@linexjlin: K2.6 built a Zig LLM inference engine from scratch on Mac in 12h, pushing Qwen 3.5 0.8B from 15 tok/s to 193.1 tok/s
Summary
Developer wrote a Zig-based LLM inference engine from zero on macOS in 12 hours, boosting Qwen 3.5 0.8B throughput from 15 to 193 tokens per second.
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Cached at: 04/21/26, 10:00 AM
K2.6 spent 12 hours writing an LLM inference engine from scratch in Zig on a Mac, and tuned Qwen 3.5 0.8B inference from 15 tok/s to 193.1 tok/s.
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K2.6 successfully downloaded and deployed the Qwen3.5-0.8B model locally on a Mac, using the niche Zig language to implement and optimize inference, demonstrating the new model’s generalization ability. After 4,000+ tool calls and 12+ hours of continuous operation, K2.6 iterated 14 times, boosting throughput from ~15 tokens/s to ~193 tokens/s, ultimately achieving 20% faster inference than LM Studio.
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