bcml/bclm-1-small-preview

Bellevue College Language Model

BCLM-1-Small-Preview

We are releasing BCLM-1 Preview, an open family of flagship language models that deliver strong, predictable performance across a range of tasks.

BCLM-1 Preview is built on a hybrid SSM/attention architecture (Bulldog) for efficient training and inference, tailored for writing, summarization, and recall out of the box.

Note: This is a preview model, and may make mistakes or errors not present in future releases.

Models

Model	Parameters	Variant	Input	Output	Thinking
BCLM-1-Small-Preview	123M	Instruction-tuned	Text-only	Text-only	No
BCLM-1-Medium	720M	Instruction-tuned	Text-only	Text-only	Planned

Sample Generations

BCLM-1-Small-Preview generates coherent, actionable text in alignment with prompts.

Photosynthesis is a vital process that occurs in plants, algae, and
certain bacteria, allowing them to convert light energy into chemical
energy. This process is essential for life on Earth as it provides the
primary energy source for nearly all ecosystems.

Prompt: What are the key components of a successful marketing campaign?

* A clear and compelling message that resonates with the target audience.
* Effective use of multiple channels to reach and engage the target
  audience effectively.
* Measurable and relevant KPIs to help optimize campaign outcomes.

Example Usage

BCLM-1 is easy to use with our library, bclm-pytorch, in Python:

import bclm

model = bclm.load("bclm-1-small-preview")

# Multi-turn chat
chat = model.chat(system_prompt="You are a helpful assistant.")

# Streaming chat (real-time token output)
for chunk in chat.send_stream("Explain the future of AI."):
    print(chunk, end="", flush=True)

transformers support coming soon.

Training

BCLM-1 was trained on NVIDIA H200 GPUs.

Stage	Steps	Loss	Perplexity (ppl)
Pretraining	24,000	2.11	8.25
SFT	6,000	1.85	6.36

Notes

BCLM-1-Small-Preview is trained for general language tasks only. Math and code generation will be supported in future releases.

Tokenizer and Supported Languages

BCLM-1 uses the tokenmonster tokenizer with a vocabulary of 32,000 tokens.

Only English is supported in this release. Additional languages will follow.

Context Length

BCLM-1-Small-Preview was trained with a maximum context length of 2,048 tokens. Extended context support is planned for the next release.

Architecture Information

Architecture	BCLM-1
Parameters	123.14M (77.55M non-embedding)
Embedding dim	384
Layers	12
Attention heads	6 (KV heads: 2)
Vocab size	32,768
SSM Layers	12
SSM State Size	156,672
Local Attn. Layers	6
Global Attn. Layers	2
Max sequence length	16,384
Local Window Size	1,024
Training Precision	BF16
Weights Precision	F32 (can be changed)
Weights format	safetensors

Learn more about the Bulldog architecture: GitHub

Limitations

Like all generative models, BCLM-1 can produce incorrect, incomplete, or fabricated information. Outputs should not be treated as factual without verification. We are not responsible for any misuse, harm, or consequences arising from the use of this model's outputs.

Citation

@software{bclm1,
  title  = {BCLM-1},
  author = {BCML Labs},
  url    = {https://github.com/bcml-labs/bclm-pytorch},
  year   = {2026}
}