AI · alternatives · 2026
24 alternatives to RunLLM
AI that doesn’t just respond—it resolves
RunLLM is an AI support tool built on UC Berkeley research that analyzes logs, code, and documentation to automatically resolve technical issues. Designed for engineering teams, it reduces mean time to resolve by 50%… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier.
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Runbear▲508Custom GPT for your Slack, Teams, HubSpot, Zendesk and more!
2025 · runbear.io · its alternatives →
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Runtimefree tier, from $99/mo▲299Sandboxed coding agents for everyone on your team
May 2026 · runtm.com · its alternatives →
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Hey HN! This is Tim from AnythingLLM (https://github.com/Mintplex-Labs/anything-llm). AnythingLLM is an open-source desktop assistant that brings together RAG (Retrieval-Augmented Generation), agents, embeddings, vector databases, and more—all in one seamless package. We built AnythingLLM over the last year iterating and iterating from user feedback. Our primary mission is to enable people with a layperson understanding of AI to be able to use AI with little to no setup for either themselves, their jobs, or just to try out using AI as an assistant but with *privacy by…
2024 · github.com · its alternatives →
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A few days ago I found myself trying out GLM 5.2 and was really positively impressed. The capabilities and security I was getting from this LLM are similar to those I've gotten from models like Claude or GPT, and this really surprised me. But then I thought, "I wonder how it would work on a normal computer like mine," and above all, "I wonder if it would work without going into OOM on a computer like mine." So I started working with the help of agents to test this possibility. I started converting the model to int4, understanding MTP usage, and if possible implementing DSA for long context.…
Jul 2026 · github.com · its alternatives →
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Hey HN, I am proud to show you guys that I have built an open source alternative to Azure OpenAI services. Azure OpenAI services was born out of companies needing enhanced security and access control for using different GPT models. I want to build an OSS version of Azure OpenAI services that people could self host in their own infrastructure. "How can I track LLM spend per API key?" "Can I create a development OpenAI API key with limited access for Bob?" "Can I see my LLM spend breakdown by models and endpoints?" "Can I create 100 OpenAI API keys that my students could use in a classroom…
2023 · github.com · its alternatives →
- 8WM
Try it out! https://glhf.chat/ Hey HN! We’ve been working for the past few months on a website to let you easily run (almost) any open-source LLM on autoscaling GPU clusters. It’s free for now while we figure out how to price it, but we expect to be cheaper than most GPU offerings since we can run the models multi-tenant. Unlike Together AI, Fireworks, etc, we’ll run any model that the open-source vLLM project supports: we don’t have a hardcoded list. If you want a specific model or finetune, you don’t have to ask us for it: you can just paste the Hugging Face link in and…
2024 · glhf.chat · its alternatives →
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TensorZero▲307Hi 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:…
2025 · github.com · 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 →
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ReachLLM▲214I built ReachLLM, which ranked top 5 in Product Hunt, but it still needs early adopters to improve. The goal of the app is that it's a self-serving SaaS to track, analyze & improve AI search visibility (ChatGPT, Perplexity, Grok, Gemini, DeepSeek, and Claude). The coolest features are: - Brand Visibility to see in numbers, exactly how many times your brand is showing up in all AI models, and compare with the competitors. - GEO Audit that checks through 20 different parameters to show the strengths and weaknesses in terms of all the best practices of GEO (Generative Engine Optimization). - AI…
2025 · reachllm.com · its alternatives →
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LLM-usage observability and monitoring tool
2025 · siloam.ai · its alternatives →
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YourGPT 2.0▲215Today we are launching YourGPT 2.0, an update focused on making support, sales, and operational workflows work together more smoothly in one system. This release improves how workflows are built, how the platform connects to external tools, and how context is maintained across long, multi-channel interactions. AI Studio now makes it much easier to create and refine workflows. You can describe the process you want in natural language and the system generates the full workflow for you. It can also help debug issues by showing what happened at each step and explaining where things went off…
Nov 2025 · yourgpt.ai · its alternatives →
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The Agentrun Workflow DSL. Contribute to Parcha-ai/agentrun development by creating an account on GitHub.
28d ago · github.com · its alternatives →
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We’re Robin, Louis, and Thomas. Pipelex is a DSL and a Python runtime for repeatable AI workflows. Think Dockerfile/SQL for multi-step LLM pipelines: you declare steps and interfaces; any model/provider can fill them. Why this instead of yet another workflow builder? - Declarative, not glue code: you state what to do; the runtime figures out how. - Agent-first: each step carries natural-language context (purpose, inputs/outputs with meaning) so LLMs can follow, audit, and optimize. Our MCP server enables agents to run pipelines but also to build new pipelines on demand. - Open…
Oct 2025 · github.com · its alternatives →
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GateLLM▲13The open-source gateway securing your AI workflows
2025 · gatellm.web.app · its alternatives →
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Playcall▲97The open-source AI alternative to Gong
Aug 2026 · playcall.dphenomenal.com · its alternatives →
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I started leaning in on AI heavily this year, as I wanted to get more done autonomously, but then my token usage climbed dramatically to the point where my weekly quota would run out before the end of the week, sometimes a couple of days into the week. I realised I had to do something about it else I'd have to double my spend. So I decided to start tracking my cost per task type. This revealed that a lot of my spend went to searches/scans or simple things like scouting tasks. I then decided to turn this into a simple CLI tool that can be used to read your OpenAI-style logs locally, and…
Jul 2026 · github.com · its alternatives →
- 20DA
Write a task in plain English. An AI agent runs it on a simulator on your Mac and tells you if a real user could complete it. Save the successful run as a regression check you can replay later.
Aug 2026 · app.deltix.ai · its alternatives →
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Run AI models or workflows on GPUs at a lower cost
2024 · its alternatives →
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When the LLM so ahh you lowk take over its job
Mar 2026 · youraislopbores.me · its alternatives →
- 23LR
I built localLLLM: a small community project for running local models. Live: https://locallllm.fly.dev The goal is simple: if someone has model + OS + GPU + RAM, they should get steps that actually work (ideally one liner) I need help populating and validating guides. If you run local models, please submit one working recipe (or report what failed). Would love to hear general feedback as well!
Apr 2026 · locallllm.fly.dev · its alternatives →
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I've spent the past few years building 50+ AI agents in prod (some reached 1M+ sessions/day), and the hardest part was never building them — it was figuring out why they fail. AI agents don't crash. They just quietly give wrong answers. You end up scrolling through traces one by one, trying to find a pattern across hundreds of sessions. Kelet automates that investigation. Here's how it works: 1. You connect your traces and signals (user feedback, edits, clicks, sentiment, LLM-as-a-judge, etc.) 2. Kelet processes those signals and extracts facts about each session 3. It forms hypotheses…
Apr 2026 · kelet.ai · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →