Alternatives
Products that do what Model Vessel does
Not sure what LLM to use? Combine them all.
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Compare LLMs on your data, measure, and pick the best.
Apr 2026 · trismik.com
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Nowadays, a common AI tech stack has hundreds of different prompts running across different LLMs. Three key problems: - Choices, picking from 100s of LLMs the best LLM for that 1 prompt is gonna be challenging, you're probably not picking the most optimized LLM for a prompt you wrote. - Scaling/Upgrading, similar to choices but you want to keep consistency of your output even when models depreciate or configurations change. - Prompt management is scary, if something works, you'll never want to touch it but you should be able to without fear of everything breaking. So we launched Prompt…
2024 · jigsawstack.com
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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
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Hey HN, I just updated my project that compares some LLMs. It uses your prompt for all the models and runs at the same time. You can see the results being generated in real-time and decide what's the best for your use case. I'm open to any suggestions and feedback. Thanks!
2024 · geminivsgpt.com
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This is another one of my automate-my-life projects - I'm constantly asking the same question to different AIs since there's always the hope of getting a better answer somewhere else. Maybe ChatGPT's answer is too short, so I ask Perplexity. But I realize that's hallucinated, so I try Gemini. That answer sounds right, but I cross-reference with Claude just to make sure. This doesn't really apply to math/coding (where o1 or Gemini can probably one-shot an excellent response), but more to online search, where information is more fluid and there's no "right" search engine + text…
2024 · ithy.com
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Hi, I was a corporate lawyer for many years working with a lot of financial services and insurance companies. In practicing law, I noticed there was a lot of repetition in the tasks I was working on even as a highly paid attorney that could be automated. I wanted to solve the problem of dealing with a lot information and data in a practical way, using AI. This motivated me to start AI Bloks/LLMWare with my husband, who had a deep background in software and is a very early adopter of AI. We have been on this journey with our open source project LLMWare for the past 4 months, producing a…
2024 · github.com
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Henry, Matt and James here – we’re building an open source toolkit that makes it easy to integrate an LLM-powered copilot that talks to your API into software products. It works by calling API endpoints which you choose to expose to it. This lets the chatbot complete tasks within your software in response to natural language queries. It’s also open source, so you don’t have to send user data to another 3rd party. We support Llama 2, but we haven’t fine-tuned Llama 2 yet (coming soon) so highest accuracy is seen with GPT-4 or fine-tuned GPT-3.5 (much faster). We started working together 2…
2023 · github.com
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Hey HN, I've been working on something cool that I wanted to share with you all. It's called Viewpoint, an analytics tool for LLMs like OpenAI, Anthropic models, and Gemini. The idea came from the constant flood of new LLM models and the need to figure out which ones work best for my projects without breaking the bank. With viewpoint, I can track token usage, costs, latency(WIP), and traffic over time, making it easier to compare different models and see which ones perform best and save money. The tool works asynchronously, so it doesn't add any latency to your LLM requests, and you have…
2024 · viewpointhq.com
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2024 · github.com
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Hi HN! I lead product at Vectara and we've just released a new LLM in our platform that outperforms GPT4 and Gemini 1.5 Pro on RAG tasks. Vectara is a Retrieval Augmented Generation (RAG) platform primarily deployed as a SaaS service which includes a generous free tier so you can try it for free. The way we've been able to offer a "better but cheaper" is that we focus a lot of our attention on taking smaller models (which can be hosted in a cost efficient way) and fine tuning them to specific tasks: in this case RAG. This ends up with a model that is less capable of arbitrary tasks like…
2024 · vectara.com
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Post-Opus 4.6, LLMs feel much better at using bash, code, local files, and tools. So I kept coming back to a simple question: if a model can use a computer reasonably well, why can’t I just give it my broker account, a strategy, and let it trade? My conclusion is that the blocker is not model capability in the abstract. It is the system around the model. A raw LLM breaks on a few practical things almost immediately: • no persistent operating memory across sessions • no trustworthy record of what it did and why • no hard approval boundary before money moves • no cheap always-on monitoring if…
Mar 2026 · github.com
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I’ve been building LLM tooling for a small VC fund and found myself explaining the same mental model over and over to non-technical people around me: how a stateless LLM becomes a chatbot, how tool use works, what an agent is mechanically, and why context windows shape all of it. I never found a guide that covered that full chain at the level I wanted, so I wrote one. It’s nine short chapters, each building on the last. Deliberately simplified: the goal is a useful mental model, not a textbook. Feedback, corrections, and contributions welcome: github.com/ymyke/aiaiai
Apr 2026 · aiaiai.guide
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Multiple models respond simultaneously, pick your answer
Jan 2026 · unichatgpt.com
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Hi HN! I built LLM OneStop (https://www.llmonestop.com), a unified interface for accessing multiple AI language models in one place. The main problem I wanted to solve: constantly switching between different AI platforms, managing multiple subscriptions, and losing conversation context when comparing outputs across models. Key features: Switch between GPT-4, Claude, Gemini, Llama, and other models mid-conversation Compare responses side-by-side Single interface instead of juggling multiple tabs/subscriptions Free tier available to try it out (no credit card needed) "Connect"…
Nov 2025 · llmonestop.com
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