MiniCPM-V 4.7 vs Iris-3B
Compare MiniCPM-V 4.7 and Iris-3B.
| Dimension | MiniCPM-V 4.7 | Iris-3B | Source |
|---|---|---|---|
| License | Apache-2.0 (HF card + GitHub, 2026-10-16) | Apache-2.0 (HF card + GitHub, 2026-10-13) | Official cards |
| Developer | OpenBMB (Tsinghua + ModelBest) | speridlabs | Official cards |
| Parameters | 8B (LLM) + Qwen3-VL-8B vision encoder | 3B + frozen Qwen3-VL-4B-Instruct text encoder | Official cards |
| Model type | Vision-language model (VLM) for image understanding | Text-to-image diffusion (pixel-space, no VAE) | Official cards |
| Modalities | Text + image → text (multimodal input, text output) | Text → image (text-to-image generation) | Official cards |
| Use case | Image captioning, OCR, chart/diagram understanding, multimodal chat | Text-to-image generation, 4-step Turbo distill, no editing | Official docs + cards |
| Hardware (vendor/card) | ~10 GB VRAM (card); RTX 3060 12 GB cited (self-reported) | ~12 GB T2I weights + 6 GB Turbo; demo ~45 GB or ~20 GB with offload | MiniCPM-V card + README; Iris-3B card |
| Hugging Face likes | ~1,400 (MiniCPM-V 4.7, 2026-10-16 ballpark) | 200 (as of 2026-10-13) | Hugging Face |
| First seen | 2026-01-10 (V4.7 repo) | 2026-10-05 (HF and GitHub created) | Official hosts |
| Quality comparison | n/a (different modalities) | n/a (different modalities) | n/a |
When to choose which
- Image understanding / multimodal chat: MiniCPM-V 4.7 — It's a vision-language model. Iris-3B is T2I generation only, no understanding.
- Text-to-image generation: Iris-3B — It's a diffusion model. MiniCPM-V 4.7 does not generate images.
- Few-step image generation (Turbo): Iris-3B — Official Turbo is 4-step. MiniCPM-V 4.7 is not a generator.
- Lower VRAM (vendor/card): MiniCPM-V 4.7 — Card quotes ~10 GB. Iris-3B T2I is ~12 GB weights, Turbo ~6 GB, but demo memory is higher. Not independently measured.
Read the entity pages: MiniCPM-V 4.7 and Iris-3B. These are different model classes: MiniCPM-V 4.7 is a vision-language model listed on ChatGPT alternatives; Iris-3B is a text-to-image model on Midjourney alternatives. Same-class perception VLM (not this pair): WeVisOne-VL. Computer-use VLM: Mage-VL-Cowork. Liquid text vs omni: LFM3-1.7B vs LFM3-Omni-2B.
FAQ
Which one is better?
They solve different problems. MiniCPM-V 4.7 understands images (VLM chat, OCR, captioning). Iris-3B generates images (text-to-image diffusion). There is no "better" across modalities.
Can I use MiniCPM-V 4.7 to generate images?
No. It's a vision-language model for understanding images and answering questions, not for generating them. Use Iris-3B or other T2I models for generation.
Can Iris-3B understand or caption images?
No. It's a text-to-image generator (diffusion model), not a VLM. Use MiniCPM-V 4.7 or other VLMs for image understanding.
Why are they on the same comparison page?
This page exists because the user request included both model names. They are different classes (VLM vs T2I) and serve different workflows. Check individual model pages for details.
Sources & verification
- https://huggingface.co/openbmb/MiniCPM-V-4_7
- https://github.com/OpenBMB/MiniCPM-o
- https://huggingface.co/speridlabs/iris-3b
- https://github.com/speridlabs/iris-3b
License notes are not legal advice. Read the original LICENSE. Trademark & disclaimer.