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  3. Multimodal
  4. LLaVA-NeXT
open sourcemultimodal

LLaVA-NeXT

Free open-source GPT-4V alternative — chat with any image locally

Developed by Haotian Liu et al. (UW-Madison & Microsoft Research)

Try Model
7B / 13B / 34B / 72B / 110BParams
YesAPI
stableStability
LLaVA-NeXT 34BVersion
Apache 2.0License
PyTorchFramework
YesRuns Local

Playground

Implementation Example

Example Prompt

user input
[Image: invoice.png] Extract the vendor name, invoice date, total amount, and line items from this invoice. Return as JSON.

Model Output

model response
{"vendor": "Acme Office Supplies", "invoice_date": "2026-04-15", "total": 384.27, "currency": "USD", "line_items": [{"item": "Standing Desk", "qty": 1, "price": 299.00}, {"item": "Monitor Arm", "qty": 2, "price": 42.63}]}

Examples

Real-World Applications

  • Document AI
  • chart-to-data extraction
  • visual Q&A
  • accessibility apps
  • content moderation
  • e-commerce description generation
  • educational tutoring with visuals.

Docs

Model Intelligence & Architecture

What is LLaVA-NeXT?

LLaVA-NeXT (also called LLaVA-1.6) is the next generation of the popular open-source multimodal AI LLaVA (Large Language and Vision Assistant), developed by researchers at UW-Madison, Microsoft Research, and Columbia University. Released in early 2024, it dramatically improves visual reasoning, OCR, and high-resolution image understanding over the original LLaVA.

The model is open-sourced under the Apache 2.0 license, with weights based on Mistral-7B, Vicuna-7B, Vicuna-13B, and Nous-Hermes-Yi-34B base models — all free for commercial use.

Why LLaVA-NeXT Is Trending in 2026

As enterprises demand visual AI for documents, charts, and diagrams without paying GPT-4V or Claude Vision per-image fees, LLaVA-NeXT has become the go-to free multimodal AI for self-hosting. With improvements in OCR, chart understanding, and 4× higher input resolution than LLaVA-1.5, it now matches or beats GPT-4V on many benchmarks.

The newer LLaVA-OneVision (mid-2024) and LLaVA-1.6 series are extending this lineage with even stronger visual reasoning.

Key Features and Capabilities

LLaVA-NeXT supports visual question answering, OCR, chart and diagram understanding, image captioning, multi-turn vision conversations, and document Q&A. It accepts images up to 672×672 (4× higher than LLaVA-1.5) with dynamic resolution scaling.

The 34B variant is particularly strong on reasoning-heavy visual tasks like math problems with diagrams and complex infographics.

Who Should Use LLaVA-NeXT?

LLaVA-NeXT is built for developers, AI researchers, document-AI teams, accessibility tool builders, and indie startups that need vision-language capabilities without paying GPT-4V's $10+ per million tokens.

Top Use Cases

Real-world applications include document intelligence (invoices, receipts, contracts), chart-to-data extraction, accessibility apps for the visually impaired, visual customer support, content moderation with images, e-commerce product description generation, and educational tutoring with visual aids.

Where Can You Run It?

LLaVA-NeXT runs via Ollama (ollama run llava:34b), LM Studio, vLLM, llama.cpp, and Hugging Face Transformers. The 7B model fits in 16 GB VRAM; 34B needs ~70 GB at BF16 or 24 GB at 4-bit quantization.

How to Use LLaVA-NeXT (Quick Start)

Easiest path: ollama pull llava:13b, then send a multimodal prompt with an image and question. For Hugging Face, use the llava-hf/llava-v1.6-mistral-7b-hf model with the AutoProcessor and AutoModelForVision2Seq classes.

When Should You Choose LLaVA-NeXT?

Choose LLaVA-NeXT when you need free, self-hostable visual AI with full data privacy. For production-grade visual reasoning at scale in 2026, also consider Qwen 2.5-VL, Gemma 3 27B (multimodal), or InternVL 2.

Pricing

LLaVA-NeXT is completely free under Apache 2.0. No API fees if self-hosted.

Pros and Cons

Pros: ✔ Apache 2.0 license ✔ Strong OCR and chart understanding ✔ 4× higher resolution than LLaVA-1.5 ✔ Multiple sizes (7B, 13B, 34B) ✔ Active community ✔ Free for commercial use

Cons: ✘ Vision quality below GPT-4V on complex tasks ✘ 672×672 max resolution ✘ Heavy GPU for 34B variant ✘ Surpassed by Qwen 2.5-VL on benchmarks

Final Verdict

LLaVA-NeXT is one of the most popular free multimodal AIs of 2026 — perfect for developers needing visual AI without per-image fees. Discover more multimodal AI at FreeAPIHub.com.

Evaluation

Advantages & Limitations

Advantages
  • ✓ Apache 2.0 license
  • ✓ Strong OCR and chart understanding
  • ✓ 4x higher resolution than LLaVA-1.5
  • ✓ Multiple sizes (7B-110B)
  • ✓ Active community
  • ✓ Free commercial use
Limitations
  • ✗ Below GPT-4V on complex tasks
  • ✗ 672x672 max resolution
  • ✗ Heavy GPU for 34B+
  • ✗ Surpassed by Qwen 2.5-VL

Important Notice

Verify Before You Decide

Last verified · Apr 29, 2026

The details on this page — including pricing, features, and availability — are based on our last review and may not reflect the provider's current offering. Providers update their products frequently, sometimes without prior notice.

What may have changed

Pricing Plans
Features & Limits
Availability
Terms & Policies

Always visit the official provider website to confirm the latest pricing, terms, and feature availability before subscribing or integrating.

Check official site

External Resources

Try the Model Official Website Source Code

Technical Details

Architecture
CLIP ViT + LLM (Mistral/Vicuna/Yi) with MLP projector
Stability
stable
Framework
PyTorch
License
Apache 2.0
Release Date
2024-01-30
Signup Required
No
API Available
Yes
Runs Locally
Yes

Rate Limits

No limits self-hosted

Pricing

Completely free under Apache 2.0

Best For

Developers needing self-hosted visual AI without GPT-4V API fees

Alternative To

GPT-4V, Claude Vision, Gemini Pro Vision

Compare With

llava vs gpt-4vllava-next vs qwen-vlllava 1.6 vs llava 1.5free multimodal aiopen source vision language

Tags

#Document AI#Visual Qa#Llava#Vision Language#Open Source AI#Multimodal AI

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