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LFM2.5-24B-A2B in the Gauntlet
Mac Studio M5 Ultra 256 GB · TensorFold 1.2.5 (official release), Ash's recipe (Liquid AI LFM2.5-24B-A2B, MLX 4-bit)
What happened on the course
Each range is one task with one answer and no retry. Every wrong or missing target is a miss and costs a penalty loop. The race time is thinking, running, shooting and loops together.
| # | Task | Targets | Hits | Thinking | Buzzer | Penalty loops | Range time |
|---|---|---|---|---|---|---|---|
| 1 | River ferry (puzzle, level 1) | ✕✕✕✕✕ | 0 / 5 | 17.9 s | no | 5 (60.0 s) | 85.1 s |
| 2 | Painter (code, level 2) | ✕✕✕✕✕ | 0 / 5 | 0.6 s | no | 5 (60.0 s) | 67.8 s |
| 3 | Bench seating (puzzle, level 3) | ✕✕✕✕✕ unusable answer | 0 / 5 | 14.0 s | no | 5 (75.0 s) | 96.2 s |
| 4 | Snake (code, level 4) | ✕✕✕✕✕ | 0 / 5 | 4.6 s | no | 5 (75.0 s) | 86.8 s |
● hit, ✕ miss. The range time runs from arriving at the mat to leaving the range, loops included. A buzzer means the thinking cap ran out and the game forced the answer.
Every number has its file
Result (result.json) Race log (log.jsonl) Model answers (io.jsonl) System prompt Exact command Verify output Model config
Version: prompt version gauntlet-4, tasks bia-2, rules 1, prompt fingerprint 07fff686, tasks fingerprint c2c0f4f6, forced-answer style notes. Verified: the replay of the race log reproduces the end state and every code answer re-runs to the same verdict. Forced-answer style: how the game asks for the answer when the buzzer sounds (a prefilled answer start, or notes when the engine refuses that). Command and config are normalized: internal addresses appear as 127.0.0.1.
- According to its maker's model card, LFM2.5-24B-A2B is made for agent and tool-call tasks and is not recommended for knowledge-heavy tasks alone. This game test does not measure that strength.
Who made what
- Recipe (docs/recipes/lfm2.5-24b-a2b.md, main) and engine (TensorFold 1.2.5, official release archive for macOS arm64)Ash HartX @ashxhartGitHubHugging FaceWebsite
- Model (LFM2.5-24B-A2B)Liquid AIX @liquidaiHugging FaceGitHubWebsite
- Model files (MLX 4-bit export, revision 667408d4)Liquid AIX @liquidaiHugging FaceGitHubWebsite
- Engine (TensorFold 1.2.5, official release archive for macOS arm64)Ash HartGitHubX @ashxhartHugging FaceWebsite
Full v2 results of the matching setup (same model, engine, quant and hardware; the engine build of the race is not recorded in the race files) · How the game test works · All races