Developer Tools1 month ago
ModelBrew — AI you don't have to double-check
Fine-tune LLMs with your data and manage custom facts with cryptographic deletion proofs.
@MBrew26730 · X
Dataset cleaning + fine tuning + continual learning at
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Fine-tune LLMs with your data and manage custom facts with cryptographic deletion proofs.
@MBrew26730 · X
Dataset cleaning + fine tuning + continual learning at
Real-time LLM-powered news aggregator surfacing trending stories with live updates.
tdubey · HN
DWS A LLM Generated, "Drudge Report" style news site
Find AI models optimized for your hardware with performance and pricing estimates.
cdnsteve · HN
Tokenstead, find AI models for your hardware
Format-agnostic LLM hub. Bring your own provider keys and route across Anthropic, OpenAI, ChatGPT/Codex, Kimi, Alibaba DashScope, and AWS Bedrock — with unified observability and c
@0xxmemo · X
Detect if your LLM API has been model-swapped or degraded with 6 deterministic probes.
cocodot LLM 降智检测 — 免费的 LLM API「降智/偷换模型」在线检测：填入任意 OpenAI 兼容端点的 base_url 和临时 API Key，跑 6 项探针（模型声明、动态题、能力完整性等）生成分项报告；Key 仅用于当次检测、不落库不留存，检测方法[开源](https://github.com/cocodot2026/cocodot-llmprobe)
Estimate VRAM requirements for running models with llama.cpp
hypfer · HN
According to this shitty vibecoded thing "I" built https://hypfer.github.io/will-it-fit-llama-cpp/ (and I guess according to math too), FP16 K/V would give me something like 90k context at the same model quant, which doesn't really fit my usage. But maybe someone else has experience to share there
OpenAI-compatible API for running open-weight LLMs and video models.
bingus-bongo · HN
Use GLM-5.3 in Cursor today via tokengo API
Visualize hardware performance metrics while running LLM inference on your system.
dev_dan_2 · HN
WatchMachineGo – A visualizer to show hardware performing LLM inference
Access open-source AI models developed in China through a privacy-focused API service.
@Jenny5143197635 · X
Check which LLMs run on your GPU given your hardware specs and budget.
jaeseok614 · HN
Open-source calculator for "will my GPU run this LLM?"
Test small language models (8M-13M parameters) in your browser that work offline.
u/Live_Confusion_3003 · Reddit
I trained an LLM that runs on an ESP32 and directly in the browser Link to try it out yourself is: topk.sh The models download their weights directly in the browser so it works offline. Keep in mind they are very small and inaccurate. (8M and 13M parameters) However, I am building 500M and 1B+ parameter local models for agent based coding and other purposes. I will be shipping hardware designed for these tasks which connect directly to you computer or other device.
Access thousands of AI models through a single OpenAI-compatible API.
@mageofweb3 · X