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Open-weight model · Any to any

MiniCPM-o-2_6

by OpenBMB openbmb/MiniCPM-o-2_6

[2025.06.20] Our official ollama repository is released. Try our latest models with one click! [2025.03.01] RLAIF-V, which is the alignment technique of MiniCPM-o, is accepted by CVPR 2025!The code, dataset, paper are open-sourced!

Parameters8.7B
Context32,768
Weights17.4 GB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads340k

Runs On

What it takes to serve MiniCPM-o-2_6 (8.7B parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

PrecisionWeightsMemory neededCheapest setupPer hourAlso fits
16-bit 17.3 GB 20.8 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 8.7 GB 10.4 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 4.3 GB 5.2 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00

Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Sep 18, 2026.

SAVRN's Notes on MiniCPM-o-2_6

Plan around 20.8 GB. That is the 16-bit footprint of MiniCPM-o 2.6, and it falls to 10.4 GB at 8-bit and 5.2 GB at 4-bit. On the cheapest card in our table, one MI300X with 192 GB at $1.85 per hour on-demand, that leaves most of the memory free, so the practical deployment is several copies per card. You get an 8.7B parameter any-to-any model assembled end to end from SigLip-400M, Whisper-medium-300M, ChatTTS-200M and Qwen2.5-7B, with a 32,768 token context.

Apache 2.0 allows commercial use, modification and redistribution, asks you to keep the license, copyright and NOTICE files and state significant changes, and carries a patent grant from contributors, which matters once a product depends on it. Before committing, check that the alignment data is the RLAIF-V-Dataset, that the weights ship only as safetensors, and that the repository was last updated August 18, 2026 after a January 12, 2025 release.

Model Card

By OpenBMB, published under apache-2.0, revision 06849bfd36da.

A GPT-4o Level MLLM for Vision, Speech and Multimodal Live Streaming on Your Phone

GitHub | MiniCPM Wiki(Chinese) | Online Demo | Technical Blog | Join Us

News

  • [2025.06.20] Our officialollama repository is released. Try our latest models with one click

  • [2025.03.01] RLAIF-V, which is the alignment technique of MiniCPM-o, is accepted by CVPR 2025!Thecode, dataset, paper are open-sourced!

  • [2025.01.24] MiniCPM-o 2.6 technical report is released!See Here.

  • [2025.01.19] MiniCPM-o tops GitHub Trending and reaches top-2 on Hugging Face Trending!

MiniCPM-o 2.6

MiniCPM-o 2.6 is the latest and most capable model in the MiniCPM-o series. The model is built in an end-to-end fashion based on SigLip-400M, Whisper-medium-300M, ChatTTS-200M, and Qwen2.5-7B with a total of 8B parameters. It exhibits a significant performance improvement over MiniCPM-V 2.6, and introduces new features for real-time speech conversation and multimodal live streaming. Notable features of MiniCPM-o 2.6 include:

Read the full model card (3,394 words)

Configuration

Architecture
MiniCPMO
Context length (tokens)
32,768
Layers
28
Hidden size
3,584
Feed-forward size
18,944
Attention heads
28
Key/value heads
4
Vocabulary size
151,700
Sliding window (tokens)
131,072
RoPE base
1e+06
Stored precision
bfloat16
Model type
minicpmo

Identity and Version

Repository
openbmb/MiniCPM-o-2_6
Publisher
OpenBMB
Task
Any to any
Modality
Multimodal
Library
transformers
Parameters
8.7B parameters
Languages
ocr, asr, tts
Revision
06849bfd36da94da1f5a88fa17e8ba63f08a4c4d
First published
2025-01-12
Last updated
2026-08-18

Files and Weights

40 files, 17.4 GB in total. The weights are 5 files totalling 17.4 GB in pt, safetensors.

