Life & fun · alternatives · 2026
24 alternatives to FrontierHarness Eval – 9 harness, same model, cost per pass varies 17x
Same model. Similar pass rates. 17.5x cost differences across 12 harness configurations.
FrontierHarness Eval is a testing tool that evaluates different harness configurations for software engineering tasks using a single model across identical conditions. It tracks performance metrics and costs across 9… 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 2 we have checked on their own sites, 2 of them free or with a free tier.
- 1
LLM Stats▲293I was overspending on GPT-4o. It was really hard to compare different models I could switch to, so I built this LLM comparison tool. It shows leaderboards, pricing, and performance data across 100+ LLMs (including all major providers and open-source models). Key features: - Live pricing comparisons - Benchmark Scores (MMLU, HumanEval, GPQA, etc.) - Context length vs cost analysis - Speed/throughput tests across providers - Quality vs price visualizations - Open source (all data verifiable) Try it out: https://llmstats.com I'd like to know your opinion :) Tech stack: Next.js,…
Oct 2025 · llm-stats.com · its alternatives →
- 2
HarnessRouter Community Editionfree tier, from $20/mo▲397Open-source unified interface for agent harnesses
Aug 2026 · harnessrouter.ai · its alternatives →
- 3
LLM Pricing▲178LLMs price comparison tool developed and updated by LLM
2024 · ailesson.io · its alternatives →
- 4
Hi HN! We’re been working hard on this low-code tool for rapid prompt discovery, robustness testing and LLM evaluation. We’ve just released documentation to help new users learn how to use it and what it can already do. Let us know what you think! :)
2023 · chainforge.ai · its alternatives →
- 5
Harness by Autonomousfree tier, from $149/mo▲295Every coding agent, every machine, one command center.
9d ago · autonomous.ai · its alternatives →
- 6
Hey HN! Tokencost is a utility library for estimating LLM costs. There are hundreds of different models now, and they all have their own pricing schemes. It’s difficult to keep up with the pricing changes, and it’s even more difficult to estimate how much your prompts and completions will cost until you see the bill. Tokencost works by counting the number of tokens in prompt and completion messages and multiplying that number by the corresponding model cost. Under the hood, it’s really just a simple cost dictionary and some utility functions for getting the prices right. It also accounts for…
2024 · github.com · its alternatives →
- 7
Hey HN, We got tired of browser frameworks restricting the LLM, so we removed the framework and gave the LLM maximum freedom to do whatever it's trained on. We gave the harness the ability to self correct and add new tools if the LLM wants (is pre-trained on) that. Our Browser Use library is tens of thousands of lines of deterministic heuristics wrapping Chrome (CDP websocket). Element extractors, click helpers, target managemenet (SUPER painful), watchdogs (crash handling, file downloads, alerts), cross origin iframes (if you want to click on an element you have to switch the target first,…
Apr 2026 · github.com · its alternatives →
- 8
Tokenwise▲143A smart LLM proxy that shows where you're overpaying
Jun 2026 · tokenwisehq.com · its alternatives →
- 9
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 · its alternatives →
- 10
- 11
One key to access every coding model in 3 flat prices
May 2026 · devpass.llmgateway.io · its alternatives →
- 12
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 →
- 13
WarpGrep▲114I review PRs all day and I've basically stopped reading them. Someone opens a 2000-line PR, I scroll, see it's mostly AI-generated React components, leave a comment, merge. I felt bad about it until I realized everyone on my team does the same thing. The problem is diffs are the wrong format. A PR might change how three buttons behave. Staring at green and red lines to understand that is crazy. The core reason we built this is that we feel that products today are built with assumptions from the past. 100x code with the same review systems means 100x human attention. Human attention cannot…
Dec 2025 · morphllm.com · its alternatives →
- 14
A collection of open-source TypeScript tools by @enmanuelmag. heimdall-mcp for MCP proxy telemetry. agent-harness-kit for multi-agent orchestration.
May 2026 · ahk.cardor.dev · its alternatives →
- 15
Convert your vector embeddings into a set of questions and their ideal responses. Use this dataset to test your LLM and catch failures caused by prompt or RAG updates. Get started in 3 lines of code: ``` pip3 install fiddlecube ``` ``` from fiddlecube import FiddleCube fc = FiddleCube(api_key="") dataset = fc.generate( [ "The cat did not want to be petted.", "The cat was not happy with the owner's behavior.", ], 10, ) dataset ``` Generate your API key: https://dashboard.fiddlecube.ai/api-key # Ideal QnA datasets for testing, eval and training LLMs Testing, evaluation or…
2024 · github.com · its alternatives →
- 16
A test runner for agentskills.io-style AI agent skills - darkrishabh/agent-skills-eval
May 2026 · github.com · its alternatives →
- 17
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 · its alternatives →
- 18
- 19
A safe eval library based on WebAssembly and Duktape/QuickJS. - maple3142/wasm-jseval
2020 · github.com · its alternatives →
- 20
We launched Infracost on HN five years ago (https://news.ycombinator.com/item?id=26064588) where our CLI generated cost estimates for infra-as-code, e.g. "this Terraform PR adds $400/mo". The idea was to shift cloud costs (FinOps) left, so engineers get visibility of costs before deployment and make better decisions. Earlier this year we started seeing agent traffic in our logs and it looked like coding agents were calling our CLI. But that CLI wasn't designed with coding agents in mind. We went down a philosophical rabbit hole to see if a CLI is even needed anymore given…
Jun 2026 · cost.dev · its alternatives →
- 21
The LLM Evaluation Framework. Contribute to confident-ai/deepeval development by creating an account on GitHub.
2023 · github.com · its alternatives →
- 22
Hey HN! We are building HarnessRouter, a canonical API for running Codex, Claude Code, Hermes, and other managed agent harnesses as your product backend. Before building HarnessRouter, I used to build our own agent harness for our products. I tried LangGraph, agent SDKs from different vendors, pydantic, LLM tool use / function call, and so on. It's a very heavy lifting engineering effort, and I am disappointed about the agent deliveries compared to what Codex, CC can deliver. That changed my mindset. The frontier labs and famous open source communities are already putting so much…
Aug 2026 · github.com · its alternatives →
- 23
100% bootstrapped new startup. It lets you fine tune Mistral-7B and SDXL. In particular, for the LLM fine tuning we implemented a dataprep pipeline that turns websites/pdfs/doc files into question-answer pairs for training the small LLM using an big LLM. It includes a GPU scheduler that can do finegrained GPU memory scheduling (Kubernetes can only do whole-GPU, we do it per-GB of GPU memory to pack both inference and fine tuning jobs into the same fleet) to fit model instances into GPU memory to optimally trade off user facing latency with GPU memory utilization It's a pretty…
2023 · docs.helix.ml · its alternatives →
- 24
Zenith is our long-running agent harness. On Frontier SWE — seventeen of the hardest public long-horizon software-engineering tasks we know of — Zenith took GPT-5.5 from 5th place to 1st, ahead of Claude Fable, by building the right harness around the model instead of swapping in a bigger one.
Jun 2026 · ii.inc · its alternatives →
Also compare
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 →