mager-bench
v1.1 // 13-challenge personal coding benchOpinionated coding tasks, scored by an LLM judge on correctness, code quality, and documentation. Free-tier models run free. Paid models get crowdfunded.
- avg latency
- 8580ms
- challenges
- 13
- judge
- claude-sonnet-5
- last run
- Sun, 26 Jul 2026 14:21:14 UTC
leaderboard
| # | model | cost | crct · qual · docs | avg score | avg latency | n |
|---|---|---|---|---|---|---|
| 01 | GPT-OSS 120B→ | free | 5.8 · 6.5 · 6.7 | 6.4 | 8580ms | 13 |
| 02 | Claude Sonnet 4.6→ | paid | 5.9 · 5.9 · 6.6 | 6.2 | 33426ms | 13 |
| 03 | Claude Haiku 4.5→ | cheap | 6.2 · 6.2 · 6.4 | 6.2 | 13326ms | 13 |
| 04 | Llama 3.3 70B→ | free | 5.3 · 5.5 · 5.8 | 5.6 | 2244ms | 13 |
| 05 | Gemini 2.5 Flash→ | free | 4.8 · 5.0 · 5.7 | 5.2 | 26981ms | 13 |
crct · qual · docs are the rubric dimensions averaged across all 13 challenges — the headline average hides whether a model is correct-but-undocumented or well-written-but-wrong.
click a model for its full challenge breakdown, raw responses, and judge notes. free + cheap run by default; paid models land when crowdfunded.
the 13 challenges
full specs + rubrics →Classic FizzBuzz — tests basic correctness and code style
Binary search implementation with full docs
Write a small HTTP API client class with error handling and docs
Write a README for a CLI tool — tests documentation ability directly
Refactor messy code and explain each change
Write pytest tests for a provided function — tests edge-case thinking and assertion quality
Find and fix 3 bugs in broken Python code — tests careful reading and correctness reasoning
Write async Python for concurrent HTTP fetching with timeout and retry
Write a complex SQL query with CTEs, window functions, and aggregations
Write idiomatic Go table-driven tests — tests knowledge of Go testing conventions
Write idiomatic Elixir ExUnit tests — tests knowledge of Elixir testing conventions
Build a Doom-style raycasting FPS engine in a single HTML file — the mager-bench signature challenge
Build a Vegas-style slot machine in a single HTML file — reels, pay table, betting, wins
score shown is the board average across all 5 scored models — a rough difficulty read. every model attempts every challenge.
fund the bench
10 paid models still waiting. Free tiers (Groq / Gemini) never need a card — crowdfunding buys the expensive head-to-heads.
$0 / $100 season goal · 0%
not scored yet
- Claude Opus 4.8unfunded~$8 / full suite
- Claude Sonnet 5unfunded~$4 / full suite
- GPT-4ounfunded~$5 / full suite
- Gemini 2.5 Prounfunded~$4 / full suite
- GPT-5.6unfunded~$6 / full suite
- Claude Fable 5unfunded~$10 / full suite
- Claude Opus 4.6unfunded~$7 / full suite
- Claude Opus 4.7unfunded~$8 / full suite
- GLM 2.5unfunded~$2 / full suite
- Kimi K3unfunded~$2 / full suite
methodology, honestly
Every score comes from a single LLM judge — currently claude-sonnet-5 — pinned across all runs so scores stay comparable. That judge is a Claude model scoring a board that includes Claude models: same-family bias is real, so treat cross-family gaps as directional, not gospel. Thinking and verdict budgets are separate contracts in the harness, and every score links to its raw response and judge notes so you can audit the reasoning instead of trusting the number.
api
$ curl /api/results → 200 OK
Same data behind this page, as JSON. Cached 1h at the edge.