fix: match current provider model aliases to capability scores

[0xzr]

Summary

• normalize current Cloudflare, Hugging Face, and NVIDIA vendor-qualified model names
• ensure GLM-5.2, MiniMax M3, Kimi K2.6, and MiMo V2.5 Pro receive their benchmark capability scores instead of the neutral fallback
• cover each live catalog form with regression tests

Verification

• pytest -q tests/test_capability.py
• pytest -q

Summary by Sourcery

Align model name normalization with current provider-specific aliases so benchmark capabilities apply to the correct models.

Bug Fixes:

• Map current Cloudflare, Hugging Face, and NVIDIA vendor-qualified model names to their canonical benchmark model names so they receive non-fallback capability scores.

Enhancements:

• Extend vendor prefix normalization to cover additional provider namespaces such as cf-moonshotai, minimaxai, xiaomimimo, and z-ai.

Tests:

• Add parametrized regression tests to ensure live catalog model names normalize to the same form as their benchmark counterparts.

[sourcery-ai]

Reviewer's guide (collapsed on small PRs)

Reviewer's Guide

This PR extends model name normalization to recognize current provider-specific vendor aliases so that several Cloudflare, Hugging Face, and NVIDIA catalog entries correctly map to existing benchmark capability scores, and adds regression tests to lock in the normalization behavior.

File-Level Changes

Change	Details	Files
Extend vendor prefix stripping in model normalization to cover new provider-specific aliases so catalog names map to correct benchmark models.	Update the vendor prefix regular expression to include cf-moonshotai, minimaxai, xiaomimimo, and z-ai as recognized vendor prefixes Ensure normalized names for GLM-5.2, MiniMax M3, Kimi K2.6, and MiMo V2.5 Pro align with their benchmark identifiers instead of falling back to neutral scoring	src/freellmpool/capability.py
Add regression tests to verify normalization of current provider catalog names to benchmark model names.	Introduce a parametrized test that exercises Cloudflare, Hugging Face, and NVIDIA catalog model identifiers and their intended benchmark equivalents Validate that normalize_model_name returns identical normalized names for each catalog/benchmark pair, preventing future regressions in capability scoring	tests/test_capability.py

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[sourcery-ai]

Hey - I've left some high level feedback:

• The growing alternation list in _VENDOR_PREFIX_RE is becoming harder to maintain; consider defining vendor/alias prefixes in a data structure (e.g., a list or mapping) and generating the regex from it so new providers/aliases can be added in a single place.

Prompt for AI Agents

Please address the comments from this code review:

## Overall Comments
- The growing alternation list in `_VENDOR_PREFIX_RE` is becoming harder to maintain; consider defining vendor/alias prefixes in a data structure (e.g., a list or mapping) and generating the regex from it so new providers/aliases can be added in a single place.

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