LLM Reference
OpenBMB

OpenBMB

3 models across 1 family · Latest: MiniCPM-V 4.6 (2026-05)

Efficient open-source language models for edge devices.

RAGAgentsLong contextVisionJSON / Tool useResearch

OpenBMB's portfolio covers 3 active models across 1 current family, spanning rag, agents, and long context. Open a model detail page to compare provider routes and sourced benchmarks.

Covers 5 workload areas across 3 active tracked models; last verified 2026-07-07.

Use it for

  • Teams evaluating rag, agents, and long context across this lab's releases
  • Comparing model families before committing to a flagship
  • Migration and pricing follow-ups across 3 tracked models

Do not use it for

  • Choosing a hosting provider without opening a model page for price ladders

Active models

3

Current models from this lab, excluding deprecated ones

Active families

1

Current model families from this lab

Open catalog

3 open

3 open source / 0 open weights

Lowest output price

Not tracked

No provider output pricing linked yet

Latest dated release

2026-05-11

MiniCPM-V 4.6

Freshness

2026-07-07

Researched 10d ago

fresh

Information

Founded2022
Beijing, China

Release cadence

Showing 3 recent dated releases (full timeline below). Latest: MiniCPM-V 4.6 (2026-05-11).

Where this lab wins

  • RAG: 1 tracked model with ruler / needle retrieval benchmarks.
  • Agentic: 1 tracked model with BFCL, tau-bench, and SWE-bench tool-use coverage.
  • Long-context: 1 tracked model with context-token or InfiniteBench-class signal.
  • Vision: 1 tracked model with multimodal benchmark coverage.

Flagship quality / price signal

Flagship: MiniCPM-4 8B (best sourced coding quality-per-dollar in this portfolio).

Quality-per-dollar unavailable for this flagship — benchmark coverage or output token pricing is still missing.

OpenBMB is a Chinese AI research organization founded in 2022. Efficient open-source language models for edge devices. OpenBMB ships 1 model family totaling 3 models, with the most recent release MiniCPM-V 4.6 in 2026-05. Notable families include MiniCPM. Use it as a stable reference for lab background, release coverage, and follow-up model pages as they are added. Researchers and evaluators can scan. View official API endpoints, benchmark performance, and coding/agent fit for every OpenBMB model.

About

OpenBMB (Open Lab for Big Model Base), co-founded by Tsinghua NLP researchers and ModelBest Inc. (面壁智能), develops the MiniCPM series of ultra-efficient language models optimized for on-device deployment. MiniCPM4 achieves 3x generation speedup on reasoning tasks, while the multimodal MiniCPM-o 4.5 approaches Gemini 2.5 Flash performance with only 9B parameters. The models are freely available for academic research and commercial use.

Featured models

ModelReleasedContextInput price ($/1M)Output price ($/1M)LicenseOpenness
MiniCPM-V 4.62026-05-11262k--Apache 2.0Open source
MiniCPM-4 8B2025-05-0132k--Apache 2.0Open source
MiniCPM 2B2024-02-014k--Apache 2.0Open source

Model families

Recent releases

  1. MiniCPM-V 4.6- 2026-05-11
  2. MiniCPM-4 8B- 2025-05-01
  3. MiniCPM 2B- 2024-02-01

Top comparisons

FAQ

Who founded OpenBMB and when?

OpenBMB was founded in 2022 and is associated with Beijing, China.

What models has OpenBMB released?

OpenBMB ships 3 models across 1 family: MiniCPM.

Is OpenBMB's technology open source?

All tracked models are released under Apache 2.0.

Where is OpenBMB headquartered?

OpenBMB is headquartered in Beijing, China.

What is OpenBMB known for?

Efficient open-source language models for edge devices. Its most prominent tracked family is MiniCPM.

How can I access OpenBMB's models?

OpenBMB's provider availability is tracked on model pages as API and hosting data is verified.

Explore related pages

Last reviewed: 2026-07-07. Data sourced from public lab announcements and provider documentation.