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Ggml Alternatives
Similar projects and alternatives to ggml
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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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Open-Assistant
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
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petals
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
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RWKV-LM
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.
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open_llama
OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA 7B trained on the RedPajama dataset
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llm
Discontinued [Unmaintained, see README] An ecosystem of Rust libraries for working with large language models (by rustformers)
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dolly
Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform
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Whisper
High-performance GPGPU inference of OpenAI's Whisper automatic speech recognition (ASR) model (by Const-me)
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FlexGen
Discontinued Running large language models like OPT-175B/GPT-3 on a single GPU. Focusing on high-throughput generation. [Moved to: https://github.com/FMInference/FlexGen] (by Ying1123)
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RedPajama-Data
The RedPajama-Data repository contains code for preparing large datasets for training large language models.
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better ggml alternative or higher similarity.
ggml discussion
ggml reviews and mentions
Posts with mentions or reviews of ggml.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2026-03-04.
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Local LLM Inference on Windows 11 and AMD GPU using WSL and llama.cpp
Manifesto / ggml / ops
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Ollama Turbo
It’s a different repo. https://github.com/ggml-org/ggml
The models are implemented by Ollama https://github.com/ollama/ollama/tree/main/model/models
I can say as a fact, for the gpt-oss model, we also implemented our own MXFP4 kernel. Benchmarked against the reference implementations to make sure Ollama is on par. We implemented harmony and tested it. This should significantly impact tool calling capability.
Im not sure if im feeding here. We really love what we do, and I hope it shows in our product, in Ollama’s design and in our voice to our community.
You don’t have to like Ollama. That’s subjective to your taste. As a maintainer, I certainly hope to have you as a user one day. If we don’t meet your needs and you want to use an alternative project, that’s totally cool too. It’s the power of having a choice.
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Xiaomi unveils open-source AI reasoning model MiMo
One of the core design goals Georgi Gerganov had with GGUF was to not need other files. It's literally bullet point #1 in the specs
>Single-file deployment
>Full information: all information needed to load a model is contained in the model file, and no additional information needs to be provided by the user.
https://github.com/ggml-org/ggml/blob/master/docs/gguf.md
We literally just got rid of that multi file chaos only for ollama to add it back :/
- Train a Mnist VAE with C and CUDA
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LLM Evaluation: Which LLM to use for developing a personal assistant?
All models of 3B and 7B size were run locally with Ollama. The 7B+ models were used with a Kaggle notebooks and a suitable gguf model file loaded with ggml.
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Everything I've learned so far about running local LLMs
I was under the impression that it was simply the file format used by llama.cpp and ggml, name inspired by the name of the author (https://github.com/ggerganov): https://github.com/ggerganov/ggml/blob/master/docs/gguf.md
He prefixes everything with “gg” (his initials).
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Building a local and private LLM server in Rust
llm: This crate provides a unified interface for loading and using Large Language Model. The backend at the time of writing is ggml only https://github.com/ggerganov/ggml.
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LLMs on your local Computer (Part 1)
git clone https://github.com/ggerganov/ggml cd ggml mkdir build cd build cmake .. make -j4 gpt-j ../examples/gpt-j/download-ggml-model.sh 6B
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GGUF, the Long Way Around
Cool. I was just learning about GGUF by creating my own parser for it based on the spec https://github.com/ggerganov/ggml/blob/master/docs/gguf.md (for educational purposes)
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Ask HN: People who switched from GPT to their own models. How was it?
If you don't care about the details of how those model servers work, then something that abstracts out the whole process like LM Studio or Ollama is all you need.
However, if you want to get into the weeds of how this actually works, I recommend you look up model quantization and some libraries like ggml[1] that actually do that for you.
[1] https://github.com/ggerganov/ggml
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A note from our sponsor - SaaSHub
www.saashub.com | 13 Jun 2026
Stats
Basic ggml repo stats
76
14,803
9.9
1 day ago
ggml-org/ggml is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of ggml is C++.
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