SWE-Bench Multimodal on Vals: Opus 5.5 leads, internet access leaks answers

Vals AI evaluated 15 models on SWE-Bench Multimodal using mini-swe-agent with internet disabled. Opus 5.5 scored highest at 70.2%. Two findings matter beyond the ranking. First, cost per task did not track score, so the most expensive run was not the best one. Second, when Vals enabled web access, agents located the upstream fixes for benchmark issues and copied them, which inflates results without measuring any bug-fixing skill. That is a contamination route that does not depend on training data at all. Anyone running internal coding evals on public repositories should disable network access or check transcripts for fetched patches before trusting a score, and should report cost per task next to accuracy.