AI · alternatives · 2026
24 alternatives to Radal
The fastest way to fine-tune and ship LLMs with no-code.
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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Qwen3.5 Small▲3550.8B-9B native multimodal w/ more intelligence, less compute
Mar 2026 · huggingface.co · its alternatives →
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Pylar▲502Hey HN! We're Hoshang & Vishal, the team behind Pylar - a governed access layer between databases and LLMs. We previously led data and AI and we kept seeing the same problem across teams using LLMs internally: agents are great with unstructured data, but the moment you want them touching your actual systems of record — Snowflake, Postgres, CRMs, product DBs — everything becomes fragile, risky, or outright unsafe. Two issues show up every single time: 1. Agents over-querying They don’t understand cost. They’ll happily generate queries that blow up your warehouse bill. 2. Accidental data…
Dec 2025 · pylar.ai · its alternatives →
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Compare AI models easily! All providers in one place. Find the best LLM for your needs with our comprehensive pricing calculator and feature comparison tool. OpenAI, Anthropic, Google, and more.
2024 · countless.dev · its alternatives →
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Dify.AI▲261Open-source platform for LLMOps, define your AI-native apps
2023 · dify.ai · its alternatives →
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Fine-tuning, RL, and inference in one CLI
Dec 2025 · github.com · its alternatives →
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LLM reinforcement fine-tuning platform to improve LLM output
2025 · rubrik.com · its alternatives →
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Fine-Tuner.ai▲218The ultimate no-code solution for building AI agents
2023 · fine-tuner.ai · its alternatives →
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Fast LLMs for low-latency and high-performance workflows
Jun 2026 · jetbrains.com · its alternatives →
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TL;DR: Vector-based RAG performs poorly for many real-world applications like codebase chats, and you should consider 'language maps'. Part of our mission at Mutable.ai is to make it much easier for developers to build and understand software. One of the natural ways to do this is to create a codebase chat, that answer questions about your repo and help you build features. It might seem simple to plug in your codebase into a state-of-the-art LLM, but LLMs have two limitations that make human-level assistance with code difficult: 1. They currently have context windows that are too small to…
2024 · twitter.com · its alternatives →
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Fine-tune LLMs from one YAML. Layer streaming trains an 8B model on a 4 GB laptop GPU. - MakazhanAlpamys/Soup
Aug 2026 · github.com · its alternatives →
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TuneTrain.ai▲79Do you know that Small Language Models (SLM) can outperform LLMs if trained (fine-tuned) on domain specific datasets, like your companies knowledge base? The issue: fine-tuning a SLM usually requires a dataset of 10k - 100k records, which is huge. I created a platform for applying "human in the loop" augmentation techniques on your small dataset, so that you can start with maybe 100 records and build-up quickly huge datasets and launch a training without prior knowledge. I implemented 2 techniques, based on LLM distillation, however: more to come. HN, what Do you think? Do you see value in…
2025 · tunetrain.ai · its alternatives →
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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 · its alternatives →
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LLM alternative with instant & real-time fine-tuning
2024 · its alternatives →
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FinetuneDB▲52AI fine-tuning platform to create custom LLMs
2024 · finetunedb.com · its alternatives →
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I’ve been working on AnyModal, a framework for integrating different data types (like images and audio) with LLMs. Existing tools felt too limited or task-specific, so I wanted something more flexible. AnyModal makes it easy to combine modalities with minimal setup—whether it’s LaTeX OCR, image captioning, or chest X-ray interpretation. You can plug in models like ViT for image inputs, project them into a token space for your LLM, and handle tasks like visual question answering or audio captioning. It’s still a work in progress, so feedback or contributions would be great. GitHub:…
2024 · github.com · its alternatives →
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2023 · github.com · its alternatives →
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Hello all! Very happy to share this toolkit that allows you to fine-tune your choice of open-source LLMs on your data! The toolkit also allows you to run ablation studies across LLMs, prompt designs, training configurations, and can ingest different data files -- all through just ONE YAML file! After fine-tuning, you can also run a bunch of tests to ensure that the fine-tuned LLM behaves as expected, enabling faster time-to-production! Why this toolkit? Why now? While closed-source LLMs have become popular for chat-based applications, enterprises are considering a shift to self-hosted SLMs…
2024 · github.com · its alternatives →
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Please forgive the sign up. It means we can give away and keep track of free inference usage/no API keys needed. Happy to send sign in credentials on request if you prefer.
2025 · enginelabs.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 →