AI · alternatives · 2026
24 alternatives to Layer-Streaming Telemetry Harness
Benchmark massive MoE LLMs under strict 0GB VRAM limits
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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OpenTelemetry-native observability for agents and LLMs
Aug 2026 · openobserve.ai · its alternatives →
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Find the local LLM that actually runs and performs best on your hardware. Ranked by real, recency-aware benchmarks, not parameter count. One command, run it instantly. - Andyyyy64/whichllm
May 2026 · github.com · its alternatives →
- 4IM
2023 · vram.asmirnov.xyz · its alternatives →
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SelfHostLLM▲134A simple calculator that estimates how many concurrent requests your GPU can handle for a given LLM, with shareable results.
2025 · selfhostllm.org · its alternatives →
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Fine-tune LLMs from one YAML. Layer streaming trains an 8B model on a 4 GB laptop GPU. - MakazhanAlpamys/Soup
Aug 2026 · github.com · its alternatives →
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The standard GPU utilization metric reported by nvidia-smi, nvtop, Weights & Biases, Amazon CloudWatch, Google Cloud Monitoring, and Azure Monitor is highly misleading. It reports the fraction of time that any kernel is running on the GPU, which means a GPU can report 100% utilization even if only a small portion of its compute capacity is actually being used. In practice, we've seen workloads with ~1–10% real compute throughput while dashboards show 100%. This becomes a problem when teams rely on that metric for capacity planning or optimization decisions, it can make underutilized systems…
Apr 2026 · systalyze.com · its alternatives →
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allocscope - a memory tracking tool. Contribute to matt-kimball/allocscope development by creating an account on GitHub.
2023 · github.com · its alternatives →
- 9AT
A 3.16M-parameter INT4 transformer running entirely in the on-chip memory of a Xilinx Kria KV260. Zero DRAM in the token loop, 59,965 tok/s on the fabric, bit-exact. Chat with it live.
Aug 2026 · mikeayles.com · its alternatives →
- 10UD
Hey HN! I’m the founder of Unify, and we’ve just released our Model Hub, which provides a collection of LLM endpoints with live runtime benchmarks all plotted across time: https://unify.ai/hub A key finding is that static tabular runtime benchmarks for LLMs simply do not work. It’s necessary to take a time-series perspective, and plot the variations through time. We currently have 21 models provided by: Anyscale, Perplexity AI, Replicate, Together AI, OctoAI, Mistral AI and OpenAI, with more on the roadmap. We test across different regions (Asia, US, Europe), with varied…
2024 · its alternatives →
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High performance storage engine for efficient LLM inference and GPU Training.
Sep 2026 · theopenlake.com · its alternatives →
- 12AT
I recently built a small open-source tool to benchmark different LLM API endpoints — including OpenAI, Claude, and self-hosted models (like llama.cpp). It runs a configurable number of test requests and reports two key metrics: • First-token latency (ms): How long it takes for the first token to appear • Output speed (tokens/sec): Overall output fluency Demo: https://llmapitest.com/ Code: https://github.com/qjr87/llm-api-test The goal is to provide a simple, visual, and reproducible way to evaluate performance across different LLM providers, including…
2025 · llmapitest.com · its alternatives →
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I made this after seeing someone posit the idea online yesterday over lunch then spent some time refining it. So far it's pretty impressive IMO! Right now I am running Qwen3-30B-A3B on my 24gb unified memory m4 MacBook Pro at 50 tok/sec and this should definitely not be working for such a large model on my middling hardware. Things are detailed in the README to get up and running and DESIGN.md has details on all the choices and such made along the way.
Aug 2026 · github.com · its alternatives →
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Built a simple web app that tells you which open-source LLMs will work on your hardware. It auto-detects your specs, shows compatible models from Hugging Face, gives realistic performance estimates (tokens/sec), and recommends quantization settings. You can also manually input specs to see "what if I upgraded my RAM?" Made this after wasting time downloading giant models only to find they crawled on my hardware. Hope it saves you some frustration!
2025 · caniusellm.com · its alternatives →
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I built a small Linux tool to deterministically verify GPU PCIe link health and bandwidth. It reports: - Negotiated PCIe generation and width - Peak Host→Device and Device→Host memcpy bandwidth - Sustained PCIe TX/RX utilization via NVML - A rule-based verdict derived from observable hardware data only This exists because PCIe issues (Gen downgrades, reduced lane width, risers, bifurcation) are often invisible at the application layer and can’t be fixed by kernel tuning or async overlap. Linux-only: it relies on sysfs and PCIe AER exposure that Windows does not provide.
Dec 2025 · github.com · its alternatives →
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GPU Observability with workload attribution. One OTLP agent per node ties hardware metrics (NVIDIA, AMD, Intel Gaudi) to the K8s pod or Slurm job burning the GPU. - last9/gpu-telemetry
Jul 2026 · github.com · its alternatives →
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Hey HN, we’re the developers of OpenLake, an open source storage engine for offloading LLM KV caches from GPU memory into a shared tier of RAM and NVMe. We built OpenLake because KV caches are outgrowing GPU memory. A single 256K token conversation on Gemma 4 31B produces approximately 43GB of KV state, more than half the memory of an 80GB H100. The problem becomes even harder across a cluster: a prefix cached on one GPU host is unavailable when the next request lands on a different GPU, forcing the new GPU to repeat work the fleet has already completed. Once the KV cache is offloaded,…
Jul 2026 · github.com · its alternatives →
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Witness-Centered Filter Layer for LLM Applications - SpecStudio-net/Vivek
Jun 2026 · github.com · its alternatives →
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Abstract page for arXiv paper 2607.23806: A Frozen 12B Beats Frontier Models on Verified Work: 100% Accuracy, 0 Tokens, Bit-Exact, Forever
Jul 2026 · arxiv.org · its alternatives →
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Measure & Maximize Ollama LLM Performance Across Hardware
2025 · llm.aidatatools.com · its alternatives →
- 22LA
Hey everyone, I’ve been working on a project called L88 — a local RAG system that I initially focused on UI/UX for, so the retrieval and model architecture still need proper refinement. Repo: https://github.com/Hundred-Trillion/L88-Full I’m running this on 8GB VRAM and a strong CPU (128GB RAM). Embeddings and preprocessing run on CPU, and the main model runs on GPU. One limitation I ran into is that my evaluator and generator LLM ended up being the same model due to compute constraints, which defeats the purpose of evaluation. I’d really appreciate feedback on:…
Feb 2026 · its alternatives →
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I thought it'd be interesting to use Linux PSI (Pressure Stall Information) for an LLM runtime to trim the KV cache. This is mainly useful imo for edge devices like the Jetson Orin super nano kit which have unified memory. I haven't benched much, but plan to do so more over time and see if I can make a real use of it as I run local LLMs. Let me know if it makes sense :P (I of course vibed this idea)
Jun 2026 · github.com · its alternatives →
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Hi everyone, I just released an open source load testing tool for LLMs: https://github.com/twerkmeister/tokenflood === What is it and what problems does it solve? === Tokenflood is a load testing tool for instruction-tuned LLMs hat can simulate arbitrary LLM loads in terms of prompt, prefix, and output lengths and requests per second. Instead of first collecting prompt data for different load types, you can configure the desired parameters for your load test and you are good to go. It also let's you assess the latency effects of potential prompt parameter changes before…
Nov 2025 · github.com · its alternatives →
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