openbmb / MiniCPM5-2B-DSpark

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Model's Last Updated: September 07 2026
text-generation

Introduction of MiniCPM5-2B-DSpark

Model Details of MiniCPM5-2B-DSpark

MiniCPM Tech Report | MiniCPM Wiki(Chinese) | GitHub Repo | UltraData | Online Demo

English | 中文

MiniCPM5-2B-DSpark

MiniCPM5-2B-DSpark is a DSpark draft checkpoint trained for exact pairing with MiniCPM5-2B and its tokenizer.

Model Specification
Property Value
Target model MiniCPM5-2B
Draft layers 5
Draft parameters 323,776,001
Draft tokens per forward pass 7
Target hidden-state layers [1, 10, 20, 30, 39]
Checkpoint precision BF16
Training Recipe

Training responses were generated by MiniCPM5-2B from a mixture of general-domain, mathematics, and code prompts.

Setting Value
Training sequences 1,959,525
Training tokens 7,054,154,509
Epochs 6
Maximum sequence length 12,288
Optimizer AdamW
Objective CE + L1 + confidence loss
Evaluation

Acceptance length is defined as the total number of completion tokens divided by the total number of speculative verification steps. Evaluation uses natural EOS termination and max_new_tokens=4096 .

Domain T=0 T=1.0
Math 6.0496 4.6050
Code 6.1106 4.4381
General 4.1585 3.0997
Aggregate 5.5174 4.0514
Usage with SGLang
python -m sglang.launch_server \
  --model-path <target-model-path> \
  --trust-remote-code \
  --speculative-algorithm DSPARK \
  --speculative-draft-model-path <draft-model-path> \
  --speculative-dspark-block-size 7
Limitations and Disclaimer

This model has no autonomous intent or legal personhood; its outputs are text generated from statistical patterns and may be inaccurate, biased, or offensive, and may be manipulated by carefully crafted prompts ("jailbreaks") into producing unintended content. Its responses on sensitive topics such as politics, health, finance, and law are not reviewed by experts and should not be treated as professional advice.

This model is provided " AS IS ", without warranty of any kind, express or implied, and the developers are not liable for any damages arising from its use. Users must employ the model only for lawful, compliant, and ethical purposes, configure their own safeguards, and label AI-generated content where required; deliberate jailbreaking, injection attacks, or inducing harmful output is prohibited, and any such testing is at the user's own risk.

License

This repository and MiniCPM model weights are released under the Apache-2.0 License.

Citation

Please cite our paper if you find our work valuable:

@article{minicpm4,
  title={Minicpm4: Ultra-efficient llms on end devices},
  author={MiniCPM, Team},
  journal={arXiv preprint arXiv:2506.07900},
  year={2025}
}

Runs of openbmb MiniCPM5-2B-DSpark on huggingface.co

103.4K
Total runs
25.6K
24-hour runs
86.2K
3-day runs
103.4K
7-day runs
103.4K
30-day runs

More Information About MiniCPM5-2B-DSpark huggingface.co Model

More MiniCPM5-2B-DSpark license Visit here:

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MiniCPM5-2B-DSpark huggingface.co

MiniCPM5-2B-DSpark huggingface.co is an AI model on huggingface.co that provides MiniCPM5-2B-DSpark's model effect (), which can be used instantly with this openbmb MiniCPM5-2B-DSpark model. huggingface.co supports a free trial of the MiniCPM5-2B-DSpark model, and also provides paid use of the MiniCPM5-2B-DSpark. Support call MiniCPM5-2B-DSpark model through api, including Node.js, Python, http.

MiniCPM5-2B-DSpark huggingface.co Url

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openbmb MiniCPM5-2B-DSpark online free

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openbmb MiniCPM5-2B-DSpark online free url in huggingface.co:

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MiniCPM5-2B-DSpark install

MiniCPM5-2B-DSpark is an open source model from GitHub that offers a free installation service, and any user can find MiniCPM5-2B-DSpark on GitHub to install. At the same time, huggingface.co provides the effect of MiniCPM5-2B-DSpark install, users can directly use MiniCPM5-2B-DSpark installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

MiniCPM5-2B-DSpark install url in huggingface.co:

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