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Infernix

C++/CUDA single-GPU inference engine for Qwen3.8 (incl. Qwen3.8-Flash-Next with offloaded experts) on the RTX 5090; grew from NInfer

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This is 1 of 239 launches in model optimization and inference runtimes — see how it stacks up on momentum and crowding →

1826 other launches read as similar to this one →

Details

External ID
1411051572
Source
GITHUB
Company
—
Product
Infernix
Website domain
github.com
Launched
Oct. 8, 2026
Cohort
—
Upvotes
92
Upvotes percentile
0.82
Tags
—

Enrichment

Niche
model optimization and inference runtimes
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
single-gpu inference engine for local llms
Manually corrected
False

Could you build this?

No Writing a custom C++/CUDA LLM inference engine with expert offloading optimized for specific GPU architectures requires expert-level GPU systems engineering.

What it would actually take: Building an inference engine like this requires modern C++, custom CUDA kernels (or CUTLASS/Triton), memory allocation orchestration between CPU RAM and GPU VRAM over PCIe, and deep knowledge of MoE architectures and FP8/FP4 quantization.

Competitors

Other products that read as similar to this one — 1826 launches clear the similarity bar, closest 8 shown.

Attention rank: #329 of 1827 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 344 days after the earliest competitor.

Other launches for this product