools now implement it —, separates the model from its connections to enterprise systems. You write an MCP server once, and it serves several models. It is an architectural choice that reduces stickiness, and for an IT department it is a serious argument: reversibility is no longer an intention, it is built into the structure of the code.
Ecosystems and alliances: Microsoft on one side, AWS and Google on the other
The cloud alliances are one of the most defining facts in the file, and often the first to decide matters in practice. OpenAI has historically been backed by Microsoft: its models are served through Azure, integrated into Microsoft 365 Copilot and into Microsoft's development tooling. For an organisation already committed to Microsoft — which is to say a large share of Moroccan and European companies — this simplifies contracting, billing and data residency. It is a considerable practical advantage.
Anthropic is backed by Amazon and Google: Claude is served through AWS Bedrock and Google Vertex AI, and both giants have invested heavily in the company. For a company whose foundation is AWS or Google Cloud, consuming Claude through the existing cloud avoids a new provider, a new contract, a new security review.
The strategic consequence is clear: for many organisations, the OpenAI-or-Anthropic choice is partly decided upstream by the choice of cloud, and it is reasonable that it should be so. But beware the false obviousness: consuming a model through your usual cloud simplifies the purchase, not the architecture. The real subject remains the abstraction layer you place on top — the one that will let you, eighteen months from now, change your mind without rewriting your applications.
Business models and solidity: what does committing to one or the other mean?
The two companies live off the same thing: consumer and professional subscriptions, and API consumption billed by the token. The proportions differ. OpenAI draws a significant share of its revenue from the general public and from large-scale professional offerings; Anthropic, structurally more oriented towards the enterprise and developers, earns a higher share of its turnover from the API and enterprise offerings. Neither publishes detailed accounts: be wary of the figures circulating in the press, they are rarely sourced.
What this changes for you, concretely: nothing about immediate solidity — both are massively funded, by Microsoft on one side, by Amazon and Google on the other — but something about product priorities. A company whose revenue comes first from developers and enterprises arbitrates its roadmaps accordingly: API stability, deprecations announced long in advance, documentation of behavioural changes. A company oriented towards the general public sometimes shifts its priorities towards features that will never serve you.
The question to ask your account manager, at one as at the other: what is your model-deprecation policy, and what contractual notice do you have on a behavioural change in production? The answer to that question will teach you more than a table of benchmarks.
What this choice changes for your strategy — and why reversibility comes first
Let us sum up what really decides matters. If your foundation is Microsoft, if you want the broadest palette of capabilities and the most spontaneous adoption, OpenAI is the shortest path. If your foundation is AWS or Google Cloud, if your use cases revolve around code, long documents and connection to your internal systems, if traceability and security posture are arguments before your regulator, Anthropic is a natural choice.
But the essential lies elsewhere, and this is our message to architecture committees: the single-vendor question is badly framed. The organisations we see age well are those that have treated models as replaceable components — an internal abstraction layer, evaluations replayable on their own data, connections to internal systems built on an open protocol. They can then change model in a quarter, arbitrate task by task, and negotiate from a position of strength.
Those that built on the proprietary building blocks of a single ecosystem, for lack of time or out of comfort, discover at renewal that the exit cost has become their main selling point — their provider's, that is. The OpenAI-or-Anthropic choice matters; the architecture that lets you change it matters more.
| Critère | OpenAI | Anthropic |
|---|---|---|
| Founding | 2015, San Francisco — research lab turned consumer platform | 2021, San Francisco — founded by OpenAI alumni, including Dario and Daniela Amodei |
| Structure | For-profit entity under the oversight of a non-profit organisation | Public benefit corporation, dedicated governance |
| Dominant thesis | The widest possible diffusion, correcting along the way | Safety by design, the trust of enterprises and regulators |
| Market entry | General public first (ChatGPT), then the enterprise | Developers and the enterprise first, then the general public |
| Cloud alliances | Microsoft — API served through Azure, Microsoft 365 integration | Amazon and Google — API served through AWS Bedrock and Google Vertex AI |
| Platform philosophy | Integrated platform: ready-made building blocks, strong stickiness | Open standard: MCP separates the model from its connections to the IT estate |
| Catalogue | Text, image, voice, video, agents, web search, Codex | Text and vision, Claude Code, Projects, artefacts, MCP |
| Argument before the regulator | Scale, certifications, enterprise confidentiality commitments | Public research on alignment, responsible scaling policy |
When to choose OpenAI or Anthropic?
Choose OpenAI if:
- Your foundation is Microsoft and you want to contract through Azure
- You are after the broadest palette of capabilities: image, voice, agents, web search
- Spontaneous adoption matters: your staff already know ChatGPT
- You assemble a product quickly with ready-made building blocks
Choose Anthropic if:
- Your foundation is AWS or Google Cloud: Bedrock and Vertex AI serve Claude natively
- Your use cases are code, long documents and connection to internal systems
- You want to build your connections on an open protocol (MCP) to stay reversible
- Your sector is regulated and security posture is an argument before the authority
In summary
Our verdict
OpenAI and Anthropic are not separated by quality — it is comparable, and the ranking flips depending on the task — but by thesis. OpenAI is the bet on diffusion and integration: the broadest platform, the shortest path if your foundation is Microsoft. Anthropic is the bet on trust and architectural openness: the natural choice if your uses are technical and document-heavy, if you are on AWS or Google Cloud, or if your regulator is looking over your shoulder. Our recommendation, as a partner of both: choose the one whose thesis resonates with yours, but never build your architecture as if that choice were final. An abstraction layer, evaluations replayable on your data, connections over an open protocol — it is this triptych, and not the name of the provider, that will protect you three years from now.
Frequently asked
What is the difference between OpenAI and Anthropic?
They are two AI labs with opposing theses. OpenAI, founded in 2015, aims for the widest diffusion: a very broad catalogue, consumer grounding, an alliance with Microsoft. Anthropic, founded in 2021 by OpenAI alumni, builds first for the enterprise and developers, with safety as a design principle and open standards such as MCP, backed by AWS and Google Cloud.
Was Anthropic founded by former OpenAI employees?
Yes. Anthropic was created in 2021 by former OpenAI executives and researchers, including Dario Amodei, a former vice-president of research, and Daniela Amodei. The disagreement was about the method and pace of developing powerful AI systems, not about the goal — which explains the technical and cultural closeness of the two houses.
Should you choose OpenAI or Anthropic for your enterprise API?
The cloud foundation often decides: OpenAI contracts naturally through Microsoft Azure, Anthropic through AWS Bedrock or Google Vertex AI. Beyond that, OpenAI offers more ready-made building blocks, Anthropic a more open architecture thanks to MCP. In both cases, isolate the provider behind an abstraction layer and evaluate both APIs on your real use cases.
Can you work with both at the same time?
Yes, and it is common among our mid-sized and large clients: each population on the platform where it is most productive, reduced dependency, a strengthened negotiating position. The extra cost is real but often lower than the productivity gain, provided you maintain unified governance across both platforms.
Which of the two companies is financially the stronger?
Both are massively funded — OpenAI by Microsoft, Anthropic by Amazon and Google — and neither publishes detailed accounts: the figures circulating in the press are rarely sourced. The useful question for an IT department is not solidity but the model-deprecation policy and the contractual notice in the event of a behavioural change in production.
Sources
- OpenAI — about and charter — accessed July 2026
- Anthropic — company and approach to safety — accessed July 2026
- Model Context Protocol (MCP) documentation — accessed July 2026
- Claude models on Amazon Bedrock — aws.amazon.com — accessed July 2026
Need an independent view?
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