feat(local-model): list every model that fits, and add Muse Glimmer 30B and Ornith 1.0 9B

docs/api-reference.md

@@ -1766,7 +1766,7 @@ A probe that fails is an answer, not an error: a server that is not on macOS, or
   - `verdict`: `ok`, `limited` or `none`. `limited` is a statement about the Mac: no model with 12 billion parameters or more fits its memory, so what it can run handles small edits and questions and does not replace a cloud model. It is judged on every model that fits, before the free disk space is looked at and whatever the pick is. With `ok` the pick can still be a small model (a larger one may be slow, have no speed figure or have no room on the disk); `notes` then says so.
   - `reason`, present only with `none`: `not-macos`, `intel`, `memory`, `disk`, `macos` (too old) or `no-harness` (no agent CLI that can be connected to a local model is installed or installable). `memory` has three sentences: nothing fits at all (slot `memory`, the size the Mac is sold as), a model fits but only below the context length an agent CLI needs (slots `budget` and `need`, so a Mac that misses by a little reads as that), and the memory size could not be read (no slot).
   - `headline` and `notes[]`: `{ text, vars? }`. `text` is an English sentence that may hold `{placeholder}` slots, and `vars` carries the slot values as text. Notes, in order: the pick is a small model although larger ones fit (verdict `ok` only); a model that fits the memory was left out because its download would not leave 10 GiB free on the disk (slots `model` and `missing`: the best-ranked such model and the GB to free up); nobody tested the pick on a Mac like this one.
-  - `pick` (absent with `none`) and `alternatives[]` (at most four, best first; empty with `none`), each one model at one context length with one agent CLI. The order: a pair tested on a Mac like this one first, then speed (`ok` before `unknown` before `slow`), then the model's rank, the agent CLI's rank and the larger context. The memory fit decides whether a row is listed and what it says (`fit`, `tag`), it does not sort, so a model is offered at the largest context it fits at. A model whose download would leave less than 10 GiB free on the disk is not listed (an unknown free disk space excludes nothing):
+  - `pick` (absent with `none`) and `alternatives[]` (every other model of the catalogue that fits, best first; empty with `none`), each one model at one context length with one agent CLI. An install is accepted only for a row of this list. The order: a pair tested on a Mac like this one first, then speed (`ok` before `unknown` before `slow`), then the model's rank, the agent CLI's rank and the larger context. The memory fit decides whether a row is listed and what it says (`fit`, `tag`), it does not sort, so a model is offered at the largest context it fits at. A model whose download would leave less than 10 GiB free on the disk is not listed (an unknown free disk space excludes nothing):
     - `modelId` (`name:tag`), `modelLabel`, `license`, `paramsB` (parameters in billions), `context` (tokens);
     - `cli`, `cliLabel`, `cliInstalled` (`false`: the CLI is not on this machine yet but can be installed without administrator rights), `slowFirstTurn?`;
     - `needBytes` and `needGb` (memory the model needs at that context, at its PEAK: the weights, what stays held per token of context, what the runner holds beside both, and what it takes for a moment while a long prompt is processed), `needSource` (`measured`: the figures were measured for this model on a Mac; `estimated`: they are another model's), `downloadBytes` and `downloadGb`, `budgetShare` (need divided by `budgetBytes`, rounded to three decimals);

src/local-model/recommend.ts

@@ -28,9 +28,10 @@
  *    gated, installed or installable, and accepting the model id.
  *  - Ranking, lexicographic: tested on a Mac like this before not tested (a measurement beats
  *    a formula); ok before unknown before slow; the higher model rank; the higher harness
- *    rank; the larger context. The pick is the first candidate, the alternatives are the next
- *    four MODELS, each at its own best context and harness, so a model is always offered at
- *    the largest context it fits at.
+ *    rank; the larger context. The pick is the first candidate, the alternatives are EVERY
+ *    other model that fits (`MAX_ALTERNATIVES` is above what the catalogue holds), each at its
+ *    own best context and harness, so a model is always offered at the largest context it
+ *    fits at.
  *  - Disk: a model whose download would leave less than 10 GiB free is not offered. It is not
  *    dropped in silence: the best-ranked model left out that way is named in `noteDiskDropped`
  *    with what is missing.
@@ -109,8 +110,13 @@ export const SLOW_BELOW_TOKENS_PER_SECOND = 10;
 export const LIMITED_BELOW_PARAMS_B = 12;
 /** What must stay free on the disk after the model download. */
 export const DISK_HEADROOM_BYTES = 10 * GIB;
-/** How many other models are listed under the pick. */
-export const MAX_ALTERNATIVES = 4;
+/**
+ * How many other models are listed under the pick, at most. Above what the stock catalogue
+ * holds (11 models: 10 beside the pick), so a Mac is shown every model that fits it and the
+ * install accepts every one of them. Still a bound: test/local-model-catalog.test.ts fails for
+ * a catalogue that outgrows it, so nothing drops out of the list unseen.
+ */
+export const MAX_ALTERNATIVES = 11;
 
 /** A memory size of at least this many GB (as sold) gets 3/4 of its memory as device limit, below it 2/3. */
 const LARGE_LIMIT_FROM_GB = 36;

src/types/local-model.ts

@@ -577,10 +577,10 @@ export interface Recommendation {
   /** Present exactly when `verdict` is `ok` or `limited`. */
   pick?: Candidate;
   /**
-   * The next models that fit and have room on the disk (at most four), best first: tested
-   * before not tested, then ok before unknown before slow speed, then the higher model rank.
-   * Each is at the largest context it fits at, with the best harness that can run it there.
-   * Empty when `verdict` is `none`.
+   * Every other model that fits and has room on the disk (`MAX_ALTERNATIVES` is above what the
+   * catalogue holds), best first: tested before not tested, then ok before unknown before
+   * slow speed, then the higher model rank. Each is at the largest context it fits at, with
+   * the best harness that can run it there. Empty when `verdict` is `none`.
    */
   alternatives: Candidate[];
   /** `DeviceBudget.budgetBytes`. 0 when no budget is computed: not macOS, or a Mac without Apple silicon. */