CrystalReasoner/Qwen2.5-3B-CrysReas-Base

CrystalReasoner: Reasoning and RL for Property-Conditioned Crystal Structure Generation

CrystalReasoner (CrysReas) is an end-to-end LLM framework for generating crystal structures from natural language instructions. It uses supervised fine-tuning (SFT) to teach crystal-structure generation, thinking traces to introduce crystallographic and physical priors before coordinates, and reinforcement learning (RL) with verifiable rewards to improve validity, stability, and property conditioning. Please see our work at crystalreasoner.github.io.

Qwen2.5-3B-CrysReas-Base

Quick Start

You can use this model directly with the transformers library:

from transformers import AutoModelForCausalLM, AutoConfig, AutoTokenizer
import torch

model_id = "CrystalReasoner/Qwen2.5-3B-CrysReas-Base"

tokenizer = AutoTokenizer.from_pretrained(model_id)
config = AutoConfig.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    config=config,
    torch_dtype=torch.bfloat16,
    trust_remote_code=True
)

messages = [
    {"role": "user", "content": "Below is a description of a bulk material. The chemical formula is NaCl. The bulk_modulus is about 100 GPa. Generate a description of the lengths and angles of the lattice vectors and then the element type and coordinates for each atom within the lattice:"},
]

text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
model_inputs = tokenizer(text, return_tensors="pt").to(model.device)

generated_ids = model.generate(
    model_inputs.input_ids,
    max_new_tokens=2048,
    pad_token_id=tokenizer.pad_token_id,
    eos_token_id=tokenizer.eos_token_id,
    use_cache=True,
)
generated_text = tokenizer.batch_decode(generated_ids, skip_special_tokens=False)[0]
print(generated_text)

If you want the generated structure in pymatgen Structure format, please use this script after the previous generation:

def get_structure(generated_text: str):
    import re
    from pymatgen.core import Lattice, Structure

    cif_match = re.search(r'<CIF>(.*?)</CIF>', generated_text, re.DOTALL)
    if cif_match:
        generated_text = cif_match.group(1)

    lines = [line.strip() for line in generated_text.strip().split('\n') if line.strip()]
    if lines and not re.match(r'^[-+0-9.eE\s]+$', lines[0]):
        lines = lines[1:]

    lengths = list(map(float, lines[0].split()))
    angles = list(map(float, lines[1].split()))
    lattice = Lattice.from_parameters(*lengths, *angles)

    species = []
    coords = []
    for line in lines[2:]:
        parts = line.split()
        species.append(parts[0])
        coords.append([float(parts[2]), float(parts[3]), float(parts[4])])

    structure = Structure(lattice, species, coords)
    return structure

structure = get_structure(generated_text)
print(structure)

Citation

Check out our paper for more details. If you use our dataset or find our work useful, please cite

@article{wu2026crysreas,
  title={CrystalReasoner: Reasoning and RL for Property-Conditioned Crystal Structure Generation},
  author={Yuyang Wu and Stefano Falletta and Delia McGrath and Sherry Yang},
  year={2026},
  journal={arXiv preprint arXiv:2605.14344},
  url={https://arxiv.org/abs/2605.14344}
}