Anthropic, OpenAI, or Cursor model for your agent skills? 7 learnings from running 880 evals (including Opus 4.7)
Claude Opus 4.7 shipped last week, and the question any engineering team reaches for is how it compares to its peers. It is the strongest frontier coding model we tested on the baseline leaderboard, and it will be the easy default a lot of teams reach for. But in 2026, the model you reach for could matter less than the skill you load with it. That is what 880 evals across nine models (Opus 4.7, Opus 4.6, Sonnet 4.6, Haiku 4.5, gpt-5.4, gpt-5.3-codex, gpt-5-codex, and Cursor's Composer-2) tell us. Let’s take a step back. It’s now 2026, and agent skills are spreading like wildfire… (even our favourite movies are catching up to them). Watch on YouTube Every major agent ecosystem now has some version of them. So the question worth asking, whether you are a dev, a platform engineer, or an engineering leader, is which skills actually earn their context weight, and which ones just add cost. At Tessl, we believe context -particularly agent skills- and the broader concept of a context development lifecycle are where this space is heading (see also: Why the best AI coding teams will win on context ). The results below add to a growing body of signals pointing to a shift that is already underway. Top-line results Model Native behavior rate coverage (e.g "without skill") Adherence to skill ("with skill") Lift $/run (with skill) Avg time (with skill) claude-opus-4-7 80.5% 94.5% +14.0 $1.00 158.9s claude-opus-4-6 77.1% 93.8% +16.7 $0.53 126.6s claude-sonnet-4-6 75.6% 93.3% +17.7 $0.31 125.1s claude-haiku-4-5 61.2% 84.3% +23.1 $0.12 77.8s gpt-5.4 75.9% 92.7% +16.8 N/A* 135.4s gpt-5.3-codex 75.8% 91.9% +16.1 N/A* 87.9s gpt-5-codex 73.8% 85.1% +11.3 N/A* 136.2s cursor-composer-2 73.6% 90.5% +16.9 N/A* 152.0s We’ve evaluated 11 node.js development skills ( documentation, fastify-best-practices, init, linting-neostandard-eslint9, node-best-practices, nodejs-core, oauth, octocat, skill-optimizer, snipgrapher, typescript-magician ) , and aggregated “with vs without” skill performance. F