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LatestBAAI3.5
BAAIAny-to-Any

BAAI Releases Emu3.5, an 'Any-to-Any' Multimodal Model

The new open-source model from the Allen Institute for AI unifies text and image understanding and generation into a single architecture.

Oct 31, 2025
NotableApache 2.0
Emu3.5

The Allen Institute for AI (BAAI) has released Emu3.5, a new open-source model that pushes the boundaries of multimodal AI. Available under the permissive Apache 2.0 license, Emu3.5 is designed as a native "any-to-any" system, capable of both understanding and generating interleaved text and images within a single, unified framework.

A Unified Architecture

Unlike systems that chain separate, specialized models for different tasks (e.g., one for captioning, another for image generation), Emu3.5 aims to handle diverse combinations of inputs and outputs natively. The model can accept prompts containing both text and images to generate responses that are also a mix of text and new images. This approach moves beyond simple text-to-image or image-to-text capabilities toward more fluid, conversational interactions across modalities.

This unified design represents a significant step toward more integrated and capable AI systems. By handling complex, multimodal instructions within one architecture, models like Emu3.5 could power more sophisticated applications in creative tools, data analysis, and robotics. Researchers and developers can explore the model and its capabilities on its official Hugging Face repository.

Sources

  • BAAI/Emu3.5

    Hugging Face

    Visit
OlderMicrosoft Releases Fara-7B Vision Agent ModelMicrosoft · Vision-Language · last yearNewerMoonshot AI Releases Kimi-K2 Reasoning ModelMoonshot AI · Reasoning · 12 months ago

Get the model

Hugging Face

Specs

Context window33K tokens
Size68.2 GB
PrecisionBF16
ArchitectureEmu3ForCausalLM
LicenseAPACHE-2.0
Downloads381
Likes176

Can you run it?

Runs on a 24 GB GPU at 4-bit.

  • BF16 (as published)

    80 GB GPU (A100 / H100) · 128 GB Mac Studio

    71.3 GB
  • 8-bit

    48 GB GPU (RTX 6000) or 2×24 GB · 64 GB Mac

    39.3 GB
  • 4-bit

    24 GB GPU (RTX 3090 / 4090) · 32 GB Mac

    23.6 GB
Your machine
  • KV cache sized for 8,192 tokens of context; longer prompts need proportionally more.

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Any-to-AnyVision-LanguageText → Image

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