Alternatives
Products that do what The Grid does
Spot market API for cheaper LLM inference
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May 2026 · github.com
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G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…
2023 · github.com
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Looking for the cheapest place to deploy llama 3.1 model? Don't worry we have found it so you don't have to.
2024 · github.com
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Hi HN! Excited to show off the project we've been working on for the last couple months. We started with an idea for a crazy twist on prediction markets: You come up with a question for traders to predict, and then decide the outcome yourself. For example, you could create a market on “Will my date with [X] go well?” Anyone can bet on it, and the bets create a forecast on the chance your date goes well. After the date is over, you get to judge the result and reward the traders who picked the correct side. There are so many ways for this mechanism to go wrong: the creator of the market can be…
2022 · manifold.markets
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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 community, I have been working on benchmarking publicly available LLMs these past couple of weeks. More precisely, I am interested on the finetuning piece since a lot of businesses are starting to entertain the idea of self-hosting LLMs trained on their proprietary data rather than relying on third party APIs. To this point, I am tracking the following 4 pillars of evaluation that businesses are typically look into: - Performance - Time to train an LLM - Cost to train an LLM - Inference (throughput / latency / cost per token) For each LLM, my aim is to benchmark them for…
2023 · github.com
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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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2024 · columns.ai
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Hi HN! We partnered with the Atlas team to build a tool called AI Predict [0] that allows anyone to ask any question about the future and get a thoroughly researched, AI-generated prediction on how likely it is to be true. How it works: Atlas replicated a Berkeley paper [1] that showed LLMs could make predictions as accurate as the crowd. We’re using a mix of models from OpenAI and Anthropic, with information retrieval powered by NewsCatcher [2]. The system is live and fully functional, though it might struggle with hyper-local questions outside of the public domain (e.g., “Will I have…
2024 · aipredict.fun
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Current AI-assisted CLI tools are often part of larger systems and work better on Linux. I built llm-term to address these. It's a Rust-based tool that compiles into a single binary file. You only need to download the binary, add it to your PATH, and configure your OpenAI key to get started. While llm-term offers an option for gpt-4o, it works great with gpt-4o-mini. So it's not costly. I appreciate any feedback or suggestions.
2024 · github.com
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We’ve just launched Gradient — an API that helps you build private LLMs that you own. We simplify inference and fine-tuning on open-source LLMs such as llama2, and you only pay by the token. Our API platform makes it possible for you to create private models with a single API call. Run inference on your fine tuned model instantly with no cold boot (and no need to pay for compute costs). The product is truly on demand - when you run fine tuning and inference on our platform, there's nearly 0 startup latency for these API calls. And you're not paying for the compute, you just pay for the…
2023 · gradient.ai
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Hi HN, We’re building https://www.switchpoint.dev – a drop-in replacement for OpenAI’s API that reduces LLM cost by smartly routing across models (e.g., Claude, Gemini, GPT-4) depending on subject and difficulty of the task. Why we built this: LLM costs are spiraling—especially for products doing retrieval, agentic reasoning, or even just high-volume chat. We were frustrated with paying GPT-4 rates when most queries didn’t need it. So we built a router that: - Starts with cheaper/free models (like Llama 8B, 4o-mini, 2.0 flash) - Streams responses and upgrades on failure - Acts…
2025 · switchpoint.dev
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2025 · github.com
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Hey HN, If you tried running open-source models like Llama 3.1 70B or 405B, you might have noticed that it gets very expensive. The reason looks obvious enough that you might have stopped even before trying it! - GPUs are very expensive to buy or rent - Running the most performing LLMs need 4, 8 or even 16 top of the line Nvidia GPUs - And that won’t get you anywhere near the level of VRAM needed to batch enough to get a decent throughput and efficiency Some have even questioned if open-source LLM providers are not doing some shenanigans to provide the prices they offer. VC funded…
2024
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