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LG AI Research opens its 750B K-EXAONE 2.5 model to developers through a free API

LG AI Research has launched the EXAONE API Platform with free access to K-EXAONE 2.5, a 750 billion parameter Korean and English model with a 512K token context that it says now matches DeepSeek V4.1 Flash and GLM 5.3 on agentic benchmarks.

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LG AI Research has opened its EXAONE API Platform, putting its K-EXAONE 2.5 model in the hands of outside developers for the first time through a free API[1]. The lab announced the move on 9 November at NVIDIA AI Day Seoul 2026 at COEX in Seoul[4].

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What is available

The platform's changelog says EXAONE foundation models are now available through the API and that the service is currently free of charge[1]. Two models are listed: K-EXAONE 2.5, which LG describes as its sovereign AI language model, and EXAONE Tabular, a small model for predictions on structured data[1][2].

According to LG's model card, K-EXAONE 2.5 has 750 billion parameters with 31 billion active, handles text only in Korean and English, and has a 512K token context window with a January 2026 knowledge cutoff[2]. It supports chat, tool calling, structured outputs, code generation and streaming[2].

The endpoint is OpenAI compatible, so existing client code can point at it with the model name k-exaone_v2.5[3]. The combined input and output budget is capped at 524,288 tokens, and a reasoning_effort parameter set to low, high or max (the default) controls how much the model thinks before answering[3].

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How it scores

K-EXAONE 2.5 is a technology validation model built by further training the second-generation model LG released in August[4][5]. LG compares it with DeepSeek V4.1 Flash and GLM 5.3 on four agentic benchmarks[2]:

Benchmark K-EXAONE 2.5 K-EXAONE 2.0 DeepSeek V4.1 Flash GLM 5.3
SWE-Bench Pro 59.21 47.1 58.41 64.03
BrowseComp 78 50.87 75.8 79
AutomationBench 74.6 16.9 74.9 71.6
Claw-Eval 77.29 62.11 75.78 77.64

The scores are self-measured on open datasets[4]. Kim Eul-jeong, head of LG's Exaone Lab, said internal analysis across 24 evaluation metrics showed overall performance up more than 70% on the August model, achieved in about eight weeks[4].

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The road to a frontier model

LG frames the free API as real-world validation ahead of its next model. Co-head of research Lim Woo-hyung said the team is concentrating on a third-generation model and aims to complete an EXAONE model with frontier-level performance by January[4]. LG is also considering NVIDIA's Dynamo inference software to improve serving efficiency, and NVIDIA has already published a Dynamo guide for K-EXAONE[4].

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Why it matters

Free access to a 750B model with a half-million-token context is an easy way for developers outside Korea to try a non-US, non-Chinese frontier contender. The benchmark claims still need independent checks, and LG has not said how long the free period will last or what limits will apply once it ends[1].

FAQ

Frequently asked questions.

01

What did LG AI Research launch?

The EXAONE API Platform, which gives API access to its K-EXAONE 2.5 language model and its EXAONE Tabular structured data model. LG says the service is currently free.

02

How big is K-EXAONE 2.5?

LG lists it at 750 billion parameters with 31 billion active, a text-only model for Korean and English with a 512K token context window and a January 2026 knowledge cutoff.

03

How does it compare with DeepSeek and GLM?

On LG's own figures it scores 59.21 on SWE-Bench Pro, 78 on BrowseComp, 74.6 on AutomationBench and 77.29 on Claw-Eval, roughly level with DeepSeek V4.1 Flash and GLM 5.3. These are self-reported results.

04

How do developers use it?

Sign up for an API key at docs.exaone.ai and call an OpenAI-compatible chat completions endpoint with the model name k-exaone_v2.5. A reasoning_effort setting of low, high or max controls how long it thinks.

05

Are the weights open?

This release is API access only. LG has published weights for earlier K-EXAONE models on Hugging Face, but has not announced open weights for version 2.5.

06

What comes next?

LG says it is focused on a third-generation model and aims to complete a frontier-level EXAONE model by January 2027.