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MiniCPM5 2B GPTQ

MiniCPM5 2B GPTQ is a GPTQ-quantized text-generation model from OpenBMB, released under the Apache 2.0 license. It is described as a dense 2B Transformer intended for on-device, local deployment, and resource-constrained scenarios, and is the second model in the MiniCPM5 series following MiniCPM5-1B. The official model card states it reaches 2B-class open-source SOTA within its comparison set and remains competitive with 4B-class models overall, with reported advantages over comparable-size models in coding, mathematics, long-context understanding, tool use, and agentic tasks. Supported languages listed in the card are English and Chinese. Training data listed includes Ultra-FineWeb, UltraX-Preview, Ultra-FineWeb-L3, UltraData-Math, UltraData-Code, UltraData-SFT-2605, UltraData-SFT-Agent-2609, and UltraData-RL-2609.

EstimatedRepository opened Sep 7, 2026Source checked 9/24/2026Version: 48d57c14

LOCALRENTED GPUOPEN WEIGHTS

Freshness 86 out of 100. Repository age: 38 days old, Sep 7, 2026. Measures age, not quality.

Popularity 46 out of 100. 3,678 downloads in 30 days; 22 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

WORKFLOWS FOR THIS MODEL 2

What do you want to do?

Choose a task. Get the software, files, settings, and steps to run it.

MAKE IT PERSONALChoose your hardware

Private chat

Chat locally with MiniCPM5 · 2B

Run the official MiniCPM5 2B GGUF on Windows, Mac, or Linux with Ollama for a simple private chat. An advanced GPTQ/vLLM route is available for Linux NVIDIA, plus a separately labelled community uncensored MLX package for Apple Silicon.

Freshness 86 out of 100. Repository age: 38 days old, Sep 7, 2026. Measures age, not quality.

OllamavLLM

3 packagesmacOS / Windows / LinuxUncensored option

Open chat guide

Coding

MiniCPM5 2B local coding assistant metadata plan

Metadata-only plan for a local coding assistant using MiniCPM5 2B GPTQ AWQ 4-bit, with portable GGUF and Apple Silicon MLX alternatives. Selects source-backed packages and supported platform routes.

Freshness 86 out of 100. Repository age: 38 days old, Sep 7, 2026. Measures age, not quality.

llama.cppvLLM

3 packagesmacOS / Windows / LinuxUncensored option

Open coding guide

Open a guide for its software, hardware requirements, and setup steps.

At a glance

Parameters: 2.52B
Architecture: llama
Context length: 131,072
License: apache-2.0
Disk space: 2 GB
Software: llama.cpp, SGLang, vLLM

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MY HARDWARE

Will it run on your machine?

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Best for

On-device text generation
Local deployment in resource-constrained scenarios
Coding-related tasks
Mathematics-related tasks
Long-context understanding and tool use or agentic tasks

Tradeoffs

Facts are limited to the supplied model card and metadata; compatibility with specific hardware or software is not stated.
No tested performance benchmarks, latency, memory, or other numerical hardware requirements are provided.
The model is GPTQ-quantized, but no license terms beyond apache-2.0 or quantization-specific limitations are given.
Language coverage is listed only as en and zh; other languages are not stated.
No claims of testing or purchase recommendations are made based on the supplied data.

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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MODEL SIZE27.36B

LOCALRENTED GPU

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