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@PandaTalk8: These test results are stunning. The original poster tested the DS4 inference engine written in C by @antirez, and local deployment seems incredibly fast. The good news is that only 128GB of RAM is needed to run a local model equivalent to GPT-4o. The bad news is that you need a MacBook Pro with 128GB of RAM.

X AI KOLs Timeline · yesterday Cached

This article reports on tests of the DS4 inference engine written in C by @antirez, noting its impressive speed when running a GPT-4o-equivalent model on a MacBook Pro with 128GB of RAM.

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#inference-engine

@QingQ77: Pure Rust LLM inference engine with custom CUDA kernels for each hardware × model × quantization combination, achieving higher inference speed than vLLM and TensorRT-LLM. https://github.com/Avarok-Cybersecurity/a…

X AI KOLs Timeline · 2d ago Cached

Atlas is a pure Rust LLM inference engine that delivers faster inference than vLLM and TensorRT-LLM by customizing CUDA kernels for each hardware × model × quantization combination.

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#inference-engine

feat: Add Mimo v2.5 model support by AesSedai · Pull Request #22493 · ggml-org/llama.cpp

Reddit r/LocalLLaMA · 3d ago Cached

A pull request has been merged into llama.cpp to add support for the Mimo v2.5 model, enhancing the framework's compatibility with this specific AI architecture.

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#inference-engine

vLLM V0 to V1: Correctness Before Corrections in RL

Hugging Face Blog · 4d ago Cached

ServiceNow engineers detail their migration from vLLM V0 to V1, focusing on resolving backend correctness issues like logprob semantics and runtime defaults to ensure stable reinforcement learning training dynamics.

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#inference-engine

@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

X AI KOLs Timeline · 2026-04-20 Cached

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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