Alternatives
Products that do what Save 50% on Snowflake in 15 minutes does
I'm a former YC founder, and I've been working with some friends from Google to build Espresso AI, an ML-powered Snowflake optimizer. We use LLMs to analyze and predict your SQL workload and run your warehouses more efficiently. Our first few customers are seeing Snowflake savings from 30% to 70%. We're launching out of beta, and if your team uses Snowflake we'd like to help you cut down your bill. You can set up Espresso in under 15 minutes with the instructions here: https://espresso.ai/onboarding Before turning anything on we'll send you a savings estimate based on your…
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Hi HN! I'm just sharing a project I've been working on during the LLM Efficiency Challenge - you can now finetune Llama with QLoRA 5x faster than Huggingface's original implementation on your own local GPU. Some highlights: 1. Manual autograd engine - hand derived backprop steps. 2. QLoRA / LoRA 80% faster, 50% less memory. 3. All kernels written in OpenAI's Triton language. 4. 0% loss in accuracy - no approximation methods - all exact. 5. No change of hardware necessary. Supports NVIDIA GPUs since 2018+. CUDA 7.5+. 6. Flash Attention support via Xformers. 7. Supports 4bit and 16bit…
2023 · github.com
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Running DeepSeek V3 (685B) requires 8×H100 GPUs which is about $14k/month. Most developers only need 15-25 tok/s. sllm lets you join a cohort of developers sharing a dedicated node. You reserve a spot with your card, and nobody is charged until the cohort fills. Prices start at $5/mo for smaller models. The LLMs are completely private (we don't log any traffic). The API is OpenAI-compatible (we run vLLM), so you just swap the base URL. Currently offering a few models.
Apr 2026 · sllm.cloud
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The finance Spreadsheet killer, 20x faster, built in Notion
2023
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Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
2024 · github.com
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I launched my startup's Snowflake optimization product here about two years ago, and we've just released our second product: a Databricks SQL optimizer. The optimizations are basically kubernetes for data warehousing: we take over autoscaling and cluster selection to increase utilization without impacting latency. The scheduler is backed by ML models that predict runtime and capacity, which means we can run machines hotter than the providers can and thereby cut costs. More info here: https://espresso.ai/post/launching-our-databricks-sql-optimi...
Oct 2025
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I’ve been a long-time Snowplow user and unofficial evangelizer. I have deep respect for its founders, Alex and Yali, who I met a few times. What made me fall in love with Snowplow was that it was unopinionated, gave access to raw event data, and was truly open source. Back in 2013, that changed everything for me. I couldn’t look at GA the same way again. Over the years, analytics moved into SQL warehouses driven by cheaper CPU/storage, dbt, reproducibility, and transparency. I saw the need for a democratized Snowplow pipeline and launched a hosted version in 2019. In January 2024,…
Oct 2025 · opensnowcat.io
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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
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Hi HN, we are the founders of Relari (https://www.relari.ai). We launched our LLM evaluation stack on HN a few months ago (https://news.ycombinator.com/item?id=39641105), which is now used in production by AI teams at companies like Vanta and PwC. We have since expanded to directly optimizing parts of an LLM pipeline using a data-driven approach. In particular, we see a lot of potential in the Auto Prompt Optimization—which could be an attractive alternative to fine-tuning in many cases—to use data to align LLMs for domain-specific tasks. Here’s a demo video:…
2024
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We built RapidFire AI, an open-source Python tool to speed up LLM fine-tuning and post-training with a powerful level of control not found in most tools: Stop, resume, clone-modify and warm-start configs on the fly—so you can branch experiments while they’re running instead of starting from scratch or running one after another. - Works within your OSS stack: PyTorch, HuggingFace TRL/PEFT), MLflow. - Hyperparallel search: launch as many configs as you want together, even on a single GPU - Dynamic real-time control: stop laggards, resume them later to revisit, branch promising configs in…
Sep 2025 · github.com
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Hey HN! We've run our privacy-focused open-source inference company for a while now, and we're launching a flat monthly subscription similar to Anthropic's. It should work with Cline, Roo, KiloCode, Aider, etc — any OpenAI-compatible API client should do. The rate limits at every tier are higher than the Claude rate limits, so even if you prefer using Claude it can be a helpful backup for when you're rate limited, for a pretty low price. Let me know if you have any feedback!
2025 · synthetic.new
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CAST AI (https://cast.ai) has built a cloud optimization platform that reduces AWS cloud costs 50% to 90%, optimizes DevOps, and automates disaster recovery via multi-cloud with a single cluster. Intelligent optimization engine delivers a cost-efficient, high-performing, and resilient infrastructure for every Kubernetes workload. If it sounds too good to be true - try free. To make it easier CAST AI provides AWS and GCP cloud credentials for free. Visit https://cast.ai Here's how it works: 1.Use CAST AI to deploy your K8s clusters. Next, take a look at the CAST AI…
2021
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Hi HN I built a fun little tool: It uses Groq’s LLaMA 3.3 + Puppeteer to analyze a website Then it roasts the design/content/UX with humor And finishes with 3–5 genuinely helpful improvement tips You can try it here: https://ai-roast-vert.vercel.app I wanted to: Practice fast idea-to-launch cycle (built in 2 days) Experiment with a viral-friendly product Monetize with a $0.55 pro version that gives a detailed roast + download Would love your feedback — on the idea, the tone, the usefulness — anything! Thanks in advance
Sep 2025 · ai-roast-vert.vercel.app
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Hi HN, I built OpenGraviton, an open-source AI inference engine that pushes the limits of running extremely large LLMs on consumer hardware. By combining 1.58-bit ternary quantization, dynamic sparsity with Top-K pruning and MoE routing, and mmap-based layer streaming, OpenGraviton can run models far larger than your system RAM—even on a Mac Mini. Early benchmarks: TinyLlama-1.1B drops from ~2GB (FP16) to ~0.24GB with ternary quantization. At 140B scale, models that normally require ~280GB fit within ~35GB packed. Optimized for Apple Silicon with Metal + C++ tensor unpacking, plus…
Mar 2026 · github.com
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