Weights5 files · 17.4 GB
Configuration14 files · 424.9 KB
Tokenizer6 files · 12.0 MB
Documentation1 file · 50.3 KB
Other13 files · 15.7 MB
Repository1 file · 1.7 KB
Every file
FileTypeSizeSHA-256
assets/Vocos.ptWeights54.4 MB 09a670eda1c0
model-00001-of-00004.safetensorsWeights4.9 GB de39e68ffea5
model-00002-of-00004.safetensorsWeights4.9 GB 095633536dea
model-00003-of-00004.safetensorsWeights4.3 GB 4ea83267712f
model-00004-of-00004.safetensorsWeights3.2 GB f988c1730525
added_tokens.jsonConfiguration1.4 KB
assets/chattts_tokenizer/special_tokens_map.jsonConfiguration7.8 KB
config.jsonConfiguration3.4 KB
configuration_minicpm.pyConfiguration7.6 KB
image_processing_minicpmv.pyConfiguration16.7 KB
model.safetensors.index.jsonConfiguration133.3 KB
modeling_minicpmo.pyConfiguration140.6 KB
modeling_navit_siglip.pyConfiguration42.1 KB
preprocessor_config.jsonConfiguration714 B
processing_minicpmo.pyConfiguration20.0 KB
resampler.pyConfiguration35.6 KB
special_tokens_map.jsonConfiguration5.4 KB
tokenization_minicpmo_fast.pyConfiguration3.0 KB
utils.pyConfiguration7.2 KB
README.mdDocumentation50.3 KB
assets/Skiing.mp4Other8.5 MB 479ace116d6a
assets/demo.wavOther1.5 MB d0b347d8ed0b
assets/input_examples/Trump_WEF_2018_10s.mp3Other161.1 KB
assets/input_examples/assistant_default_female_voice.wavOther224.0 KB 2ee6f84892e6
assets/input_examples/assistant_female_voice.wavOther235.2 KB 1d712ba6de1d
assets/input_examples/assistant_male_voice.wavOther144.0 KB e6b5eff26be1
assets/input_examples/audio_understanding.mp3Other321.0 KB
assets/input_examples/chi-english-1.wavOther492.2 KB
assets/input_examples/cxk_original.wavOther384.0 KB
assets/input_examples/exciting-emotion.wavOther696.0 KB
assets/input_examples/fast-pace.wavOther986.4 KB
assets/input_examples/icl_20.wavOther618.5 KB 53892ece0713
assets/input_examples/indian-accent.wavOther1.4 MB 716533af9ec8
.gitattributesRepository1.7 KB
assets/chattts_tokenizer/tokenizer.jsonTokenizer448.6 KB
assets/chattts_tokenizer/tokenizer_config.jsonTokenizer11.0 KB
merges.txtTokenizer1.7 MB
tokenizer.jsonTokenizer7.0 MB
tokenizer_config.jsonTokenizer14.1 KB
vocab.jsonTokenizer2.8 MB

License and Download

License
apache-2.0
Access
Open weights, no gate
Download size
17.4 GB
Download from OpenBMB

Released by OpenBMB through its official repository on Hugging Face. Read the license.

Built From

  • Described by arXiv:2405.17220
  • Described by arXiv:2408.01800
  • Trained on (disclosed) openbmb/RLAIF-V-Dataset

Memory Requirements

PrecisionWeights in memory
As published17.4 GB
16-bit17.3 GB
8-bit8.7 GB
4-bit4.3 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Compare MiniCPM-o-2_6

Questions About MiniCPM-o-2_6

How much GPU memory does MiniCPM-o-2_6 need?

About 20.8 GB at 16-bit and 5.2 GB at 4-bit: the weights (8.7B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run MiniCPM-o-2_6 on?

At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

Can I use MiniCPM-o-2_6 commercially?

Yes. MiniCPM-o-2_6 is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.

What is MiniCPM-o-2_6's context length?

32,768 tokens, from the maximum position embeddings in its published configuration.

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