vLLM/Recipes
MiniCPM (OpenBMB)

openbmb/MiniCPM-V-4.6

MiniCPM-V 4.6 (1.3B) — pocket-sized multimodal LLM for ultra-efficient single-image, multi-image, and video understanding, built on SigLIP2-400M + a Qwen3.5-0.8B hybrid-attention backbone

~1.5× token throughput vs Qwen3.5-0.8B with mixed 4×/16× visual token compression

View on HuggingFace
dense1.3B262,144 ctxvLLM 0.22.0+multimodal
Guide

Overview

MiniCPM-V 4.6 is OpenBMB's most edge-friendly multimodal model to date. It pairs a SigLIP2-400M vision encoder with a Qwen3.5-0.8B hybrid linear/full-attention language backbone (~1.3B params total). It handles single-image, multi-image, and video understanding, and introduces mixed 4×/16× visual token compression — switch the downsample_mode per request to trade accuracy for speed.

MiniCPM-V 4.6 ships as two independent checkpoints — this recipe covers the Instruct model (openbmb/MiniCPM-V-4.6). For chain-of-thought output, use the separate openbmb/MiniCPM-V-4.6-Thinking checkpoint instead (unlike v4.5, the mode is no longer toggled at runtime).

Prerequisites

  • vLLM ≥ 0.22.0 — the MiniCPMV4_6ForConditionalGeneration architecture landed via PR #43213 (merged 2026-05-22) and first shipped in the v0.22.0 release. No fork is required.
  • transformers ≥ 5.7.0 — the model is merged as a standalone architecture only in this version.
  • For video inputs, install the vllm[video] extra.

Launch command

Use the command builder above. The baseline is simply:

vllm serve openbmb/MiniCPM-V-4.6 --trust-remote-code --port 8000

Enable the Tool calling feature to add --enable-auto-tool-choice --tool-call-parser qwen3_coder. The model emits a Qwen3-Coder-style <tool_call> block inside the message content.

At 1.3B params the model fits on a single GPU (TP=1). v4.6 supports context up to 256K, but start with a smaller --max-model-len (e.g. 8192) and raise it to fit your GPU memory and workload.

Client usage

Image:

curl -s http://localhost:8000/v1/chat/completions -H 'Content-Type: application/json' -d '{
  "model": "openbmb/MiniCPM-V-4.6",
  "messages": [{"role": "user", "content": [
    {"type": "image_url", "image_url": {"url": "https://huggingface.co/datasets/openbmb/DemoCase/resolve/main/refract.png"}},
    {"type": "text", "text": "What causes this phenomenon?"}
  ]}]
}'

Stop tokens: v4.6 uses the Qwen3.5 backbone with a new vocab. If you see runaway generations, pass "stop_token_ids": [248044, 248046] in your request body.

References