niklaslenzGLM-5.3-Flash in the Gauntlet
2 DGX Sparks 256 GB · TensorFold native (Zig 0.17.0, engine f350cd3e + Mia's 112 patches), Mia's GLM-5.3-Flash recipe 1104 @d4226a1 (EXL3 4 bpw, DFlash2 drafts, tensor parallel 2)
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) | ✕●✕✕✕ | 1 / 5 | 6.8 s | no | 4 (48.0 s) | 62.0 s |
| 2 | Painter (code, level 2) | ✕✕●✕✕ | 1 / 5 | 4.2 s | no | 4 (48.0 s) | 59.4 s |
| 3 | Bench seating (puzzle, level 3) | ✕✕✕✕● | 1 / 5 | 6.7 s | no | 4 (60.0 s) | 73.9 s |
| 4 | Snake (code, level 4) | ✕✕✕✕✕ | 0 / 5 | 16.9 s | no | 5 (75.0 s) | 99.1 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.
Who made what
- Recipe (version 1104, commit d4226a1) and EXL3 quantMia's AI LabX @MiaAI_labGitHubHugging FaceWebsite
- ModelZ.ai (GLM-5.3-Flash)Hugging FaceX @Zai_orgGitHubWebsite
- Draft model (DFlash2, revision bf582e4e)Inco AIX @inco_aiHugging FaceGitHubWebsite
- Engine (TensorFold, commit f350cd3e)Ash HartX @ashxhartGitHubHugging FaceWebsite
- EXL3 formatturboderpX @turboderp_Hugging FaceGitHub
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