From e0732af1fdb1c23cfaa6157325e950f781149df2 Mon Sep 17 00:00:00 2001 From: Inferencebot Date: Thu, 29 Oct 2026 17:11:17 +0000 Subject: [PATCH] =?UTF-8?q?models:=20apertus-70b=20is=20262K=20context,=20?= =?UTF-8?q?not=2065K=20=E2=80=94=20measured,=20not=20copied?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 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 | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/models.md b/models.md index 05d73ab..6c4dbb8 100644 --- a/models.md +++ b/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