Open-source ML.
Ready to run.

Pick any model from the Hugging Face Hub. Download the app and run it. Detection, segmentation, VLMs, speech, diffusion, classification, depth, OCR, and more. Runs on CPU or GPU. Optional OpenAI-compatible API and MCP server. Nothing leaves your machine.

DETR SAM 2 SigLIP 2 InternVL Whisper FLUX SegFormer GPT-OSS Pixtral SDXL
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ZeroInfer
5 local models
GPU: 0.01 / 8.00 GB | RAM: 9.08 / 15.71 GB | CPU: 24.00 %
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detr-resnet-50
zebras.png
sam2-hiera-large
What’s in this image?
Qwen2.5-VL-3B-Instruct
meeting.wav
whisper-tiny
YOUR LOCAL WORKSPACE
What would you like to run today?
Pick from your library, browse the Hub, or paste a model id.
All VLM Text Segmentation SAM Detection Classify Diffusion Depth Docs / OCR ASR TTS Embeddings
INSTALLED · 5
  • Florence-2-base
    microsoft · image-text-to-text
    462 MB
  • whisper-tiny
    openai · automatic-speech-recognition
    150 MB
  • detr-resnet-50
    facebook · object-detection
    165 MB
  • segformer-b0-ade-512
    nvidia · image-segmentation
    14 MB
  • Llama-3.2-1B-Instruct
    meta-llama · text-generation
    2.5 GB
SUGGESTED FOR YOU
  • InternVL2_5-1B
    OpenGVLab · image-text-to-text
    ↓ 1.9 GB
  • SmolLM3-3B
    HuggingFaceTB · text-generation
    ↓ 6.0 GB
  • sam2.1-hiera-tiny
    facebook · mask-generation
    ↓ 150 MB
  • stable-diffusion-xl-base-1.0
    stabilityai · text-to-image
    ↓ 6.9 GB
  • bark-small
    suno · text-to-speech
    ↓ 1.2 GB

See it in action.

Three different models, three different tasks, all running locally on the same machine.

Input photo
input a photo from your disk
Detection output with bounding boxes
output bounding boxes & labels
facebook/detr-resnet-50 · object-detection · 167 MB · runs on CPU or GPU
Object detection

Find what’s in the frame.

Spot objects in a photo with DETR. Get bounding boxes, labels, and confidence scores, with inference running on your own machine.

Input photo
input a photo with point prompts
Segmentation masks output
output per-pixel masks
facebook/sam-vit-base · mask-generation · 375 MB · runs on CPU or GPU
Image segmentation

Go beyond the bounding box.

Select objects with point prompts and let SAM trace their outlines. Get per-pixel masks that separate your subjects from the background.

“Hi, how are you? How’s your day going?”
prompt your text
audio press play
facebook/mms-tts-eng · text-to-speech · 145 MB · runs on CPU or GPU
Text to speech

Give your words a voice.

Turn a text prompt into spoken audio with MMS-TTS. Play the generated speech right in the app, with inference running locally.

API and MCP Support

One switch in Settings turns your local models into an OpenAI endpoint - and into tools Claude can call. Off by default. Localhost only. It never serves the app's interface.

chat.py
from openai import OpenAI

client = OpenAI(base_url="http://localhost:11500/v1", api_key="local")

resp = client.chat.completions.create(
    model="Qwen/Qwen2.5-0.5B-Instruct",
    messages=[{"role": "user", "content": "Hello!"}],
    stream=True,
)
  • ◇
    Drop-in OpenAI SDK. Set base_url, use any api key. Nothing else changes.
  • ◈
    LangChain & LangGraph. ChatOpenAI(base_url=…) just works, so your agents run on local weights.
  • ≋
    Streaming. stream=True streams tokens over SSE, exactly like the hosted API.
  • ⚙
    Tool & function calling. Parsed per family - Qwen · Hermes · Llama · Mistral.
  • ☰
    Shares warm models. It runs inside the engine, so it reuses what the app already loaded - not a second copy.

Claude, with your models.

Register the MCP server once - the app copies the exact command for your install - and Claude can run anything ZeroInfer has installed. Eleven tools.

▣detect_objects
▦segment_image
✦generate_image
♬transcribe_audio
♪text_to_speech
✎generate_text
⋮embed_text
⚲search_models
↯download_model
☰list_models
◉zeroinfer_status

Not just LLMs.

Eleven task workspaces. Every major modality.

⊡

Detection

DETR, YOLOS, RT-DETR, D-FINE, Table Transformer. Draws labeled boxes server-side.

◉

Segmentation

SegFormer, Mask2Former, OneFormer, EoMT. Panoptic, instance, semantic. Composited overlays.

✦

Mask generation

SAM v1, SAM 2, SAM 2.1, SAM 3. Auto grid-sampling mode, full multi-region output.

☰

VLMs

Qwen-VL, LLaVA, Florence-2, Moondream, PaliGemma. Ask anything about an image.

♪

Speech

Whisper, Wav2Vec2, MMS for ASR. SpeechT5, Bark, VITS for TTS. Both directions, long-audio aware.

◈

Classification

ViT, ResNet, ConvNeXt, BEiT, SigLIP, CLIP. Image, zero-shot, audio. Confidence-ranked labels.

❋

Diffusion

Stable Diffusion, SDXL, FLUX, Kandinsky, PixArt. Text-to-image, img2img, inpaint.

⌨

Text generation

Llama, Mistral, Qwen, Gemma, Phi, DeepSeek. Chat-template aware, reasoning-model aware.

◐

Depth

DPT, MiDaS, ZoeDepth, Depth Anything v1/v2, Depth Pro. Single image → colorized depth map.

▤

Documents · OCR

TrOCR, Donut, LayoutLMv3, Pix2Struct. Read scanned pages, receipts, forms. Ask questions about them.

Everything in the Hub, ready to run.

200+ model families, each one verified against our architecture whitelist. If it shows up in ZeroInfer, it loads. No broken downloads, no missing packages, no guesswork.

Detection

DETRYOLOSRT-DETRRT-DETRv2D-FINEConditional-DETRDeformable-DETRTable-TransformerOWL-ViTOWLv2Grounding-DINO

Segmentation

SegFormerMaskFormerMask2FormerOneFormerEoMTUperNetBEiTDPTDETR-panopticMobileViT

Mask generation

SAMSAM 2SAM 2.1SAM 3MedSAM

VLMs

Qwen-VLQwen2.5-VLQwen3-VLLLaVALLaVA-NextViP-LLaVAFlorence-2MoondreamPaliGemmaIdefics 2/3SmolVLMKosmos-2InternVLPixtralFastVLMLFM2-VLDeepSeek-VLJanus-ProFuyuOvisAriaGLM4VCohere2-VisionEmu3

Text generation

Llama 3/4GPT-OSSMistral 3Qwen 2/3Gemma 2/3/3nPhi 3/4DeepSeekSmolLM3OLMo 3OLMoEFalcon-H1Nemotron-HBitNetStarCoder 2CohereGraniteMiniMax

ASR · TTS

WhisperDistil-WhisperWav2Vec2MMSMoonshineParakeetSpeechT5BarkVITS

Diffusion

SD 1.5SD 2.1SDXLSD 3 / 3.5FLUX.1KandinskyPixArtSanaKolors

Classification

ViTDeiTSwinConvNeXtBEiTResNetEfficientNetMobileNetCLIPSigLIPSigLIP 2

Depth

DPTGLPNZoeDepthDepth AnythingDepth Anything v2Depth ProMiDaS

Documents · OCR

TrOCRDonutLayoutLMLayoutLMv2LayoutLMv3Pix2Struct