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MiniCPM5 1B SFT

MiniCPM5 1B SFT is an Apache-2.0 licensed, text-generation model from openbmb/MiniCPM5-1B-SFT. It is an SFT-only checkpoint (before RL/OPD) in the MiniCPM5 series, supporting English and Chinese. The model is a dense 1B Transformer with a LlamaForCausalLM architecture, 1,080,632,832 parameters (679,552,512 non-embedding), 24 layers, GQA with 16 Q heads and 2 KV heads, and a 131,072 token context length. It includes a hybrid reasoning chat template with a `thinking` mode activated via `enable_thinking`, and is intended for on-device, local deployment, and resource-constrained scenarios.

EstimatedRepository opened May 21, 2026Source checked 9/24/2026Version: a60b37f1
LOCALRENTED GPUOPEN WEIGHTS
Freshness 57 out of 100. Repository age: 147 days old, May 21, 2026. Measures age, not quality.
Popularity 49 out of 100. 5,106 downloads in 30 days; 47 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
1.08B
Architecture
llama
Context length
131,072
License
apache-2.0
Disk space
2 GB
Software
llama.cpp, SGLang, vLLM
View the model source
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Best for

  • Local assistants on edge or on-device environments
  • Coding agents
  • Tool-use workflows
  • Reasoning scenarios where a compact model is preferred
  • Long-context text generation with English and Chinese

Tradeoffs

  • It is an SFT-only checkpoint and does not include RL or OPD post-training.
  • No performance benchmarks or numerical hardware requirements are provided.
  • No evaluation results or testing claims are included.
  • The model card does not specify compatibility with specific inference backends or formats.
  • No purchasable recommendations or deployment guarantees are provided.

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

Explore its uses

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