Model reference · open weights
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.
Summary of the OpenGVLab/InternVL2-Llama3-76B model card, 2026-10-30
What it is
| Released by | OpenGVLab |
|---|---|
| Released | 2024-07-15 |
| Parameters | 76.3B |
| VRAM | 153 GB for the weights |
What it runs on
| Card | Requests at once | Context max | Memory |
|---|---|---|---|
| 8K each | |||
| RTX 3060 12 GB … H200 141 GB 11 smaller cards | |||
| B200 180 GB | 5 | all 8K | 176 GB |
| 4× L40S 48 GB tensor parallel | 5 | all 8K | 44.0 GB a card |
| 2× H200 141 GB tensor parallel | 40 | all 8K | 138 GB a card |
| 4× H100 80 GB tensor parallel | 49 | all 8K | 78.1 GB a card |
| 4× A100 80 GB tensor parallel | 56 | all 8K | 78.2 GB a card |
| 2× B200 180 GB tensor parallel | 68 | all 8K | 176 GB a card |
| 4× RTX PRO 6000 Blackwell 96 GB tensor parallel | 72 | all 8K | 93.8 GB a card |
| Requests at once | 8K tokens each |
|---|---|
| 1 | 157 GB |
| 5 | 168 GB |
| 8 | 176 GB |
| 16 | 198 GB |
| 32 | 241 GB |
| 64 | 327 GB |
One card, with vLLM's small-card settings.
From the model card
[📂 GitHub] [📜 InternVL 1.0] [📜 InternVL 1.5] [📜 Mini-InternVL] [📜 InternVL 2.5]
[🆕 Blog] [🗨️ Chat Demo] [🤗 HF Demo] [🚀 Quick Start] [📖 Documents]
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 Name | Vision Part | Language Part | HF Link | MS Link |
|---|---|---|---|---|
| InternVL2-1B | InternViT-300M-448px | Qwen2-0.5B-Instruct | 🤗 link | 🤖 link |
| InternVL2-2B | InternViT-300M-448px | internlm2-chat-1_8b | 🤗 link | 🤖 link |
| InternVL2-4B | InternViT-300M-448px | Phi-3-mini-128k-instruct | 🤗 link | 🤖 link |
| InternVL2-8B | InternViT-300M-448px | internlm2_5-7b-chat | 🤗 link | 🤖 link |
| InternVL2-26B | InternViT-6B-448px-V1-5 | internlm2-chat-20b | 🤗 link | 🤖 link |
| InternVL2-40B | InternViT-6B-448px-V1-5 | Nous-Hermes-2-Yi-34B | 🤗 link | 🤖 link |
| InternVL2-Llama3-76B | InternViT-6B-448px-V1-5 | Hermes-2-Theta-Llama-3-70B | 🤗 link | 🤖 link |
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.
| Benchmark | GPT-4o-20240513 | Claude3.5-Sonnet | InternVL2-40B | InternVL2-Llama3-76B |
|---|---|---|---|---|
| Model Size | - | - | 40B | 76B |
| DocVQAtest | 92.8 | 95.2 | 93.9 | 94.1 |
| ChartQAtest | 85.7 | 90.8 | 86.2 | 88.4 |
| InfoVQAtest | - |
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.