Neuronpedia, an open source platform for AI interpretability
Neuronpedia is an open source interpretability platform that enables users to explore, visualize, and steer the internal workings of AI models. It features tools like HeadVis, Natural Language Autoencoders, Circuit Tracer, and steerable activations, supporting over 50 million latent vectors across numerous models. Created by Johnny Lin, it is backed by organizations including Anthropic and Google DeepMind.
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Neuronpedia is an open source interpretability platform.
Explore, visualize, and steer the internals of AI models.
Gurnee et al.
Jacobian Lens
Revealing a Global Workspace in Language Models
Fraser-Taliente, Kantamneni, Ong et al.
Natural Language Autoencoders
Translate a Model's Internal Thoughts Into Text
Lu et al.
Assistant Axis
Monitor & Stabilize the Character of an LLM
Multi-Org
Circuit Tracer
Trace a Model's Internal Reasoning Steps
Google Deepmind
Gemma Scope 2
SAEs and Transcoders for Gemma 3
Latest Update
June 2026
HeadVis, plus NLA Contributions and more SAEs
Explore 36,000+ Attention Heads Across 37 Models
Newsletter
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Releases and Models
Browse five+ terabytes of activations, explanations, and metadata. Neuronpedia supports probes, latents/features, custom vectors, concepts, and more.
Releases
Featured
HeadVis: Browse & Investigate Attention Heads
Luger, Kamath, et al., Anthropic
Featured
Natural Language Autoencoders
Fraser-Taliente, Kantamneni, Ong et al., Anthropic
Featured
Circuit Tracing with Interpretable Attention
OpenMOSS Team, Fudan University
Featured
Assistant Axis: Situating and Stabilizing the Character of an LLM
Lu et al, Anthropic Fellows
Featured
Gemma Scope 2: Suite of SAEs and Transcoders for Gemma 3
Language Model Interpretability Team, Google DeepMind
Featured
Circuit Tracer: Tracing the Internal Reasoning Steps of a Model
Hanna & Piotrowski, Anthropic Fellows
Featured
Gemma Scope - Exploring the Inner Workings of Gemma 2
Language Model Interpretability Team, Google DeepMind
Featured
SAE Bench
Adam Karvonen · Can Rager
Gemma 4 SAEs
David Chanin
Qwen 3.5 SAEs
David Chanin
Olmo 3 7B SAE
David Chanin
Olmo 3 32B SAE
Bartosz Cywinski
Qwen Scope
Alibaba
Qwen3 SAEs
Adam Karvonen
Qwen2.5 7B IT SAE
David Chanin
Beta
Weight-Sparse Transformers Have Interpretable Circuits
OpenAI
Temporal Feature Analysis
Lubana, Rager, Hindupur, et al.
gpt-oss BatchTopK SAEs
Andy Arditi
Finding Misaligned Persona Features in Open-Weight Models
Andy Arditi
Circuit Tracer Transcoders
Hanna & Piotrowski
A Bunch of Matryoshka SAEs
David Chanin
Llama 3.3 70B Instruct SAE
Goodfire
Llama Scope R1: SAEs for DeepSeek-R1-Distill-Llama-8B
OpenMOSS Team, Fudan University
AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders
pyvene.ai, The Stanford NLP Group
Llama Scope: SAEs for Llama-3.1-8B
OpenMOSS Team, Fudan University
Feature Splitting for GPT2-Small
Joseph Bloom
Multi TopK SAE for Llama3.1-8B
EleutherAI
Sparse Autoencoder for GPT2-Small - v5
OpenAI
Identifying Functionally Important Features with End-to-End Sparse Dictionary Learning
Apollo Research · Jordan Taylor
Transcoders Enable Fine-Grained Interpretable Circuit Analysis for Language Models
