Candidate bench
Repo: https://github.com/LeviTheWeasel/rp-benchmark
Owner: LeviTheWeasel (GitHub); community-calibrated arena at arena.l3vi4th4n.ai
Exact data URL: https://raw.githubusercontent.com/LeviTheWeasel/rp-benchmark/main/results/composite_leaderboard.json
What it measures
Roleplay quality in LLMs across 27 dimensions: character consistency, user agency (does the model write your character for you?), lorebook integration, prose quality, genre-specific skills, and more. Scores are a weighted composite of five evaluation methods — a human-voted ELO arena (1,857 pairwise votes), multi-turn Bayesian arena (1,262 votes), an LLM judge rubric, flaw detection, and behavioral flags.
It's asking something nobody else is asking at scale: does this model make a good RP partner?
Data-reality check — CONFIRMED
- Fetched
composite_leaderboard.json on 2026-07-20: 200 OK, valid JSON
- 21 models in the leaderboard array with
composite_score, rank, and per-dimension subscores
- Current frontier models present:
claude_opus_4_6, claude_opus_4_7, claude_sonnet_4_5, gpt_4_1, gpt_5_5, gemini_3_1_pro, deepseek_v4_pro, kimi_k2_6
- Latest commit to this file: 2026-06-04 ("feat: ingest 644 new multi-turn votes from Plotpoints Supabase")
- Direction: higher-better (composite_score, 0–100 scale; top entry
claude_opus_4_6 scored 97.6)
Why it fits BenchDirectory
- Personal/indie: single GitHub user, not a company or academic lab
- Novel, opinionated question ("AI benchmarks from curious people")
- Community-backed (human votes in the arena) — real signal, not just LLM-judge
- 21 models on the board with a real composite scoring methodology
- Machine-readable data confirmed current as of June 2026
Notes for adapter
- JSON structure:
{ weights: {...}, n_models: 21, leaderboard: [{rank, model, composite_score, ...}] }
- Primary score:
composite_score (higher-better, roughly 0–100)
scoreLabel: "Composite score" — scoreExplainer: "Weighted composite of human arena votes, LLM judge rubric, flaw detection, and behavioral flags — higher means a better roleplay partner."
- Worth exposing sub-scores (arena_elo, judge_score) as
extras
- Throw if fewer than 5 entries parse
Candidate bench
Repo: https://github.com/LeviTheWeasel/rp-benchmark
Owner: LeviTheWeasel (GitHub); community-calibrated arena at arena.l3vi4th4n.ai
Exact data URL:
https://raw.githubusercontent.com/LeviTheWeasel/rp-benchmark/main/results/composite_leaderboard.jsonWhat it measures
Roleplay quality in LLMs across 27 dimensions: character consistency, user agency (does the model write your character for you?), lorebook integration, prose quality, genre-specific skills, and more. Scores are a weighted composite of five evaluation methods — a human-voted ELO arena (1,857 pairwise votes), multi-turn Bayesian arena (1,262 votes), an LLM judge rubric, flaw detection, and behavioral flags.
It's asking something nobody else is asking at scale: does this model make a good RP partner?
Data-reality check — CONFIRMED
composite_leaderboard.jsonon 2026-07-20: 200 OK, valid JSONcomposite_score,rank, and per-dimension subscoresclaude_opus_4_6,claude_opus_4_7,claude_sonnet_4_5,gpt_4_1,gpt_5_5,gemini_3_1_pro,deepseek_v4_pro,kimi_k2_6claude_opus_4_6scored 97.6)Why it fits BenchDirectory
Notes for adapter
{ weights: {...}, n_models: 21, leaderboard: [{rank, model, composite_score, ...}] }composite_score(higher-better, roughly 0–100)scoreLabel: "Composite score" —scoreExplainer: "Weighted composite of human arena votes, LLM judge rubric, flaw detection, and behavioral flags — higher means a better roleplay partner."extras