AI · alternatives · 2026
24 alternatives to Open Benchmarks Grants– a $3M commitment to close the AI eval gap
Today, we're launching the Open Benchmarks Grants: a $3M commitment to fund open-source and academic teams building benchmarks for AI agents. In partnership with HuggingFace, PrimeIntellect, FactoryHQ, Together, Harbor, and PyTorch, the grants provide funding, data development support, and research collaboration. Our ability to measure AI has been outpaced by our ability to develop it, and we believe this evaluation gap is one of the most important problems in AI. Open benchmarks are one of the most important levers for advancing AI safely and responsibly—but the academic and open-source…
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
- 1AG
Hi HN, Last year, we launched a non-profit AI research lab called AI Grant (http://aigrant.org). Our goal is to fund promising people around the world working on AI. No strings attached. We've since given away over $100,000 to 30 teams working on different projects. You can see some of them here: http://aigrant.org/#finalists. We just started accepting applications for our third batch! The academic grant application process is burdensome. It's only avalible to a choice few. Applications take days to complete. AI Grant is open to anyone on the internet. You can apply…
2018 · its alternatives →
- 2
oqoqo▲325Most benchmarks today exist in curated environments and do not translate well to the real world. We built Oqoqo to bridge this gap. Oqoqo makes it super simple to build realistic evals and custom benchmarks for tasks users actually care about. Oqoqo can: - Reliably measure how agent friendly your product surfaces are against Codex, Claude Code, OpenClaw, Hermes, Pi, Opencode, Cursor, GitHub Copilot - Regression test MCP, CLI, skills, SDK, and any agent facing interface (we are continuously using Oqoqo to dogfood and improve our own MCP/CLI) - Create and share custom benchmarks for how…
Aug 2026 · oqoqo.ai · its alternatives →
- 3
APIEval-20▲121An open benchmark for AI agents that test APIs
May 2026 · resources.kusho.ai · its alternatives →
- 4AT
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 · its alternatives →
- 5
Context Gateway▲220We built an open-source proxy that sits between coding agents (Claude Code, OpenClaw, etc.) and the LLM, compressing tool outputs before they enter the context window. Demo: https://www.youtube.com/watch?v=-vFZ6MPrwjw#t=9s. Motivation: Agents are terrible at managing context. A single file read or grep can dump thousands of tokens into the window, most of it noise. This isn't just expensive — it actively degrades quality. Long-context benchmarks consistently show steep accuracy drops as context grows (OpenAI's GPT-5.4 eval goes from 97.2% at 32k to 36.6% at 1M…
Mar 2026 · github.com · its alternatives →
- 6
Find the best active AI software & compute grants & credits
2025 · hackernoon.ai · its alternatives →
- 7
We’re excited to share ML-Dev-Bench, a new open-source benchmark that tests AI agents on real-world ML development tasks. Unlike typical coding challenges or Kaggle-style competitions, our benchmark simulates end-to-end ML workflows including: - Dataset handling and preprocessing - Debugging model and code failures - Implementing new model architectures - Fine-tuning and improving existing models With 30 diverse tasks, ML-Dev-Bench evaluates agents across critical stages of ML development. To complement this, we built Calipers, a framework that provides systematic performance evaluation and…
2025 · github.com · its alternatives →
- 8
An open-source benchmark of how much code AI models add.
