14B open-source model matches o3-mini on code tasks; full training recipe, dataset, and RL framework included for reproducibility.
Summary
Eliminates dependency on closed API-gated models for competition-level coding benchmarks. Developers can now audit training, fine-tune on proprietary codebases, and run inference on consumer hardware without token costs.
Why it matters
Eliminates dependency on closed API-gated models for competition-level coding benchmarks. Developers can now audit training, fine-tune on proprietary codebases, and run inference on consumer hardware without token costs.
Implementation verdict
Replaces o3-mini API calls for coding tasks if latency tolerance exists. Requires GPU with 14B model capacity (28GB VRAM minimum) and integration via Hugging Face Transformers. Training cost documented at ~$27K; worth evaluating now as baseline for local reasoning-based coding agents.
Sources
Dev Signal
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