Head-to-head
deepseek-r1:32b vs GPT-5.5 (Codex)
Both models answered the same one-shot tasks under identical rules — no retries, answers published unedited. Two separate axes, never blended: does the code actually run, and how do blind-scored text answers hold up against a written gold answer. Frontier references sit outside the blind field and are deliberately unscored on text.
| Model | Runnable sims | Blind text avg | Failure modes |
|---|---|---|---|
| deepseek-r1:32b | 27% (23/85) | 8.90 (20 scored) | ERR 34 · STAT 7 · BLANK 19 · HANG 1 · DNF 1 |
| GPT-5.5 (Codex) frontier reference | 95% (81/85) | unscored by design | ERR 2 · STAT 1 · BLANK 1 |
Biggest contrasts
Rounds where the two models diverged most — open them and read both answers side by side.
| Round | deepseek-r1:32b | GPT-5.5 (Codex) |
|---|---|---|
| R152 · Hash table with visible collision chains | BLANK | OK |
| R151 · Binary search tree growing node by node | ERR | OK |
| R137 · Cloth mesh hanging and rippling in the wind | BLANK | OK |
| R130 · Radix sort ordering by one digit at a time | ERR | OK |
| R129 · Heap sort sifting the maximum to the back | STAT | OK |
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Generated 2026-07-31 from the published rounds. Harness failures are excluded from every base — a broken cluster node is our fault, not the model's.