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automated AI research

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Oct 22, 2026 · Artificial Intelligence

Flint-40B-A2B: AI-Built MoE Coding Model Hits 125 tok/s on MacBook Pro

Recursive_SI's first model Flint-40B-A2B, a 40B MoE model activating 2.5B parameters per token, was built in under four months using the automated Eureka Machine system. It achieves state-of-the-art local coding performance on benchmarks like SWE-Bench while running at 125+ tokens/sec on MacBook Pro M4 Pro and 150+ tokens/sec on NVIDIA RTX Spark, with open weights on Hugging Face under Apache 2.0.

Apple SiliconEureka MachineFlint-40B-A2B

0 likes · 10 min read

Flint-40B-A2B: AI-Built MoE Coding Model Hits 125 tok/s on MacBook Pro

SuanNi

Jun 12, 2026 · Artificial Intelligence

Recursive AI’s First Results: SOTA on Three Key Benchmarks

Recursive’s new AI research system automatically generates and validates ideas, code, and experiments, and its first release beats state‑of‑the‑art on three benchmarks—fixed‑budget language‑model training, small‑model training speed, and GPU kernel efficiency—while detailing its methodology, reward‑cheating safeguards, and open‑source results.

AI benchmarksGPU kernel optimizationRecursive AI

0 likes · 8 min read

Recursive AI’s First Results: SOTA on Three Key Benchmarks

Machine Heart

Jun 12, 2026 · Artificial Intelligence

Recursive AI Takes Its First Step: Automated Research System Sets New SOTA Benchmarks

Recursive Superintelligence unveiled an open‑source system that automates the AI research loop, achieving state‑of‑the‑art results on three distinct benchmarks—NanoChat autoresearch, NanoGPT speedrun, and SOL‑ExecBench—while illustrating the practical progress toward recursive self‑improvement warned about by Anthropic.

AI automationAnthropicGPU kernel optimization

0 likes · 12 min read

Recursive AI Takes Its First Step: Automated Research System Sets New SOTA Benchmarks