Top-level at-a-glance table with PPL, NIAH, speed ratios across all
tested hardware, compression ratios, and link to decode regression
analysis doc.
Co-Authored-By: tturney@psyguard.ai
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
First community diagnostic from @Ambisphaeric (M1 Max 64GB):
- Prefill: 93-98% of q8_0 (excellent, flat curve)
- Decode: 84% short → 39% at 32K (M1 constant LUT issue)
M2 Pro Mac Mini partial results (in progress, noisy from workloads).
Co-Authored-By: tturney@psyguard.ai
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Community testers need to know which fork to build. Apple Silicon
uses our Metal fork, NVIDIA/AMD uses spiritbuun's CUDA fork.
Also added flash attention requirement warning.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-Authored-By: tturney@psyguard.ai
1. Zip failure no longer deletes raw artifacts — preserves data if zip fails
2. main() returns 1 on unhandled exception (was always returning 0)
3. --skip-ppl no longer requires llama-perplexity binary
4. Multi-GPU nvidia-smi: sum memory/util, max temp across all GPUs
5. Model path logged as basename only (was leaking full path with username)
6. Build instructions now platform-aware (Metal vs CUDA)
7. Sharing instructions: GitHub issues + @no_stp_on_snek DM
8. Removed legacy bash diagnostic script (superseded by Python v5)
253 tests, 100% coverage.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-Authored-By: tturney@psyguard.ai