Motif-Technologies / Motif-3-Beta

huggingface.co
Total runs: 473
24-hour runs: 0
7-day runs: -192
30-day runs: -192
Model's Last Updated: September 01 2026
text-generation

Introduction of Motif-3-Beta

Model Details of Motif-3-Beta

Motif-3-Beta

⚠️ Preview / beta checkpoint — not the final release. This repository hosts an intermediate checkpoint of Motif-3 . The final checkpoint will be released soon.

Motif-3 is a large-scale Mixture-of-Experts (MoE) language model built from the ground up by Motif Technologies following a fully in-house, proprietary design — not a re-parameterization of existing open-source architectures.

Highlights
  • 🧠 ~314B total parameters / ~13B active per token (sparse MoE)
  • 📏 256K context length (262,144 tokens), natively long-context
  • ⚡ Sparse routing: 384 experts with 8 activated per token, plus 1 shared expert
  • 🌐 Multilingual , general-purpose
Model details
Model type Mixture-of-Experts causal language model
Total parameters ~314B
Active parameters ~13B / token
Hidden size 4096
Layers 53
Routed experts 384 (top-8)
Shared experts 1
Context length 262,144 (256K)
Vocabulary 220,160
Tensor type bfloat16
Architecture

Motif-3 is a fully in-house design and introduces several custom components:

  • Grouped Differential Latent Attention (GDLA)
  • Grouped PolyNorm activation , applied per expert
  • Modified mHC
Benchmarks

Artificial Analysis Intelligence Index (AAII): 44

See Artificial Analysis for details.

Usage

A dedicated vLLM serving guide is coming soon.

The model ships with custom modeling code, so load it with trust_remote_code=True :

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_id = "Motif-Technologies/Motif-3-Beta"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    trust_remote_code=True,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)

messages = [{"role": "user", "content": "Hello!"}]
inputs = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True, return_tensors="pt"
).to(model.device)

outputs = model.generate(inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0][inputs.shape[-1]:], skip_special_tokens=True))
Access

This model is openly available — anyone can download the weights, no access request required.

License

Permission is granted to use, modify, and redistribute this software for personal, educational, and non-commercial research purposes only.

Commercial use is prohibited without prior written permission from Motif Technologies.


© Motif Technologies. All rights reserved.

Runs of Motif-Technologies Motif-3-Beta on huggingface.co

473
Total runs
0
24-hour runs
-6
3-day runs
-192
7-day runs
-192
30-day runs

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