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TinyLoRA Proves 13 Bytes Can Outsmart Billions on Math Tests

Forget million-parameter fine-tunes. A new method from Meta hits 91.8% on GSM8K math problems with 13 params on a 7B model. This flips efficiency scripts—and eyes on-device tweaks.

Priya Sundaram 📅 Mar 24, 2026 ⏱️ 3 min read 👁️ 6 views
Graph showing TinyLoRA's 13-parameter model outperforming full fine-tuning on GSM8K math benchmark

⚡ Key Takeaways

  • TinyLoRA hits 91.8% GSM8K with 13 params on 7B model, beating full FT.
  • RL trumps SFT by 100-1000x in tiny regimes due to denser signals.
  • Tiling shares + fp32 + r=2 optimize micro-updates for edge AI.

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Priya Sundaram
Written by

Priya Sundaram

Hardware and infrastructure reporter. Tracks GPU wars, chip design, and the compute economy.

#GSM8K benchmark #TinyLoRA #parameter-efficient fine-tuning #reinforcement-learning

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Originally reported by MarkTechPost

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