Show HN: Ante, a coding agent in a single binary that runs offline
github.com
github.com
This is a coding agent implementation I am working on, which delivers what this promises (at least on the "lean" part), except it's actually fully open source, and even more lean (few MBs of runtime memory usage).
MIT-licensed, written in C, multi-provider / multi-model, minimalist approach to system prompt and tools (think kinda like pi, but with a bit more "batteries included", like subagents and background tasks out of the box), polished presentation, inspectable (usable transcript view), etc.
Also, security aside, engineers want the freedom to modify and experiment with the tools we rely on.
Tools like this are too important to be closed. Do you want to be Internet Explorer or Firefox?
How do you think the backdoor situation would have been resolved if xz hadn't been open-source?
https://github.com/smol-env/smol
here are traces from an agentic task around using duckduckdb
comparing CPU and RAM usage of the whole container over time w/ OpenCode, hermes, pi, codex, smol
https://x.com/__tosh/status/2086882367126286466
https://x.com/__tosh/status/2086882204060160350
smol is very minimal only using stdlib (in this case it is the go version but you can also take a look at implementations in python, clojure, php)
(any OpenAI Responses API compatible endpoint works, if your endpoint does not support 'custom' tools you can have your agent change the smol implementation to use 'function' tool implementation instead)
that said: be aware that smol does not come with any system prompt and does not load agents.md files by default
some older not so strong models benefit from a system prompt and guidance in agents.md that complements them
that said 2: system prompt and or loading agents.md automatically is easy to add though if you want it
I can’t even guess what this means
But from a fellow engineer's perspective we don't need another commercial solution in this space. Every major tech vendor is working on harnesses, and we will get ones that will run circles around yours for free. The open source ones that get popular will have mit/freebsd/etc permissive licenses. (or no one will adopt them) But coming at it from the angle you are indicates you haven't reasoned well about this. Please don't hurt yourself and those around you by starting a startup on this idea.
Yes the core part is a simple loop, but we have all built toy compilers, inference engine, browsers (it is just a curl command eth) etc. The core algorithm is supposed to be simple.
Had a discussion recently: https://x.com/NoCommas/status/2086568454434537710?s=20
I wonder if this is a viable approach; after all frontier model providers are betting on the opposite.
Then again, they bundle their harness and offer subsidiary pricing - so maybe they themselves aren’t sure if models are as important.
Had a discussion recently: https://x.com/NoCommas/status/2086568454434537710?s=20
A coding agent is more like a carpenter, a mason, an electrician,... rather than a hammer in that case.
One could even argue what defines AI instructability is heuristics as opposed to specifics
And you won't get purity tests from the layperson: in the end, you're responsible for the build quality so if you tirelessly labor/oversee those teams you're considered capable; if it ends sub-par, then you're a stooge.
Really? Last time I checked, other tools can operate without ripping off the works of millions of humans.
"I thought using loops was cheating, so I programmed my own using samples. I then thought using samples was cheating, so I recorded real drums. I then thought that programming it was cheating, so I learned to play drums for real. I then thought using bought drums was cheating, so I learned to make my own. I then thought using premade skins was cheating, so I killed a goat and skinned it. I then thought that that was cheating too, so I grew my own goat from a baby goat. I also think that is cheating, but I’m not sure where to go from here. I haven’t made any music lately, what with the goat farming and all."
So sometimes when I want to hear what my song COULD be if I were good at every one of those, I will use Suno. But I do not let it change my lyrics, or chose it's own arrangement. I will give it a VERY ROUGH demo (out of key singing, basic drums and strums, and it will "polish" my turds into really shiny turds.
The problem being that the users of LLMs aren't even putting forth the effort to do the stealing themselves, which would at least have implied some level of discernment and artistic effort in selecting what to steal.
Like bad managers stealing credit for their subordinates' hard work, bad LLM advocates wish to normalize taking credit for the work the LLM does on their behalf.
