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Insight for: No Difference in tokens/sec - Ministral3 8B Q5_K_M

TurboQuant (turbo3 and turbo4) performance optimization for LLM inference, specifically on Apple M1 hardware.
Analyzed: Apr 1, 2026
This issue reports a critical failure in TurboQuant's core value proposition: performance improvement. On Apple M1 hardware, `turbo3` and `turbo4` not only fail to increase `tokens/sec` but actually degrade performance compared to the baseline `llama-cpp`. This directly undermines the market viability of TurboQuant as a speed optimization for Apple Silicon users. For B2B SaaS, performance regressions are unacceptable. Solutions promising efficiency gains must deliver consistently across target hardware. This indicates a significant engineering challenge in optimizing quantization for specific architectures, highlighting the need for rigorous cross-platform benchmarking and targeted development to ensure promised benefits materialize.
tokens/sec llama-cpp llama-server turbo3 turbo4 Ministral3 8B Q5_K_M MAC M1 32GB RAM
GitHub Issue