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Strata-GLM

Strata fork that runs GLM-5.3-Flash (320B-A18B, 157 GB) on one PC: RTX 5090 + 128 GB RAM + NVMe, ~30 tok/s chat. Fork of Niko1221/Strata (MIT).

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This is 1 of 94 launches in llm inference engines — see how it stacks up on momentum and crowding →

80 other launches read as similar to this one →

Details

External ID
1413797095
Source
GITHUB
Company
—
Product
Strata-GLM
Website domain
github.com
Launched
Oct. 11, 2026
Cohort
—
Upvotes
28
Upvotes percentile
0.56
Tags
—

Enrichment

Niche
llm inference engines
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
local inference runner for large llms on consumer hardware
Manually corrected
False

Could you build this?

No Running a 320B parameter MoE model across heterogeneous memory tiers (GPU VRAM, CPU RAM, NVMe) at ~30 tok/s requires custom high-performance C++/CUDA kernel engineering, memory-mapped I/O paging, and low-level quantization/pipelining.

What it would actually take: Building this requires systems programming in C++/CUDA and low-level runtime engines like llama.cpp or custom tensor runtimes. The hardest part is orchestrating asynchronous pre-fetching of active MoE expert weights from NVMe and system RAM to GPU VRAM without stalling generation, along with specialized quantized GEMM kernels. It demands deep systems engineering expertise in GPU memory hierarchies, PCIe bandwidth saturation, and LLM inference engine architectures.

Competitors

Other products that read as similar to this one — 80 launches clear the similarity bar, closest 8 shown.

Attention rank: #37 of 81 (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