MODEL PROFILE

Intern-S1

internlm · Intern-S1

We introduce **Intern-S1**, our **most advanced open-source multimodal reasoning model** to date. Intern-S1 combines **strong general-task capabilities with state-of-the-art performance on a wide range of scientific tasks**, rivaling leading closed-source commercial models. Built upon a 235B MoE language model (Qwen3) and a 6B Vision encoder (InternViT), Intern-S1 has been further pretrained on **5 trillion tokens** of multimodal data, including over **2.5 trillion scientific-domain tokens**. This enables the model to retain strong general capabilities while excelling in specialized scientific domains such as **interpreting chemical structures, understanding protein sequences, and planning compound synthesis routes**, making Intern-S1 to be a capable research assistant for real-world scientific applications. Features We evaluate the Intern-S1 on various benchmarks including general datasets and scientifc datasets. We report the performance comparsion with the recent VLMs and LLMs below. Benchmarks Intern-S1 InternVL3-78B Qwen2.5-VL-72B DS-R1-0528 Qwen3-235B-A22B Kimi-K2-Instruct Gemini-2.5 Pro o3 Grok-4

Visual QAlicense:apache-2.0
Context windowNot disclosed
Input → OutputText、Image → Text
Model weightsNot verified
Profile updated2026/10/30 07:39:26
OVERVIEW

Model overview

We introduce **Intern-S1**, our **most advanced open-source multimodal reasoning model** to date. Intern-S1 combines **strong general-task capabilities with state-of-the-art performance on a wide range of scientific tasks**, rivaling leading closed-source commercial models. Built upon a 235B MoE language model (Qwen3) and a 6B Vision encoder (InternViT), Intern-S1 has been further pretrained on **5 trillion tokens** of multimodal data, including over **2.5 trillion scientific-domain tokens**. This enables the model to retain strong general capabilities while excelling in specialized scientific domains such as **interpreting chemical structures, understanding protein sequences, and planning compound synthesis routes**, making Intern-S1 to be a capable research assistant for real-world scientific applications. Features We evaluate the Intern-S1 on various benchmarks including general datasets and scientifc datasets. We report the performance comparsion with the recent VLMs and LLMs below. Benchmarks Intern-S1 InternVL3-78B Qwen2.5-VL-72B DS-R1-0528 Qwen3-235B-A22B Kimi-K2-Instruct Gemini-2.5 Pro o3 Grok-4

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

Source prices & cost analysis

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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Frequently asked questions

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Sources & traceability

许可证:apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。