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mozilla-ai
llamafile
C++2023–2026
mozilla-ai / llamafile

llamafile

Distribute and run LLMs with a single file.

82Distinct people
112Mentions
3Explicit recommenders
26.6KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Distribute and run LLMs with a single file.

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

Handy is an awesome project, highly recommended - many of our engineers and PMs use it! CJ, Handy's creator, recently joined us as a Builder in Residence at Mozilla.ai. So for…

JohnPDickerson used a recommendation phrase. 3 indexed comments match. This is a phrase match, not a verdict.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 6:36:16 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year112 dated mentions

Observed mentions: 2023-11-29 19:29:49 UTC to 2026-10-27 20:17:14 UTC.

02040602023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 26 mentions; 2 submissions, 24 comments20232024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 62 mentions; 5 submissions, 57 comments20242025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 19 mentions; 3 submissions, 16 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 5 mentions; 0 submissions, 5 comments. Incomplete calendar period.2026*

* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC26224
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC62557
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC19316
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC505

From the project README

An excerpt from the repository, fetched Nov 12, 2026.

Read the project’s introduction
llamafile llamafile lets you distribute and run LLMs with a single file. llamafile is a Mozilla Builders project (see its announcement blog post), now revamped by Mozilla.ai. Our goal is to make open LLMs much more accessible to both developers and end users. We're doing that by combining llama.cpp with Cosmopolitan Libc into one framework that collapses all the complexity of LLMs down to a single-file executable (called a "llamafile") that runs locally on most operating systems and CPU architectures, with no installation. llamafile also includes whisperfile, a single-file speech-to-text tool built on whisper.cpp and the same Cosmopolitan packaging. It supports transcription and translation of audio files across all the same platforms, with no installation required. v0.10.* llamafile versions starting from 0.10.0 use a new build system, aimed at keeping our code more easily aligned with the latest versions of llama.cpp. This means they support more recent models and functionalities, but at the same time they might be missing some of the features you were accustomed to (check out this doc for a high-level description of what has been done). If you liked the "classic experience" more, you will always be able to access the previous versions from our releases page. Our pre-built llamafiles always show which version of the server they have been bundled with (0.9.* example, 0.10.* example), so you will always know which version of the software you are downloading. We want to hear from you! Whether you are a new user or a long-time fan, please share what you find most valuable about llamafile and what would make it more useful for you. Read more via the blog and add your voice to the discussion here. Quick Start Download and run your first llamafile in minutes: # Download an example model (Qwen3.5 0.8B) curl -LO https://huggingface.co/mozilla-ai/llamafile_0.10/resolve/main/Qwen3.5-0.8B-Q8_0.llamafile # Make it executable (macOS/Linux/BSD) chmod +x Qwen3.5-0.8B-Q8_0.llamafile # Run it ./Qwen3.5-0.8B-Q8_0.llamafile We chose this model because that's the smallest one we have built a llamafile for, so most likely to work out-of-the-box for you. If you have powerful hardware and/or GPUs, feel free to choose larger and more expressive models which should provide more accurate responses. Windows users: Rename the file to add .exe extension before running. Note - Only executables under 4GB can run on Windows, so any llamafile above 4GB won't work. Download the llamafile binary and run it with any external weights/models(GGUF). Documentation Check the full documentation at docs.mozilla.ai/llamafile, or directly jump into one of the following subsections: Quickstart Pre-built llamafiles Running a llamafile Creating llamafiles Source installation Technical details Supported Systems Troubleshooting Whisperfile Licensing While the llamafile project is Apache 2.0-licensed, our changes to llama.cpp and whisper.cpp are licensed under MIT (just like the projects themselves) so as to remain compatible and upstreamable in the future, should that be desired. The llamafile logo on this page was generated with the assistance of DALL·E 3.
Read the full README on GitHub

