Unverified50% confidenceBenchmarkExact time
Ψ-0.6 surpasses leading open-weight models in a zero-shot manner on the MindCube complex spatial reasoning benchmark.
1
Sources
50%
Confidence
Short-term (~14 days)
Relevance
10/27/2026
First Seen
Valid until: 11/10/2026
Sources
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Related Claims
UnverifiedAfter INT8 quantization, a model at the 0.9B scale can theoretically reduce its inference memory footprint to below approximately 1GB.68% similarUnverifiedOn four Theory-of-Mind benchmarks, the weak model's average score rose from 0.49 to 0.91.65% similarUnverifiedQ8_0 quantization compresses model weights from 32-bit floating-point numbers to 8-bit integers, with precision loss typically within 1% compared to FP32.64% similarUnverifiedIn the setting closest to reality (where unstated constraints must be actively discovered), the best-performing model configuration achieves an average FDE-Gym score of only 0.56.63% similarUnverifiedThe lower the quantization bit depth, the more likely the model is to show degraded performance on detailed reasoning, but for most tasks at quantization levels above 4-bit, the experiential difference is not obvious to ordinary users.63% similar
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