Compare/contrast: people who develop games on top of high-level genre-specific game engines like RPG Maker are still considered to be "building a game." What's the difference between using a pre-made purpose-fit engine like RPG Maker, vs. asking an AI (or, for that matter, a contracted software company) to build you a custom purpose-fit engine?
They can one shot entire games, with relatively minor issues.
And obviously asking for small code snippets and integrating them yourself has been well supported for five years.
But in Agent mode... not so much. I was asking frontier models to make simple changes to my Pong game (you know like the one from 1972) and it constantly failed to make simple changes or would break something else in the process.
The main issue is that they can't see what they're doing. Actually one of the agents tried playing the pong game by screenshotting every frame, and it ran for about 20 minutes before I realized what it was doing, and told it to calm down.
It takes about 10 seconds to process an image, so it was running the game at 0.1 frames per second... 600x slower than realtime. The technology is not quite there yet.
If your game is something turn-based though, with discrete States and well-defined transitions between them, they can help out a lot more with that.
But I am curious about building a larger scale game with/without professional engines like Godot. I highly doubt the model/agent is intelligent enough to setup the entire development environment correctly, thus may be struggle to test and debug themselves. Maybe something like GUI-agent a future?
It's not true as a general rule that they could give you correct small code snippets five years ago; I had frontier models not even understanding enough of the OpenGL API to make separate framebuffers correctly. I asked this as a test and the resulting recommended code would of course compile, but leave someone who didn't already know the correct way to do it staring at a black screen and potentially spending the next hour debugging that.
If you think you're somehow going to make an actual game worthy of people's time with LLMs, you are almost certainly mistaken. Not only because it'll be a complete, unworkable mess with really bad fundamentals, but also because if you're vibecoding the actual technical part you probably also think game design is just about "having ideas" or something else that's really reductive and incorrect.
Wait til you see the code for some of the best selling games of all time ;)
Opt-out every time is unacceptable. If you opt out once it should be enough. One accidental execution path without the right environment and you're spewing telemetry to spaghetti knows where.
That would also be true with opt-in by environment variable, though.
as for why stop here yep, the goal is to be able to find the best sweet spot in being self contained v.s. all-in-one bloat ware. for example, we still use a bundled `tmux` skill for the orchestration.
Harness is compute and Model is data
Fuck you. Will there ever be a decent agent where the answer to this is "No"?
- Ante installs a pinned, checksum-verified official llama.cpp build matched to your machine (Metal on Apple silicon; CUDA, Vulkan, or CPU on Linux) and handles upgrades when the pin changes. - It discovers GGUF files already on disk (~/.ante/models, the llama.cpp and Hugging Face caches), attaches to llama servers already running on local ports, and estimates RAM/VRAM from model size and context window before anything loads. - `ante --offline-model /path/to/model.gguf "prompt"` boots the server, runs the session, and shuts it down. `/offline-mode` does the same interactively; `ante serve --offline-model` loads a model once for many clients. - No API key, no account. Once the model is on disk, inference needs no network at all; set ANTE_TELEMETRY=off and no telemetry is exported either.
On capability, we'd rather publish the number than oversell: we benchmark local models with the same harness and auditable runs as frontier ones, and Qwen3.6 27B (a 17 GB download) scores 56.2% on Terminal-Bench 2.1 across 445 trials (live results: https://antigma.ai/eval). That's a real gap from frontier models. The design bet is that you mix: hosted providers and local live in the same catalog, `/providers` switches mid-session, so sensitive repos or high-volume work go local and hard problems go frontier.
Hosted models work with your own keys or subscription. But nothing about trying Ante requires signing up for anything: download the binary, point it at a GGUF.
Offline mode is under active development and has rough edges with the overview at https://ante.run/local/overview. I'll be in the comments.
> Ante installs a pinned, checksum-verified official llama.cpp
But in README: > Ante ships its own inference engine
May I suggest you use the first phrasing in both places. I took it as Ante devs had written their own engine and I doubt I'm the only one.