Jacob Dunefsky · Philippe Chlenski
Sparse Autoencoders for Pythia-70M-Deduped
Under Peer Review
Attention SAE Research Paper
Under Peer Review
Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
Joseph Bloom
Models
GEMMA-4-31B
Gemma-4-31BGoogle Deepmind
QWEN3.5-4B
Qwen3.5-4BAlibaba
GEMMA-4-E2B
Gemma-4-E2BGoogle Deepmind
GEMMA-4-E4B
Gemma-4-E2BGoogle Deepmind
QWEN3.5-0.8B
Qwen3.5-0.8BAlibaba
OLMO-3-1025-7B
Olmo-3-1025-7BAllen AI
OLMO-3-1125-32B
Olmo-3-1125-32BAllen AI
QWEN3.6-27B
Qwen3.6-27BAlibaba
QWEN3.5-27B
Qwen3.5-27BAlibaba
QWEN3-32B
Qwen3-32BAlibaba
QWEN3.5-9B-PT
Qwen3.5-9B BaseAlibaba
QWEN3.5-2B-PT
Qwen3.5-2B BaseAlibaba
QWEN3-14B
Qwen3-14BAlibaba
QWEN3-8B
Qwen3-8BAlibaba
CIRCUITGPT-PYTHON
CircuitGPT-PythonOpenAI
GEMMA-3-27B
Gemma-3-27BGoogle Deepmind
GEMMA-3-12B
Gemma-3-12BGoogle Deepmind
GEMMA-3-270M-IT
Gemma-3-270M-ITGoogle Deepmind
GEMMA-3-1B-IT
Gemma-3-1B-ITGoogle Deepmind
GEMMA-3-4B-IT
Gemma-3-4B-ITGoogle Deepmind
GEMMA-3-12B-IT
Gemma-3-12B-ITGoogle Deepmind
GEMMA-3-27B-IT
Gemma-3-27B-ITGoogle Deepmind
GEMMA-3-270M
Gemma-3-270MGoogle Deepmind
GEMMA-3-4B
Gemma-3-4BGoogle Deepmind
GEMMA-3-1B
Gemma-3-1BGoogle Deepmind
GEMMA-2-27B
Gemma-2-27BGoogle Deepmind
GPT-OSS-20B
GPT-OSS-20BOpenAI
LLAMA3.1-8B-IT
Llama3.1-8B-ITMeta
QWEN2.5-7B-IT
Qwen2.5-7B-ITAlibaba
QWEN3-1.7B
Qwen3-1.7BAlibaba
QWEN3-4B
Qwen3-4BAlibaba
LLAMA3.3-70B-IT
Llama3.3-70B-ITMeta
GEMMA-2-2B-IT
Gemma-2-2B-ITGoogle Deepmind
GEMMA-2-9B-IT
Gemma-2-9B-ITGoogle Deepmind
LLAMA3.1-8B
Llama3.1-8B (Base)Meta
GEMMA-2-2B
Gemma-2-2BGoogle Deepmind
GEMMA-2-9B
Gemma-2-9BGoogle Deepmind
P70M-D
Pythia-70M-DedupedEleutherAI
GPT2-SMALL
GPT2-SmallOpenAI
Jump To
Jump to Source/SAE
Jump to Feature
INDEX
Jump to Random
Graph
Visualize and trace the internal reasoning steps of a model with custom prompts, pioneered by Anthropic's circuit tracing papers.
Steer
Modify model behavior by steering its activations using latents or custom vectors. Steering supports instruct (chat) and reasoning models, and has fully customizable temperature, strength, seed, etc.
Search
Search over 50,000,000 latents/vectors, either by semantic similarity to explanation text, or by running custom text via inference through a model to find top matches.
Search via Inference
Run Example Search
API + Libraries
Neuronpedia hosts the world's first interpretability API (March 2024) - and all functionality is available by API or Python/TypeScript libraries. Most endpoints have an OpenAPI spec and interactive docs.
Inspect
Go in depth on each probe/latent/feature with top activations, top logits, activation density, and live inference testing. All dashboards have unique links, can be compiled into sharable lists, and supports IFrame embedding, as demonstrated here.
Who We Are
Neuronpedia was created by Johnny Lin, an ex-Apple engineer who previously founded a privacy startup. Neuronpedia is supported by Decode Research, Open Philanthropy, the Long Term Future Fund, AISTOF, Anthropic, Manifund, and others.
Get Involved
Citation
@misc{neuronpedia, title = {Neuronpedia: Interactive Reference and Tooling for Analyzing Neural Networks}, year = {2023}, note = {Software available from neuronpedia.org}, url = {https://www.neuronpedia.org}, author = {Lin, Johnny} }