diff --git a/shared/homepage/app.js b/shared/homepage/app.js
index cfe54ad..95680fb 100644
--- a/shared/homepage/app.js
+++ b/shared/homepage/app.js
@@ -35,9 +35,10 @@ function esc(s) {
// them (the LLM cards), else the plain description string.
function descHTML(svc) {
const d = svc.details;
- if (d && (d.role || d.spec || d.inputs || d.use)) {
+ if (d && (d.role || d.spec || d.inputs || d.use || d.equiv)) {
const lines = [];
if (d.role) lines.push('
' + esc(d.role) + '
');
+ if (d.equiv) lines.push('' + esc(d.equiv) + '
');
if (d.spec) lines.push('' + esc(d.spec) + '
');
if (d.inputs && d.inputs.length) lines.push('Inputs: ' + esc(d.inputs.join(' · ')) + '
');
if (d.use) lines.push('Use: ' + esc(d.use) + '
');
diff --git a/shared/homepage/docs.html b/shared/homepage/docs.html
index ab14b3b..e3d093f 100644
--- a/shared/homepage/docs.html
+++ b/shared/homepage/docs.html
@@ -56,6 +56,7 @@
frank-large — deep reasoning
- Model: Qwen3.8-Flash-Next v2 Swift1.5 abliterated (halogen flash-server, ~62 GiB) — an uncensored edition that thinks before answering.
+ - Equivalent: Claude Sonnet 5 / OpenAI-Luna (Summer 2026 frontier intelligence).
- Capacity: 200k-token context, two conversations at a time; sees images.
- Inputs: text, image.
- Best for: cybersecurity and debugging. Use requires Frank's permission.
@@ -64,6 +65,7 @@
frank-primary — the primary model
- Model: Qwen3.8-Flash-Next at native FP8 precision (radiance, 173 GiB across both R9700s) — the biggest brain on the network.
+ - Equivalent: Claude Opus 4.8 / OpenAI-Terra (Summer 2026 frontier intelligence).
- Capacity: 200k-token context, two conversations at a time; sees images.
- Inputs: text, image.
- Best for: software engineering, system administration, and instruction tasks.
@@ -72,6 +74,7 @@
frank-secondary — the fast utility model
- Model: Qwen3.5-9B-Uncensored (Q6_K, 6.9 GiB) on the RTX 3090 — roughly 95 tokens per second.
+ - Equivalent: last year's frontier level (2025).
- Capacity: two simultaneous conversations, 200k tokens each; sees images.
- Inputs: text, image.
- Best for: agentic search, RAG, research subagents, translation, roleplay, and summarization — any small task that doesn't need much intelligence, and anything with a picture (screenshots, photos, diagrams). This is the model Open WebUI offers to family accounts.
diff --git a/shared/homepage/services.json b/shared/homepage/services.json
index 4a2ad89..8b42520 100644
--- a/shared/homepage/services.json
+++ b/shared/homepage/services.json
@@ -269,6 +269,7 @@
"section": "AI",
"details": {
"role": "Deep reasoning model",
+ "equiv": "Equivalent to Claude Sonnet 5 / OpenAI-Luna (Summer 2026 frontier intelligence).",
"spec": "Qwen3.8-Flash-Next v2 Swift1.5 abliterated (halogen flash-server, ~62 GiB) — 200k-token context, two conversations at a time; sees images. Speculative decoding always on.",
"inputs": ["text", "image"],
"use": "Cybersecurity and debugging. Requires Frank's permission."
@@ -286,6 +287,7 @@
"section": "AI",
"details": {
"role": "Primary model",
+ "equiv": "Equivalent to Claude Opus 4.8 / OpenAI-Terra (Summer 2026 frontier intelligence).",
"spec": "Qwen3.8-Flash-Next at native FP8 precision (radiance, 173 GiB) — 200k-token context, two conversations; sees images. Runs on both R9700s with tiered expert memory.",
"inputs": ["text", "image"],
"use": "Software engineering, system administration, and instruction tasks."
