How it's built
Methodology & sourcing
One honest, coding-only composite — and a clear paper trail for every number.
Vibe Coding Index weights
Each suite is normalised to 0–100 and combined with the weights below. We weight agentic, real-repo work highest — that's what an AI coding harness does all day. When a model is missing a suite, we renormalise over the suites it does have instead of inventing a zero.
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SWE-bench Verified
40%
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Terminal-Bench
30%
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LiveCodeBench
30%
SWE-bench Verified
40%Real GitHub issues fixed end-to-end.
metric: resolved · scale 0–100
Terminal-Bench
30%Agentic tasks in a real shell.
metric: resolved · scale 0–100
LiveCodeBench
30%Fresh competitive-programming problems.
metric: pass@1 · scale 0–100
Data & citations
This dataset is verified. Every suite score links to its source (SWE-bench, LiveCodeBench, Aider, Terminal-Bench leaderboards), and model-level pricing/speed cite the vendor or Artificial Analysis. 42 suite figures currently carry a source link.
Anything we can't verify is left blank (—). We never fill a gap with a guess.
Where live data plugs in
The seeder reads a single verified file — .ovibe/knowledge/benchmark-data.json — verbatim, with per-figure source URLs. Swapping in a live benchmark-API feed means writing that same JSON on a schedule; no schema or UI changes. Suites, pricing, speed and latency all live in benchmark_models / benchmark_scores.
Primary sources
Snapshot: Jul 9, 2026Each suite is pulled from a single independent leaderboard where one exists; model-level pricing and throughput cite the vendor and Artificial Analysis. Where no independent run exists yet, the vendor's self-reported figure is used and flagged in the caveats below.
SWE-bench Verified
Real GitHub issues resolved end-to-end. Independent runs from the Epoch AI Benchmarking Hub; a few 2026 frontier models are vendor self-reported (via llm-stats.com) until Epoch reruns them.
Epoch AI Benchmarking Hub ↗Terminal-Bench
Agentic tasks in a real shell. Best public entry per model from the Terminal-Bench board. Note: 2.0 and 2.1 runs are mixed and are not directly comparable (2.0 scores higher).
tbench.ai leaderboard ↗LiveCodeBench
Fresh competitive-programming problems (pass@1), single independent harness.
vals.ai · LiveCodeBench ↗Pricing, speed & latency
Token pricing and context from each vendor own docs; output speed (tok/s) and time-to-first-token from Artificial Analysis.
Artificial Analysis ↗- · Terminal-Bench mixes 2.0 and 2.1 entries across models — read it as directional, not head-to-head.
- · Independent SWE-bench runs typically land 3–5 points below vendor self-reports; mixed provenance is noted per figure.
- · Anything we can't verify from a primary source stays blank (—). We never fill a gap with a guess.