9d ago · parsimony.lasu.dev · its alternatives →
- 9
I built BenchFlow, an open-source framework that lets you integrate and evaluate AI tasks using Docker-based benchmarks. You can try it out right now by cloning the repo and running a benchmark in minutes. As an AI researcher, I was frustrated with how much time my team spent setting up benchmark environments rather than actually improving our models. We'd spend weeks configuring environments, only to find inconsistencies when comparing results with other teams. BenchFlow started as an internal tool to standardize our evaluation process, and we decided to open-source it after seeing how much…
2025 · github.com · its alternatives →
- 10
Hey HN, Automated research is the next big step in AI, with companies like OpenAI aiming to debut a fully automated researcher by 2028 (https://www.technologyreview.com/2026/03/20/1134438/openai-i...). However, there is a very real possibility that much of this corporate research will remain closed to the general public. To counter this, we spent the last month building Enlidea---a machine-to-machine ecosystem for open research. It's a decentralized research hub where autonomous agents propose hypotheses, stake bounties, execute code, and perform automated…
Mar 2026 · enlidea.com · its alternatives →
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ml-intern▲91Hugging Face's AI agent that automates post-training
Apr 2026 · smolagents-ml-intern.hf.space · its alternatives →
- 13
I'm Fenil, co-founder/CEO of OpenFunnel (YC F24), building this with my co-founder/CTO Aditya. We're launching OpenBenchmarks (https://openbenchmarks.com), open-source, reproducible benchmarks for SaaS APIs, starting with the category we know best: GTM APIs. ## Why we built this More and more B2B software evaluation will/already runs through reasoning models inside agentic workflows rather than through people. And buyers increasingly pick vendors that are API-first and ship MCPs, so they can wire them into internal workflows. Strong reasoning models are skeptical of…
Jul 2026 · openbenchmarks.com · its alternatives →
- 14
OpenAI's new mission and what it says about capitalism
2015 · content.blubrry.com · its alternatives →
- 15
Hi all! This morning, we released a new Apache 2.0 licensed model on HuggingFace for detecting hallucinations in retrieval augmented generation (RAG) systems. What we've found is that even when given a "simple" instruction like "summarize the following news article," every LLM that's available hallucinates to some extent, making up details that never existed in the source article -- and some of them quite a bit. As a RAG provider and proponents of ethical AI, we want to see LLMs get better at this. We've published an open source model, a blog more thoroughly describing our methodology (and…
2023 · vectara.com · its alternatives →
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Reproducible benchmarks for evaluating AI models
Aug 2026 · github.com · its alternatives →
- 18
I built a small benchmark to test CLI coding agents on blind bug detection. A challenger agent injects bugs and writes ground truth (`bugs.json`). A different reviewer agent audits the repo without seeing ground truth, and an LLM matcher scores bug-to-finding assignments. Current run: 50 repos, 150 challenges, 450 reviews, 2,603 injected bugs. Weighted detection: Claude 58.05%, Codex 37.84%, Gemini 27.81%. LLM-judge benchmarks are easy to get wrong, so I’d really appreciate critical feedback on benchmark fairness, scoring/matching methodology, and obvious failure modes I’m missing. Full…
Feb 2026 · github.com · its alternatives →
- 19
we had hundreds of discussions with engineering leaders over the past few months, and everyone's trying to understand where they are in the AI journey. we collected all this data into a benchmark and built a free grader to let you know where you stand. you answer on a 1–5 scale (e.g., autonomy runs from "suggestions only" to "agents own multi-hour workflows across code, infra, and external systems") - takes about 5 minutes. https://agent-benchmarks.com/software-factory/ waiting for your results!
Jul 2026 · agent-benchmarks.com · its alternatives →
- 20
Open Source Reliability Harness: Make your agents follow rules. One line of code to enforce, trace, and improve. - GitHub - open-bias/open-bias: Open Source Reliability Harness: Make your agents follow rules. One line of code to enforce, trace, and improve.
Apr 2026 · github.com · its alternatives →
- 21
A vendor-neutral Kubernetes incident benchmark for testing AI investigation tools across detection, diagnosis, and mitigation. Deploy faults, capture investigations, and compare results with a configurable AI judge. - edgedelta/project-arena
14d ago · github.com · its alternatives →
- 22
Hey folks, I’m the creator of WFGY — a semantic reasoning framework for LLMs. After open-sourcing it, I did a full technical and value audit — and realized this engine might be worth $8M–$17M based on AI module licensing norms. If embedded as part of a platform core, the valuation could exceed $30M. Too late to pull it back. So here it is — fully free, open-sourced under MIT. --- ### What does it solve? Current LLMs (even GPT-4+) lack *self-consistent reasoning*. They struggle with: - Fragmented logic across turns - No internal loopback or self-calibration - No modular thought units - Weak…
2025 · github.com · its alternatives →
- 23NA
Hi HN, A few months ago, we announced our AI Grant project. We give $2,500 in cash and $20,000 in GPU training credits to anyone who wants to work on AI research. Today, we're excited to announce our second batch of Fellows! We were flooded with nearly 1,000 applications. Topics were diverse: robotics, NLP, biology, tooling, physics, dataset acquisition, fundamental research and more. The applicants were also diverse, spanning from world-class Google researchers to high school students. Check out https://blog.aigrant.org/new-ai-grant-fellows-43f1c26c13d9 for an overview of the…
2017 · 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 →