Benchmark Accuracy
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Deep Cogito’s Open LLMs Outperform Similar-Sized Models Using IDA Technique
San Francisco startup Deep Cogito unveils open-source LLMs (3B–70B parameters), claiming superior performance over Meta’s Llama, DeepSeek, and Alibaba’s Qwen in benchmarks like MMLU and GSM8K. Their innovation, Iterated Distillation and Amplification (IDA), enables self-improvement cycles without human feedback, using two phases: computational exploration for advanced reasoning (Amplification) and consolidation of insights into core parameters (Distillation). A 70B IDA-tuned model achieved 91.73% MMLU accuracy, outperforming Llama 3.3 70B. Future plans include larger MoE models (109B–671B) under open licenses, aiming to challenge proprietary AI dominance while sparking debates about scaling intelligence economically.
