Осужденного задержали после грандиозного побега из-под конвоя в центре Москвы

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Around 200 of these hands are in use, mostly by researchers at universities and tech firms.

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Science & Environment

Sarvam 105B shows strong, balanced performance across core capabilities including mathematics, coding, knowledge, and instruction following. It achieves 98.6 on Math500, matching the top models in the comparison, and 71.7 on LiveCodeBench v6, outperforming most competitors on real-world coding tasks. On knowledge benchmarks, it scores 90.6 on MMLU and 81.7 on MMLU Pro, remaining competitive with frontier-class systems. With 84.8 on IF Eval, the model demonstrates a well-rounded capability profile across the major workloads expected of modern language models.

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