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Llm Alternatives
Similar projects and alternatives to llm
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textgen
Open-source desktop app for local LLMs. Text, vision, tool-calling, OpenAI/Anthropic-compatible API. 100% private.
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ollama
Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.
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guidance
Discontinued A guidance language for controlling large language models. [Moved to: https://github.com/guidance-ai/guidance] (by microsoft)
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aichat
All-in-one LLM CLI tool featuring Shell Assistant, Chat-REPL, RAG, AI Tools & Agents, with access to OpenAI, Claude, Gemini, Ollama, Groq, and more.
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simpleaichat
Python package for easily interfacing with chat apps, with robust features and minimal code complexity.
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llama-gpt
A self-hosted, offline, ChatGPT-like chatbot. Powered by Llama 2. 100% private, with no data leaving your device. New: Code Llama support!
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llm discussion
llm reviews and mentions
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I benchmarked Python AI-app security scanners. Here's what each catches.
We ran all three (working) tools against simonw/llm, Simon Willison's clean CLI for LLMs, 48 Python files.
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Your text file is the prompt now: LLM's shebang trick
Simon Willison's llm CLI tool already does a lot — run prompts, manage models, call tools, store logs in SQLite. But a Hacker News comment last week sent him down a rabbit hole, and the result is one of those tricks that makes you stop and stare.
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Show HN: GoModel – an open-source AI gateway in Go; 44x lighter than LiteLLM
I've been maintaining an abstraction layer over multiple providers for a couple of years now - https://llm.datasette.io/
The best effort we have to defining a standard is OpenAI harmony/responses - https://developers.openai.com/cookbook/articles/openai-harmo... - but it's not seen much pickup. The older OpenAI Chat Completions thing is much more of an ad-hoc standard - almost every provider ends up serving up a clone of that, albeit with frustrating differences because there's no formal spec to work against.
The key problem is that providers are still inventing new stuff, so committing to a standard doesn't work for them because it may not cover the next set of features.
2025 was particularly turbulent because everyone was adding reasoning mechanisms to their APIs in subtly different shapes. Tool calls and response schemas (which are confusingly not always the same thing) have also had a lot of variance - some providers allow for multiple tool calls in the same response, for example.
My hunch is we'll need abstraction layers for quite a while longer, because the shape of these APIs is still too frothy to support a standard that everyone can get behind without restricting their options for future products too much.
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3 AIs Reviewed the Same Codebase. They Disagreed on 2 Findings. That is the Point.
Simon Willison's llm is one of the better-engineered CLI tools in the Python ecosystem. It has a clean architecture, a comprehensive plugin system, and parameterized SQL throughout. The reviewers independently noted the consistent SQL safety, which speaks to the care that has gone into the project. We pointed our tools at it and filed the findings that survived review.
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Claude Sonnet 4.6 System Card
Took me a while to create the pelican because I was busy adding Opus/Sonnet 4.6 support to my plugin for https://llm.datasette.io/ - pelican now available here, it's not quite as good as the Opus 4.6 one but does look equivalent to the Opus 4.5 one - and it has a snazzy top hat. https://simonwillison.net/2026/Feb/17/claude-sonnet-46/
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AI Doesn't Reduce Work–It Intensifies It
> Has Simon actually produced anything novel or compelling?
Here are some of my recent posts which I self-evaluate as "novel and compelling".
- Running Pydantic’s Monty Rust sandboxed Python subset in WebAssembly https://simonwillison.net/2026/Feb/6/pydantic-monty/ - demonstrating how easy and useful it is to be able to turn Rust code into WASM that can run independently or be used inside a Python wheel for Pyodide in order to provide interactive browser demos of Rust libraries.
- Distributing Go binaries like sqlite-scanner through PyPI using go-to-wheel https://simonwillison.net/2026/Feb/4/distributing-go-binarie... - I think my go-to-wheel utility is really cool, and distributing Go CLIs through PyPI is a neat trick.
- ChatGPT Containers can now run bash, pip/npm install packages, and download files https://simonwillison.net/2026/Jan/26/chatgpt-containers/ - in which I reverse engineered and documented a massive new feature of ChatGPT that OpenAI hadn't announced or documented anywhere
I remain very proud of my current open source projects too - https://datasette.io and https://llm.datasette.io and https://sqlite-utils.datasette.io and a whole lot more: https://github.com/simonw/simonw/blob/main/releases.md
Are you ready to say none of that is "novel or compelling", in good faith?
- Show HN: GenAI Prompts as "Native" Programs
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Don't fall into the anti-AI hype
My great regret from the past few years is that experimenting with LLMs has been such a huge distraction from my other work! My https://llm.datasette.io/ tool is from that era though, and it's pretty cool.
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Ask HN: What's a standard way for apps to request text completion as a service?
When I'm writing a script that requires some kind of call to an LLM, I use this: https://github.com/simonw/llm.
- You Don't Need to Spend $100/Mo on Claude Code:Your Guide to Local Coding Models
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A note from our sponsor - SaaSHub
www.saashub.com | 15 Jun 2026
Stats
simonw/llm is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of llm is Python.