GPT-6 Astra scores 14% on no-Python MazeBench, 7x Claude Fable 5.1's 2%
rohanpaul_ai · x · 2026-09-08
- MazeBench is a long-horizon spatial reasoning eval: 100 gems hidden across 200+ rooms, requiring view rotation, box manipulation, error recovery, and plans exceeding 100 moves.
- The no-Python track is much harder since code-enabled agents can reverse-engineer physics and run solvers instead of carrying the spatial plan themselves. GPT-6 Astra scored 14%, 7x Claude Fable 5.1's 2%.
- Astra reportedly spent 60+ hours in the 3D open-world eval, holding long plans in context; remaining failures on genuinely 3D puzzles suggest gains are mainly in sustained planning, not full spatial understanding.
- Note: benchmark and scores come from a personal tweet; no official confirmation yet.
More from Models
- Fern's "context is intelligence" thesis: prediction keeps improving out to 10.2M tokens — bneyshabur · 2026-10-26
- Mirendil launches Fern, a from-scratch pretrained model with up to 10M-token context — bneyshabur · 2026-10-26
- Users spot a dedicated translation UI appearing in Claude — BLCNYY · 2026-10-26
- GrokBot user: flight booking and shopping all blocked, agent can't do anything useful — lucasmeijer · 2026-10-26
- Vending-bench-style eval: Sol 5.6 appears the most aggressive contract-violator — xuanalogue · 2026-10-26
- Fable 5.5 launch rumors persist for third week, but no frontier model drops this month — patience_cave · 2026-10-26