docs: add upstream base model official evaluations

README.md

@@ -128,3 +128,27 @@ Source: <https://github.com/ailiance/ailiance/tree/main/output/lm-eval-base-2026
 Will include kicad-sch / iact-bench validators + W3 lm-eval delta. See spec for
 methodology:
 <https://github.com/ailiance/ailiance-bench/blob/main/docs/superpowers/specs/2026-05-11-kicad-sch-gap-design.md>
+
+## Upstream base model — official evaluations
+
+This LoRA fine-tunes [`mistralai/Devstral-Small-2-24B-Instruct-2512`](https://huggingface.co/mistralai/Devstral-Small-2-24B-Instruct-2512),
+Mistral's coding-specialist LLM. Headline software-engineering benchmarks
+from the upstream model card:
+
+| Benchmark                | Devstral Small 2 (24B) | Devstral 2 (123B) | DeepSeek v3.2 (671B) | Claude Sonnet 4.5 |
+|--------------------------|-----------------------:|------------------:|---------------------:|------------------:|
+| **SWE Bench Verified**   | **68.0 %**             | 72.2 %            | 73.1 %               | 77.2 %            |
+| **SWE Bench Multilingual** | **55.7 %**           | 61.3 %            | 70.2 %               | 68.0 %            |
+| **Terminal Bench 2**     | **22.5 %**             | 32.6 %            | 46.4 %               | 42.8 %            |
+
+(For reference, GPT-5.1 Codex High: 73.7 % SWE Verified · 52.8 % Terminal Bench 2.)
+
+Devstral Small 2 (24B) is competitive with much larger open models on
+SWE Bench Verified (e.g. matches GLM-4.6 at 355B). Architecture uses
+rope-scaling per Llama 4 + Scalable-Softmax ([arXiv:2501.19399](https://arxiv.org/abs/2501.19399)).
+
+**Source:** [official Devstral-Small-2-24B-Instruct-2512 model card](https://huggingface.co/mistralai/Devstral-Small-2-24B-Instruct-2512).
+
+> **Reading these alongside this LoRA:** Devstral Small 2 is a strong
+> coding base. This LoRA inherits its SWE-Bench performance and adds
+> language- or domain-specific specialization.