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llm inference engines

Recent window: last 5.4 months (2026-05-01 → 2026-10-11), compared with the prior 5.4 months.

horizontal · 94 members · Data as of 2026-10-14

LLM inference engines provide specialized runtimes and execution backends optimized to run large language models efficiently across consumer GPUs, edge devices, and enterprise servers. They are used by machine learning engineers and developers who need maximum token throughput, low latency, and minimal memory footprints when serving models. Unlike training frameworks or high-level AI app builders, these products focus strictly on the low-level execution layer through custom kernels, quantization, and hardware-specific hardware acceleration.

This theme's recent-window count is below the current min-count filter, so it does not appear in the opportunity scorecard.

Pulled from real Hacker News comment threads on this niche's launches.

Most asked for

  • Add tool/API integration for web search capability (1)
    Raised on Maple-Preview
  • AMD GPU RDNA assembly implementation (1)
    Raised on Tiny-vLLM
  • Apple M series GPU support (1)
    Raised on ZSE
  • Author disclosure requirement for LLM usage in projects (1)
    Raised on NanoEuler
  • Benchmark across different hardware platforms (1)
    Raised on Llm.sql
  • Benchmarks against omlx and fast-mlx (1)
    Raised on Rapid-MLX
  • Benchmarks for 140B models on base Mac Mini 16GB configuration (1)
  • Better reasoning and tool-use for conversational requirements (1)
    Raised on Maple-Preview

Concerns raised

Compared to

Members

Name Source Upvotes ▼ Launched
SemIf GITHUB 2318 2026-09-16
Open-source engine running Gemma 4 26B in 2 GB RAM on any M-series Mac HN 919 2026-07-29
Strata GITHUB 918 2026-09-24
Llama 3.1 70B on a single RTX 3090 via NVMe-to-GPU bypassing the CPU HN 395 2026-02-21
Run an 80B Qwen in 4.3 GB of RAM on a Mac, and a 35B on an iPhone HN 312 2026-08-03
Running 104GB Qwen3.8-Flash-Next on 48GB Mac with at ~12 tok/s HN 240 2026-09-01
BaseRT PH 222 2026-07-19
Tiny-vLLM HN 205 2026-05-29
kvmem-llama.cpp GITHUB 176 2026-09-14
Maple-Preview HN 173 2026-08-04
lithos-metal GITHUB 129 2026-10-05
qwenimage-ncnn-vulkan GITHUB 112 2026-09-21
glm53-tensorfold-spark GITHUB 99 2026-09-28
Infernix GITHUB 98 2026-10-08
open-jev-fast GITHUB 88 2026-09-27
mirai-s-ada GITHUB 83 2026-10-06
A tiny LLM running at 21,000 tok/s on a $250 FPGA (Live Demo) HN 79 2026-08-10
strata-mlx GITHUB 75 2026-10-10
vllm-jev GITHUB 72 2026-09-24
PS5LM GITHUB 67 2026-10-01
ZSE HN 58 2026-02-26
NanoEuler HN 55 2026-06-28
jevmlx GITHUB 54 2026-09-17
kyojin GITHUB 53 2026-10-02
sarvam-jev GITHUB 50 2026-09-18
I ran a language model on a PS2 HN 46 2026-03-21
solar-mini4-jev GITHUB 43 2026-09-21
UnbiasedStrata GITHUB 35 2026-10-07
glm53-flash-offload GITHUB 34 2026-10-01
reflex GITHUB 34 2026-09-23
mlxfast-bonsai2-27b-engine GITHUB 30 2026-09-24
Strata-GLM GITHUB 28 2026-10-11
coachwhip GITHUB 28 2026-10-01
MegaCapybara GITHUB 26 2026-10-03
system-one GITHUB 24 2026-09-17
ninfer-ternary-bonsai-ada GITHUB 23 2026-09-20
gr8 GITHUB 22 2026-10-10
TandemLLM GITHUB 21 2026-09-28
janas GITHUB 21 2026-09-20
qwen38-flash-next-b70-offload GITHUB 21 2026-10-06
Run Agent Skills with mistral.rs v0.8.10: /v1/skills support and more HN 20 2026-06-18
deepseek-v4.1-tensorfold-tp2-2xgb10 GITHUB 20 2026-10-04
hashyy GITHUB 18 2026-10-03
JEV-CPU GITHUB 18 2026-09-19
gfx1151-engine GITHUB 18 2026-09-19
factorio-transformer GITHUB 17 2026-10-04
Run 500B+ Parameter LLMs Locally on a Mac Mini HN 17 2026-03-09
cyber-on-strata GITHUB 17 2026-10-09
PipeSwift GITHUB 16 2026-10-12
Qwen3.8-Flash-Dual-DGX-Sparks-TensorFold GITHUB 16 2026-10-07