Run Full Kimi K3 with 29 GB of RAM
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HN · launched Jul 30, 2026 · 9 upvotes (top 49%) · 0 views
Niche: llm inference and deployment tools · 188 launches, 6 in the last 7 days · Explore this niche →
Category and tags
- Horizontal
- Model & infra
- Developer
- AI-native
- Hobby / open-source project
Visit website ↗ Source listing ↗
More like this: all 188 launches in llm inference and deployment tools →
Could you build this?
No Fitting a massive Mixture-of-Experts LLM like Kimi K3 into just 29 GB of RAM requires cutting-edge model quantization, expert offloading, and custom low-bit weight dequantization kernels.
What it would actually take: This requires low-level C++ or CUDA/Metal systems engineering leveraging extreme quantization techniques (such as 2-bit/3-bit K-quants or dynamic expert pruning) and asynchronous memory-mapped disk/RAM paging to dynamically load only active MoE experts per token. It relies on custom hardware-specific SIMD/tensor core instructions to prevent token throughput from collapsing while swapping gigabytes of sparse weights. Achieving usable tokens-per-second under this memory constraint requires deep expertise in LLM inference architecture and GPU memory subsystems.
Discussion
2 comments analyzed.
Competitors mentioned: OpenRouter, ONNX runtime
Concerns raised: Performance drop from running on personal PC vs full version, Memory constraints and quantization tradeoffs affecting model quality, Tradeoff between model size and quality
Competitors
Other products that read as similar to this one : 295 launches clear the similarity bar, closest 8 shown.
Attention rank: #149 of 296 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 265 days after the earliest competitor.
- Run an 80B Qwen in 4.3 GB of RAM on a Mac, and a 35B on an iPhone · hn · 2026-08-03 · 312 upvotes · similarity 0.57
- DMR · github · 2026-11-05 · 27 upvotes · similarity 0.55
- Warp · hn · 2026-09-15 · 13 upvotes · similarity 0.53
- baa · github · 2026-10-12 · 11 upvotes · similarity 0.48
- I audited 500 K8s pods. Java wastes ~48% RAM, Go ~18% · hn · 2025-12-13 · 36 upvotes · similarity 0.48
- Qwen3.6-35B-A3B on a 16 GB M1 Pro with SSD-streamed MoE · hn · 2026-07-17 · 24 upvotes · similarity 0.47
- A new engine to run Kimi K3 on a laptop · hn · 2026-07-29 · 7 upvotes · similarity 0.47
- Fine-tune an 8B model on a 4 GB laptop GPU · hn · 2026-08-04 · 139 upvotes · similarity 0.45
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