Add image-model selection guide from the intelligence-radar digest

Maps the 2026-10-08 image-generation decision tree onto OpenRouter model IDs
with per-image quotes and caps for llm_connect.images, and documents the
anchor-win-rate scoring that makes Elo leaderboards usable for Topnotch.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

Assistant: claude-code
Assistant-Model: opus
Assistant-Process: 197486@bnt-lap001
Assistant-Session: 8e588643-5640-4ad7-9309-4ed3e12b2423

docs/image-model-selection.md

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+# Choosing an image model for `llm_connect.images`
+
+`llm_connect.images` has no default image model and does not choose one (see
+[`contracts/functional/images.md`](../contracts/functional/images.md)). This
+guide is advisory input for the caller. It does not change that contract.
+
+**Source:** intelligence-radar topic digest
+`digests/topics/2026-10-08-1527_Image_Generation_with_Generative_AI_Digest.md`
+(evidence observed 2026-10-08). Rankings and prices in this field change
+monthly. Re-derive the table from the digest's sources before relying on it
+after about 2026-11.
+
+## Picking a model
+
+All IDs below are OpenRouter model IDs. Prices are for one 1024² image. The
+quote is the per-image estimate plus some margin, and the cap leaves room for
+the provider-reported cost to come in above the quote.
+
+| Need | Model | ≈ $/img | `--quote-usd` | `--max-cost-usd` |
+|---|---|---|---|---|
+| Best result, cost secondary (Frontier) | `openai/gpt-image-2.5-sunburst` | 0.21 | 0.25 | 0.30 |
+| Same quality, faster | `openai/gpt-image-2.5-flare` | 0.21 | 0.25 | 0.30 |
+| Near-frontier at scale (Efficient) | `google/gemini-nano-banana-2.1` | 0.034 | 0.04 | 0.08 |
+| Efficient, better-evidenced fallback | `microsoft/mai-image-2.6` | 0.039 | 0.045 | 0.08 |
+| Routine imagery (Budget) | `meta/muse-image` | 0.010 | 0.012 | 0.03 |
+| Drafts, thumbnails, bulk variants | `recraft/recraft-v4.1-flash` | 0.007 | 0.008 | 0.02 |
+| Text-heavy (posters, infographics, CJK) | `openai/gpt-image-2.5-sunburst` | 0.21 | 0.25 | 0.30 |
+| Brand / consistent style set | `recraft/recraft-v4-styles` | 0.035 | 0.04 | 0.08 |
+| Vector-style output | `recraft/recraft-v4.1-vector` | 0.08 | 0.09 | 0.15 |
+
+Decision order:
+
+1. Need vector output, brand style, or heavy text? Take that row.
+2. Otherwise decide how much an excellent image is worth compared with a good
+   one:
+   - the image is the product → Frontier;
+   - many images, and quality matters → Efficient;
+   - illustrative or routine → Budget;
+   - exploration → bulk.
+3. For important assets, **explore cheap, then finish expensive**. Render 10–20
+   Budget variants, then re-render the chosen one or two with the Frontier
+   model. 20 × Muse plus 2 × Sunburst costs about the same as three Frontier
+   attempts. This is a hypothesis to test with quality-ledger rows, not a
+   measured result.
+
+Not available on OpenRouter, and therefore not reachable from this module:
+self-hostable open weights (Qwen-Image-2.1, FLUX.2 [dev]), Ideogram,
+Midjourney and Reve.
+
+## Scoring rule behind the classes
+
+Image leaderboards publish pairwise-preference **Elo**. Elo is an interval
+scale, so "within 10% of the best model" cannot be computed as a ratio of Elo
+values. The digest makes the scores usable as follows:
+
+```
+task_score(m) = P(m beats anchor) = 1 / (1 + 10^(-(Elo_m - Elo_anchor)/400))
+```
+
+Here the anchor is a fixed reference model. On the Artificial Analysis board
+that is FLUX.2 [dev], Elo 1000.
+
+- **Frontier:** the model with the highest `task_score`.
+- **Topnotch:** `task_score >= 0.90 × task_score(frontier)`. With the
+  Frontier at Elo 1198, this means Elo ≥ about 1133.
+- **Efficient:** the cheapest Topnotch model.
+- **Sufficient / Budget:** a per-task floor. For routine imagery the digest uses
+  a provisional floor of Elo ≳ 1100, the level of the frontier from about ten
+  months earlier. Budget is the cheapest model above that floor.
+
+Callers that already use `AdaptiveRoutingPolicy` quality floors can use the
+same mapping. Convert Elo to an anchor win rate first, then apply a ratio
+floor. Do not threshold raw Elo differences across leaderboards: the scales
+differ. Arena's top gap is about 95 points where Artificial Analysis shows
+about 40.
+
+## Caveats
+
+- OpenRouter bills most image models through a per-token rate. For Recraft,
+  Krea, Muse, Qwen, Seedream and FLUX 3, about 4,175 image tokens reproduces
+  the vendor's per-image price. For OpenAI and Google, cost depends on the
+  quality tier. Let the receipt's `cost_source=provider` correct the quotes
+  after the first runs.
+- It is not verified here that every listed model accepts OpenRouter's
+  `/images` endpoint with explicit `size` and `aspect_ratio=1:1`. Do one
+  capped single render per model before running a batch.
+- Nano Banana 2.1 had only a few thousand arena votes on 2026-10-08. If its
+  score drops, MAI-Image-2.6 becomes the Efficient pick.