What Hacker News says

26 sources
You can download the llamafile executables from Mozilla's release page here: https://github.com/Mozilla-Ocho/llamafile/releases and then use the `-m` flag which lets you load any GGUF weights you want from Hugging Face. A lot of people I know will also just rent a VM with an H100 for a few hours from a company like vast.ai, SSH into it, don't care about its security, and just want to have to wget the fewest files possible. Everyone's threat vector is different. That's why llamafile provides multiple choices so you can make the right decision for yourself. It's also why I like to focus on simply just making things easy, because that's one place where we can have an impact building positive change, due to how the bigger questions e.g. security are ultimately in the hands of each individual.
In Emacs-copilot: Large language model code completion for Emacs
llamafile is designed with the hope of being a permanently working artifact where upgrades are optional. You can upgrade to new llamafile releases in two ways. The first, is you can redownload the full weights I re-upload to Hugging Face with each release. However you might have slow Internet. In that case, you don't have to re-download the whole thing to upgrade. What you'd do instead, is first take a peek inside using: unzip -vl wizardcoder-python-13b-main.llamafile [...] 0 Stored 0 0% 03-17-2022 07:00 00000000 .cosmo 47 Stored 47 0% 11-15-2023 22:13 89c98199 .args 7865963424 Stored 7865963424 0% 11-15-2023 22:13 fba83acf wizardcoder-python-13b-v1.0.Q4_K_M.gguf 12339200 Stored 12339200 0% 11-15-2023 22:13 02996644 ggml-cuda.dll Then you can extract the original GGU
Read the rest
F weights and our special `.args` file as follows: unzip wizardcoder-python-13b-main.llamafile wizardcoder-python-13b-v1.0.Q4_K_M.gguf .args You'd then grab the latest llamafile release binary off https://github.com/Mozilla-Ocho/llamafile/releases/ along with our zipalign program, and use it to insert the weights back into the new file: zipalign -j0 llamafile-0.4.1 wizardcoder-python-13b-v1.0.Q4_K_M.gguf .args Congratulations. You've just created your first llamafile! It's also worth mentioning that you don't have to combine it into one giant file. It's also fine to just say: llamafile -m wizardcoder-python-13b-v1.0.Q4_K_M.gguf -p 'write some code' You can do that with just about any GGUF weights you find on Hugging Face, in case you want to try out other models. Enjoy!
In Emacs-copilot: Large language model code completion for Emacs
Yes you need to install CUDA and MSVC for GPU. But here's some good news! We just rolled our own GEMM functions so llamafile doesn't have to depend on cuBLAS anymore. That means llamafile 0.4 (which I'm shipping today) will have GPU on Windows that works out of the box, since not depending on cuBLAS anymore means that I'm able to compile a distributable DLL that only depends on KERNEL32.DLL. Oh it'll also have Mixtral support :) https://github.com/Mozilla-Ocho/llamafile/pull/82
In Bash one-liners for LLMs
It's so great. I've been this vision model to rename all the files in my Pictures folder. For example, the one-liner: llamafile --temp 0 \ --image ~/Pictures/lemurs.jpg \ -m llava-v1.5-7b-Q4_K.gguf \ --mmproj llava-v1.5-7b-mmproj-Q4_0.gguf \ --grammar 'root ::= [a-z]+ (" " [a-z]+)+' \ -p $'### User: What do you see?\n### Assistant: ' \ --silent-prompt 2>/dev/null | sed -e's/ /_/' -e's/$/.jpg/' Prints to standard output: a_baby_monkey_on_the_back_of_a_mother.jpg This is something that's coming up in the next llamafile release. You have to build from source to have the ability to use grammar and --silent-prompt on a vision model right now. Weights here: https://huggingface.co/jartine/llava-v1.5-7B-GGUF/tree/main Sauce here: https://github.com/mozilla-Ocho/llamafile
In Show HN: I Remade the Fake Google Gemini Demo, Except Using GPT-4 and It's Real

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