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Models/MiniCPM5/MiniCPM5 2B Base
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MiniCPM5 2B Base

MiniCPM5 2B Base is a dense 2B Transformer text-generation model from the MiniCPM5 series, released under the Apache-2.0 license by openbmb. It is positioned for on-device, local deployment, and resource-constrained scenarios, and its model card describes it as reaching 2B-class open-source SOTA within its stated comparison set. The model supports English and Chinese, uses the transformers library, and is associated with long-context, tool-calling, on-device, and edge-ai tags. It was trained on datasets including Ultra-FineWeb, UltraX-Preview, UltraData-Math, UltraData-Code, and several UltraData SFT/RL datasets.

EstimatedRepository opened Aug 27, 2026Source checked 9/23/2026Version: 96a57cd5
LOCALRENTED GPUOPEN WEIGHTS
Freshness 83 out of 100. Repository age: 49 days old, Aug 27, 2026. Measures age, not quality.
Popularity 52 out of 100. 10,996 downloads in 30 days; 30 lifetime likes. Checked Oct 15, 2026. Measures adoption, not quality.
What do these scores mean?

Two ways to compare models. Neither score measures answer quality, benchmark performance, or whether a model fits your machine.

Freshness · release age

A new release starts at 100. The score halves every 180 days: 100 × 2^(−age in days / 180). When the release date is unavailable, a repository date is a fallback—not proof of when the model was released. Missing dates stay unscored.

Check the date source
Popularity · adoption

Downloads over the past 30 days carry 80% of the score; lifetime likes carry 20%. Both use a logarithmic scale, capped at 10 million downloads and 100,000 likes. If likes are unavailable, downloads carry all the weight. Missing download statistics stay unscored.

round(80 × min(1, log10(1 + downloads) / 7) + 20 × min(1, log10(1 + likes) / 5))

Check the statistics source
Scores as of Oct 15, 2026. Statistics checked Oct 15, 2026. Statistics are marked for refresh after 72 hours.Full scoring method

At a glance

Parameters
2.52B
Architecture
llama
Context length
524,288
License
apache-2.0
Disk space
4.7 GB
Software
llama.cpp, SGLang, vLLM
View the model source
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Best for

  • On-device text generation
  • Local deployment in resource-constrained environments
  • English and Chinese language tasks
  • Long-context understanding tasks
  • Tool-calling and agentic tasks

Tradeoffs

  • The supplied facts do not specify detailed context length limits.
  • No specific hardware requirements are provided.
  • No information is given about supported inference frameworks beyond the transformers library.
  • Performance outside the stated comparison set is not described.
  • No testing or benchmark results are provided beyond the claimed 2B-class open-source SOTA statement.

Ways to run it

llama.cpp · Windows, macOS, Linux

Repository-specific command in publisher documentation; confirm dependencies and hardware in the source.

llama-server -m MiniCPM5-2B-F16.gguf -a MiniCPM5-2B --port 8080 -ngl 99 -c 8192 --jinja
Official instructions

SGLang · Linux

Repository-specific command in publisher documentation; confirm dependencies and hardware in the source.

python -m sglang.launch_server --model-path openbmb/MiniCPM5-2B --port 30000
Official instructions

vLLM · Linux

Repository-specific command in publisher documentation; confirm dependencies and hardware in the source.

vllm serve openbmb/MiniCPM5-2B --port 8000
Official instructions

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