Model reference · open weights

InternVL2-Llama3

LLMs OpenGVLab Vision + text 1 build Open, with conditions 4k dl/mo

InternVL2-Llama3 is an open-weight language model from OpenGVLab. InternVL2-Llama3-76B (BF16) weighs 153 GB; the smallest configuration that runs it is 4× L40S 48 GB.

For self-hosting, compare this build's requirements below with the GPU you plan to rent.

  • InternVL2-Llama3-76B is a multimodal large language model developed by OpenGVLab for image-text-to-text tasks.
  • It features 76.3B parameters and is trained with an 8k context window to handle long texts, multiple images, and videos.
  • The model is multilingual and released under the llama3 licence.

Summary of the OpenGVLab/InternVL2-Llama3-76B model card, 2026-10-30

What it is

Released byOpenGVLab
Released2024-07-15
Parameters76.3B
VRAM153 GB for the weights

What it runs on

Memory and cards for InternVL2-Llama3-76B (BF16)

153 GBweights, file size
328 MBcache per 1K tokens
2.2 GBruntime overhead, at least
8,192 tokenscontext max
CardRequests at onceContext maxMemory
8K each
RTX 3060 12 GB … H200 141 GB
11 smaller cards
B200 180 GB5all 8K176 GB
4× L40S 48 GB
tensor parallel
5all 8K44.0 GB a card
2× H200 141 GB
tensor parallel
40all 8K138 GB a card
4× H100 80 GB
tensor parallel
49all 8K78.1 GB a card
4× A100 80 GB
tensor parallel
56all 8K78.2 GB a card
2× B200 180 GB
tensor parallel
68all 8K176 GB a card
4× RTX PRO 6000 Blackwell 96 GB
tensor parallel
72all 8K93.8 GB a card
Memory needed at each load
Requests at once8K tokens each
1157 GB
5168 GB
8176 GB
16198 GB
32241 GB
64327 GB

One card, with vLLM's small-card settings.

From the model card

What OpenGVLab says about InternVL2-Llama3

Read the model card

[📂 GitHub] [📜 InternVL 1.0] [📜 InternVL 1.5] [📜 Mini-InternVL] [📜 InternVL 2.5]

[🆕 Blog] [🗨️ Chat Demo] [🤗 HF Demo] [🚀 Quick Start] [📖 Documents]

Introduction

We are excited to announce the release of InternVL 2.0, the latest addition to the InternVL series of multimodal large language models. InternVL 2.0 features a variety of instruction-tuned models, ranging from 1 billion to 108 billion parameters. This repository contains the instruction-tuned InternVL2-Llama3-76B model.

Compared to the state-of-the-art open-source multimodal large language models, InternVL 2.0 surpasses most open-source models. It demonstrates competitive performance on par with proprietary commercial models across various capabilities, including document and chart comprehension, infographics QA, scene text understanding and OCR tasks, scientific and mathematical problem solving, as well as cultural understanding and integrated multimodal capabilities.

InternVL 2.0 is trained with an 8k context window and utilizes training data consisting of long texts, multiple images, and videos, significantly improving its ability to handle these types of inputs compared to InternVL 1.5. For more details, please refer to our blog and GitHub.

Model NameVision PartLanguage PartHF LinkMS Link
InternVL2-1BInternViT-300M-448pxQwen2-0.5B-Instruct🤗 link🤖 link
InternVL2-2BInternViT-300M-448pxinternlm2-chat-1_8b🤗 link🤖 link
InternVL2-4BInternViT-300M-448pxPhi-3-mini-128k-instruct🤗 link🤖 link
InternVL2-8BInternViT-300M-448pxinternlm2_5-7b-chat🤗 link🤖 link
InternVL2-26BInternViT-6B-448px-V1-5internlm2-chat-20b🤗 link🤖 link
InternVL2-40BInternViT-6B-448px-V1-5Nous-Hermes-2-Yi-34B🤗 link🤖 link
InternVL2-Llama3-76BInternViT-6B-448px-V1-5Hermes-2-Theta-Llama-3-70B🤗 link🤖 link

Model Details

InternVL 2.0 is a multimodal large language model series, featuring models of various sizes. For each size, we release instruction-tuned models optimized for multimodal tasks. InternVL2-Llama3-76B consists of InternViT-6B-448px-V1-5, an MLP projector, and Hermes-2-Theta-Llama-3-70B.

Performance

Image Benchmarks

BenchmarkGPT-4o-20240513Claude3.5-SonnetInternVL2-40BInternVL2-Llama3-76B
Model Size--40B76B
DocVQAtest92.895.293.994.1
ChartQAtest85.790.886.288.4
InfoVQAtest-

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

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