Model reference · open weights
InternVL2 is an open-weight language model from OpenGVLab. InternVL2-8B (BF16) weighs 16.2 GB; the smallest configuration that runs it is 2× RTX 3060 12 GB.
Summary of the OpenGVLab/InternVL2-2B model card, 2026-10-01. The estimate below is for another build of the family.
What it is
| Released by | OpenGVLab |
|---|---|
| Released | 2024-06-27 |
| Parameters | 2.2B |
| VRAM | 16.2 GB for the weights |
What it runs on
| Card | Requests at once | Context max | Memory | |
|---|---|---|---|---|
| 8K each | 32K each | |||
| RTX 3060 12 GB … RTX 4060 Ti 16 GB 2 smaller cards | — | — | — | |
| RTX 3090 24 GB | 4 | 1 | all 32K | 23.4 GB |
| RTX 4090 24 GB | 4 | 1 | all 32K | 23.4 GB |
| RTX 5090 32 GB | 11 | 2 | all 32K | 31.0 GB |
| L40S 48 GB | 24 | 6 | all 32K | 44.0 GB |
| A100 80 GB | 55 | 13 | all 32K | 78.2 GB |
| H100 80 GB | 52 | 13 | all 32K | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | 67 | 16 | all 32K | 93.8 GB |
| DGX Spark (GB10) 128 GB unified | 79 | 19 | all 32K | 107 GB |
| H200 141 GB | 108 | 27 | all 32K | 138 GB |
| B200 180 GB | 143 | 35 | all 32K | 176 GB |
| 2× RTX 3060 12 GB tensor parallel | 2 | — | 23K | 11.6 GB a card |
| 2× RTX 4060 Ti 16 GB tensor parallel | 9 | 2 | all 32K | 15.4 GB a card |
| 2× RTX 4090 24 GB tensor parallel | 24 | 6 | all 32K | 23.4 GB a card |
| 2× RTX 3090 24 GB tensor parallel | 24 | 6 | all 32K | 23.4 GB a card |
| Requests at once | 8K tokens each | 32K tokens each |
|---|---|---|
| 1 | 19.2 GB | 22.4 GB |
| 5 | 23.5 GB | 39.6 GB |
| 8 | 26.7 GB | 52.5 GB |
| 16 | 35.3 GB | 86.9 GB |
| 32 | 52.5 GB | 156 GB |
| 64 | 86.9 GB | 293 GB |
One card, with vLLM's small-card settings.
Builds
| Build | Params | Precision | Weights | Smallest setup |
|---|---|---|---|---|
| InternVL2-2B ↗ | 2.2B | BF16 | 4.4 GB | RTX 3060 12 GB |
| InternVL2-1B ↗ | 938M | BF16 | 1.9 GB | RTX 3060 12 GB |
| InternVL2-26B ↗ | 25.5B | BF16 | 51.0 GB | H100 80 GB |
| InternVL2-8B (above) ↗ | 8.1B | BF16 | 16.2 GB | 2× RTX 3060 12 GB |
| InternVL2-4B ↗ | 4.1B | BF16 | 8.3 GB | RTX 4060 Ti 16 GB |
| InternVL2-2B-AWQ ↗ | — | AWQ | 2.2 GB | RTX 3060 12 GB |
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 InternVL2-2B 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. InternVL2-2B consists of InternViT-300M-448px, an MLP projector, and internlm2-chat-1_8b.
| Benchmark | PaliGemma-3B | Mini-InternVL-2B-1-5 | InternVL2-2B |
|---|---|---|---|
| Model Size | 2.9B | 2.2B | 2.2B |
| DocVQAtest | - | 85.0 | 86.9 |
| ChartQAtest | - | 74.8 | 76.2 |
| InfoVQAtest | - | 55.4 | 58.9 |
| TextVQAval | 68.1 | 70.5 | 73.4 |
| OCRBench | 614 | 654 |
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.