@@ -303,6 +305,7 @@
"section": "AI",
"details": {
"role": "Fast utility model",
+ "equiv": "Equivalent to last year's frontier level (2025).",
"spec": "Qwen3.5-9B-Uncensored (Q6_K, 6.9 GiB) on llama.cpp CUDA — two 200k-token conversations at a time; sees images; ~95 tok/s decode on the RTX 3090.",
"inputs": ["text", "image"],
"use": "Agentic search, RAG, research subagents, translation, roleplay, and summarization — any small task that doesn't need much intelligence."
diff --git a/shared/homepage/style.css b/shared/homepage/style.css
index ebe6f35..bc5c10d 100644
--- a/shared/homepage/style.css
+++ b/shared/homepage/style.css
@@ -81,6 +81,7 @@ body::before {
.desc { color: var(--fg); margin: 8px 0; }
.desc-role { color: var(--dim); font-weight: bold; }
.desc-spec { color: var(--fg); }
+.desc-equiv { color: var(--head); font-style: italic; }
.desc-inputs { color: var(--dim); }
.desc-use { color: var(--fg); margin-top: 4px; }
.links a { color: var(--link); text-decoration: underline; margin-right: 12px; }
@@ -118,6 +119,6 @@ html[data-bare="1"] body { background: #fff; color: #000; font-family: serif; te
html[data-bare="1"] body::before { display: none; }
html[data-bare="1"] .panel, html[data-bare="1"] .top, html[data-bare="1"] .foot { border-color: #000; background: none; }
html[data-bare="1"] .badge, html[data-bare="1"] .name, html[data-bare="1"] .desc, html[data-bare="1"] .summary, html[data-bare="1"] .section-title { color: #000; }
-html[data-bare="1"] .desc-role, html[data-bare="1"] .desc-spec, html[data-bare="1"] .desc-inputs, html[data-bare="1"] .desc-use { color: #000; font-weight: normal; }
+html[data-bare="1"] .desc-role, html[data-bare="1"] .desc-spec, html[data-bare="1"] .desc-inputs, html[data-bare="1"] .desc-use, html[data-bare="1"] .desc-equiv { color: #000; font-weight: normal; }
html[data-bare="1"] .section-title { border-color: #000; }
html[data-bare="1"] .links a, html[data-bare="1"] .toggle, html[data-bare="1"] .foot a { color: #000; }
diff --git a/tests/homepage_config.bats b/tests/homepage_config.bats
index 6cf3293..d38d156 100644
--- a/tests/homepage_config.bats
+++ b/tests/homepage_config.bats
@@ -77,3 +77,20 @@ assert by_probe.get("127.0.0.1:7770") == "frank-large", by_probe.get("127.0.0.1:
assert by_probe.get("127.0.0.1:7771") == "frank-secondary", by_probe.get("127.0.0.1:7771")
PY
}
+
+@test "every fleet LLM card carries a user-facing equivalence note" {
+ # Frank's capability framing (2026-10-08): each card must state, in plain
+ # terms, what the model is equivalent to — the cards' whole purpose for
+ # family users is "how smart is this and what is it for".
+ python3 - "$REPO_ROOT/shared/homepage/services.json" <<'PY'
+import json, sys
+services = json.load(open(sys.argv[1]))
+fleet = {s["name"]: s for s in services if s.get("name") in ("frank-large", "frank-primary", "frank-secondary")}
+assert len(fleet) == 3, sorted(fleet)
+for name, s in fleet.items():
+ eq = s.get("details", {}).get("equiv", "")
+ assert eq.strip(), f"{name} card has no equivalence note"
+PY
+ grep -q "desc-equiv" "$REPO_ROOT/shared/homepage/app.js"
+ grep -q "desc-equiv" "$REPO_ROOT/shared/homepage/style.css"
+}