NX-AI/xlstm

Health v2 · maintenance only

Adoption not part of the score

2198 stars · 187 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Official PyTorch implementation of xLSTM, an extended Long Short-Term Memory recurrent architecture with exponential gating and matrix memory, including the xLSTM 7B large language model. It serves as a research library and model codebase for training and running recurrent language models competitive with Transformers and State Space Models.

Use cases

• train a recurrent language model as an alternative to transformers
• run the xLSTM 7B model for fast and efficient inference
• experiment with new RNN architectures for sequence modeling
• implement exponential gating and matrix memory in PyTorch
• compare xLSTM against state space models on language modeling benchmarks
• fine-tune an xLSTM model on custom text data

When to choose

• you need an efficient recurrent alternative to Transformers for language modeling
• you want fast inference with constant-memory recurrent state
• you are researching modern RNN/LSTM architectures
• you want to use or extend the official xLSTM implementation from NXAI

When to avoid

• you need a mature ecosystem with broad tooling like Hugging Face Transformers
• your workload depends on Transformer-specific tooling or fine-tuning pipelines
• you need non-PyTorch support
• you only need a pretrained off-the-shelf chat model with minimal setup

Facets

library · maturity active

machine-learning deep-learning llm-inference llm-training deep-learning large-language-models machine-learning python cross-platform rnn lstm sequence-modeling pytorch language-modeling research transformer-alternative natural-language-processing gpu linux

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markdown · JSON · MCP: product_card(name="NX-AI/xlstm")