Unverified50% confidenceFactExact time
RedPen runs on an 8GB Apple Silicon MacBook, requiring no GPU and no Docker; Gemma 3 1B is called via llama.cpp after Q4 quantization, with weights of 769MB, a load time of 2.3 seconds, and a resident memory of 0.83GB; rule processing takes 12-28 milliseconds, a full review (including the model layer) takes 11-17 seconds, and results are rendered via SSE streaming.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/14/2026
First Seen
Valid until: 1/12/2027
Sources
Related Entities
Related Claims
UnverifiedRunning via llama.cpp on a MacBook Pro with an M4 Pro chip and 24GB unified memory, the text decoding speed is 10.13 tokens/second, with each complete task taking 4 to 7 minutes.77% similarUnverifiedThe FP4-based model (svdq-fp4_r32) built on Nunchaku has a size of 6.6GB, fits entirely within 8GB of VRAM without CPU offloading, and reduces the per-step time to 3.4–3.8 seconds.75% similarUnverifiedRedPen's hardware floor is 8GB of memory, at which 1-3B Q4-quantized models can run and 7B cannot; scanned PDFs are not supported, and when there is no selectable text the file is not sent to an OCR service but simply stated as unsupported.73% similar
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