models: apertus-70b is 262K context, not 65K — measured, not copied

The provider's published catalog says this model takes 30K input and has no
vision support. Both of those are wrong. Sent through our own gateway:

- an image returns the right answer ("Red" for a solid red PNG)
- prompts of 32K, 70K, 130K and 262K input tokens are all accepted, with
  Regolo's own usage accounting reporting prompt_tokens=262021

Our own description of the v1.5 generation — image understanding and a 262K
context window — matches what the model demonstrably does, which is why the
figure goes to 262K. The old 65K undersold the model by roughly 4x.

Regolo's meta-model for qwen3.5-122b says 120K; it processed 262,023 tokens and
still followed the instruction at the end, so that row's 262K is confirmed as
written and is left alone.

Adds a line under the table recording that context figures here are measured
through the gateway rather than copied from provider catalogs, because that
difference is exactly what caused a member to report this as an error.

models.md

@@ -82,13 +82,17 @@ The emoji in the model name marks its **value tier** (the same icons used in the
 | `🔒 tinfoil/gpt-oss-120b` | Tinfoil | architectural | undisclosed | — | 131K | $0.15 / $0.60 / — | Lightweight open-weight reasoning; cheapest private tier. |
 | `🌱 greenpt/glm-5.3-flash` | GreenPT | policy | ✅ 100% renewable | — | 1M | $0.11 / $0.44 / $0.022 | Fast GLM model, renewable energy. |
 | `🌱 greenpt/glm-5.3` | GreenPT | policy | ✅ 100% renewable | — | 1M | $1.10 / $4.40 / $0.275 | GLM flagship — strongest agentic model in the green tier. |
-| `🌱 regolo/apertus-70b` | Regolo | policy + ZDR | ✅ 100% renewable | ✅ | 65K | $0.46 / $2.44 / — | Fully open sovereign model (Apache-2.0), large/capable, image understanding. |
+| `🌱 regolo/apertus-70b` | Regolo | policy + ZDR | ✅ 100% renewable | ✅ | 262K | $0.46 / $2.44 / — | Fully open sovereign model (Apache-2.0), large/capable, image understanding. |
 | `🌱 regolo/qwen3.5-122b` | Regolo | policy + ZDR | ✅ 100% renewable | ✅ | 262K | $1.16 / $4.87 / — | Large vision+reasoning MoE (Qwen 3.5, 122B-A10B); 262K context. |
 
 Vision is verified working through the co-op gateway (base64 image input via
 `/v1/chat/completions`, standard OpenAI format). In the chat UI, just attach
 an image to your message while using a ✅ model.
 
+Context figures are measured the same way, through the gateway. Where a
+provider's public catalog advertises a smaller limit than the model actually
+accepts, the measured figure is the one shown here.
+
 **Reading the Privacy column:** *architectural* means the protection is built
 into the infrastructure (TEE enclaves) — even the provider can't read your
 prompts. *Policy* means the provider commits, by contract and policy, not to