Add PublicAI Apertus models + sovereignty/open-source notes
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@@ -16,17 +16,20 @@ provider today is best on both.
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| **Tinfoil** | *private* | **Strongest — architectural** | Not a green claim | Runs in hardware enclaves (TEEs) with end-to-end encryption (EHBP), verifiable via remote attestation. Neither we nor Tinfoil can read your prompts or responses at inference time. Energy mix is not disclosed. |
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| **GreenPT** | *green* | **Policy-based** | **Strongest — 100% renewable** | Standard (non-enclave) hosting in the EU; privacy rests on GreenPT's commitments and EU data rules, not on cryptography. Compute runs on 100% renewable energy. |
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| **PublicAI** | *public* | (to be confirmed) | (to be confirmed) | Coming soon — publicly developed models. Details pending. |
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| **PublicAI** | *public* | Policy-based | Undisclosed | A gateway for **publicly developed, sovereign models** — open-weight models built by national/public programs rather than private labs. Privacy is policy-based (no enclave); energy mix is not disclosed. |
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**Reading the gradations:**
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- **Privacy:** *architectural* (Tinfoil) beats *policy-based* (GreenPT). An
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- **Privacy:** *architectural* (Tinfoil) beats *policy-based* (GreenPT, PublicAI). An
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enclave protects you even if the provider is compromised; a policy protects
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you only as far as the provider keeps its word. Both are better than a
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provider with neither.
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- **Green energy:** *100% renewable* (GreenPT) beats *undisclosed* (Tinfoil).
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GreenPT reports its energy mix; Tinfoil does not, so we can't claim greenness
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for it — it may or may not be renewable.
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- **Green energy:** *100% renewable* (GreenPT) beats *undisclosed* (Tinfoil,
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PublicAI). GreenPT reports its energy mix; the others do not, so we can't
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claim greenness for them.
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- **Sovereignty:** *publicly developed* (PublicAI) is its own value — the models
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come from public/national AI programs, built as public goods rather than
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proprietary products. It's a third axis, independent of privacy and energy.
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Trade-offs are real: the most private option (Tinfoil) isn't the greenest, and
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the greenest option (GreenPT) isn't the most private. The point of the co-op is
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@@ -45,6 +48,34 @@ provider — your own cost is your monthly allowance, not per-token billing).
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| `greenpt/green-r` | GreenPT | policy | 100% renewable | $0.35 / $0.95 | Reasoning, renewable energy. |
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| `greenpt/green-l` | GreenPT | policy | 100% renewable | $0.25 / $0.80 | Lightweight, renewable energy. |
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| `greenpt/glm-5.3-flash` | GreenPT | policy | 100% renewable | $0.11 / $0.44 | Fast GLM model, renewable energy. |
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| `publicai/apertus-v1.5-8b` | PublicAI | policy | undisclosed | $0.10 / $0.20 | Fully open sovereign model, small/fast. |
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| `publicai/apertus-v1.5-70b` | PublicAI | policy | undisclosed | $0.82 / $2.92 | Fully open sovereign model, large/capable. |
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### About the Apertus models
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Apertus is the **Swiss AI Initiative's** open foundation model, built by a
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public collaboration between **EPFL, ETH Zurich, and the Swiss National
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Supercomputing Centre (CSCS)**. It's "fully open" in the strict sense — not just
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downloadable weights:
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- **Open weights & code** — released under the **Apache-2.0** license, so anyone
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can use, modify, and redistribute it, commercially or not.
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- **Open training data** — trained only on *fully open* data (unlike most
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proprietary models, which keep their training set secret). The data, code,
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methods, and alignment principles are all published and reproducible.
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- **Open values** — governed by a public **Apertus Charter** that documents the
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model's values and principles rather than leaving them implicit.
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- **Sovereign & public-good** — designed to European data-protection norms
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(GDPR, EU AI Act, Swiss law) as an example of "AI as a public good," not a
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proprietary product. Trained across 1,500+ languages (40% non-English).
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The v1.5 generation adds image understanding, a longer 262K-token context
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window, improved tool use, and instruction-following. It's the *publicly
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developed* counterpart to the private (Tinfoil) and renewable (GreenPT)
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offerings — sovereignty as a third axis of member choice.
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*Source: [apertus-ai.org](https://www.apertus-ai.org/) and the
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[Swiss AI Hugging Face](https://huggingface.co/swiss-ai) model cards.*
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Some models also have a discounted cached-input rate (when a prompt is reused
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and doesn't need to be re-read) — see the `code/litellm` config for the exact
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