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South Korea Ships Two 700B+ AI Models

South Korea Ships Two 700B+ AI Models

Model Comparisons

SK Telecom's A.X K2 and LG's K-EXAONE 2.0 both launched within 48 hours under Apache 2.0 licensing, competing for Korea's National AI Foundation Model project.

South Korea released two frontier-scale open-source AI models within 48 hours of each other. SK Telecom published A.X K2, a 688-billion-parameter model, on Hugging Face on July 29, 2026; LG AI Research followed on July 31 with K-EXAONE 2.0, a 750-billion-parameter model. Both are competing for the same prize: Korea’s National AI Foundation Model project, a government initiative to prove the country can build frontier-class AI entirely with domestic technology.

Quick facts

  • K-EXAONE 2.0 (LG AI Research): 750 billion total parameters, 37 billion active per token, released July 31, 2026 under Apache 2.0.
  • A.X K2 (SK Telecom): 688 billion parameters, released July 29, 2026, also Apache 2.0 licensed.
  • Both use a Mixture-of-Experts architecture with a 262,144-token context window — nearly identical technical blueprints from competing teams.
  • K-EXAONE 2.0 scored 70.1 average across 24 benchmarks, up from 63.3 for its 236-billion-parameter predecessor — a jump of over 10%, with a roughly 30% improvement specifically on coding and agentic-coding benchmarks.
  • On long-context comprehension (OpenAI-MRCR), K-EXAONE 2.0 scored 94.4, ahead of the 71.5 LG reports for Zhipu AI’s GLM-5.1 on the same test.

Why two labs shipped almost the same thing at almost the same time

This isn’t a coincidence of timing so much as a shared deadline. Both companies are competing teams inside South Korea’s Independent (Sovereign) AI Foundation Model Project, run by the Ministry of Science and ICT, which is heading into a second-phase evaluation round. According to TechTimes’ reporting, a third major team — Motif Technologies — has not yet released a comparable public model ahead of the evaluation, leaving LG and SK Telecom as the two clearest public data points so far.

Both companies made the same licensing bet, too: full Apache 2.0, the same permissive license Meta uses for Llama, allowing any company anywhere to download, modify, and deploy either model commercially with no royalty and no obligation to release their changes. For LG specifically, that’s a real shift — The Elec reports that earlier EXAONE releases used more restrictive licensing, making K-EXAONE 2.0 the first fully commercially permissive release in the series.

What K-EXAONE 2.0 actually improved

LG’s model more than tripled in size from its 236-billion-parameter predecessor, and the performance gains tracked with that: a 10%+ jump in average benchmark score across 24 tests spanning nine categories — knowledge, math, coding, agentic tasks, instruction following, long-context understanding, multilingual performance, and safety — plus a roughly 30% improvement specifically on coding and agentic-coding evaluations. LG also added Multi-Token Prediction and a technology it calls DSpark, which the company says makes text generation three to five times faster during inference. Language support expanded to 10 languages, up from a narrower Korean-and-English focus.

LG’s own technical report is notably candid that the model doesn’t win every comparison — it acknowledges trailing some competitors in specific areas, even as it leads on long-context tasks like OpenAI-MRCR and the Korean-language Ko-LongBench benchmark, where LG reports K-EXAONE 2.0 beat China’s GLM-5.1 by more than 10% on average across the three long-context tests it compared.

What this means if you’re choosing an open-weight model

For teams evaluating open-source models to self-host or fine-tune, both releases are immediately usable under fully commercial terms, and both now sit in the same size and architecture class as the leading Chinese open-weight releases they’re explicitly benchmarked against. The practical differentiators right now are strongest multilingual coverage (K-EXAONE 2.0’s 10 languages) versus SK Telecom’s own positioning for A.X K2, and long-context performance, where LG’s published numbers currently lead. Neither model has had significant independent, third-party benchmark verification yet — the figures above come from each company’s own technical reporting.

Side by side: K-EXAONE 2.0 vs. A.X K2

  • Developer: K-EXAONE 2.0 — LG AI Research. A.X K2 — SK Telecom.
  • Release date: K-EXAONE 2.0 — July 31, 2026. A.X K2 — July 29, 2026.
  • Total parameters: K-EXAONE 2.0 — 750 billion. A.X K2 — 688 billion.
  • Architecture: both use a Mixture-of-Experts design with a 262,144-token context window — K-EXAONE 2.0 activates roughly 37 billion parameters per token, selecting 8 of 256 specialized expert modules for each generated token.
  • License: both Apache 2.0, fully commercial, no restrictions.
  • Predecessor size: K-EXAONE 2.0 more than tripled its 236-billion-parameter predecessor; SK Telecom has not published an equivalent first-generation comparison for A.X K2 in the reporting reviewed here.

The architectural convergence is itself notable: two separate Korean teams, working independently under the same government program, landed on nearly identical technical choices — MoE routing, the same context window length, the same licensing model. That’s less a coincidence than a signal about where the current competitive frontier for mid-size sovereign AI models actually sits right now.

Key takeaway

Two competing Korean teams just put frontier-scale, fully commercial open-weight models into the same window as the leading Chinese open releases, and did it under deliberate government pressure to prove Korea can build this domestically. Whichever model wins the government evaluation, both are already downloadable and usable today — worth a real evaluation against your own workload rather than taking either company’s benchmark numbers at face value.

Up Next
xAI Confirms Grok 4.6 and 4.7

xAI Confirms Grok 4.6 and 4.7

Grok

Elon Musk has put public timelines on Grok 4.6 and 4.7, while xAI has already shipped Grok Voice Think Fast 2.0, becoming the API default on August 5, 2026.

xAI is running an unusually tight release schedule this summer. Elon Musk has put public timelines on the next two Grok models — Grok 4.6 and Grok 4.7 — while the company has already shipped a new voice model, Grok Voice Think Fast 2.0, that becomes the default for Grok’s voice API on August 5, 2026.

Quick facts

  • Musk says Grok 4.6 arrives around August 7, 2026, roughly two weeks after Grok 4.5’s July 16 launch.
  • Grok 4.7 is expected a few weeks after that, described by Musk as a larger, 2.1-trillion-parameter model.
  • Grok Voice Think Fast 2.0 is live now via the xAI API, and becomes the default “grok-voice-latest” model on August 5, 2026, priced at $0.08 per minute of audio.
  • Grok 4.5, the current flagship, is a 1.5-trillion-parameter model priced at $2 per million input tokens and $6 per million output tokens, positioned specifically for coding and multi-step agentic tasks.

What Musk actually said

The Grok 4.6 timeline didn’t come from a press release — it came from Musk replying directly to a post on X. On July 24, 2026, Musk confirmed, “Grok 4.6 in 2 weeks and Grok 4.7 in 4 weeks.” He followed up on July 28 with more specifics, according to reporting from American Bazaar: Grok 4.6 is a 1.5-trillion-parameter model built around improved supervised fine-tuning and reinforcement learning, targeting an August 7 release, while Grok 4.7 will scale up further to 2.1 trillion parameters and improve on 4.6 across the board, with the tradeoff of being somewhat slower to serve despite better token efficiency.

Worth flagging: not every outlet agrees on the exact numbers. At least one other report describes Grok 4.6 as a 2-trillion-parameter model rather than 1.5 trillion, and xAI itself hasn’t published a full technical spec sheet for either model yet. Until xAI posts an official model card, treat any specific parameter count — including the ones above — as Musk’s stated intent rather than a confirmed final spec.

Where Grok 4.5 set the baseline

Grok 4.5 went public on July 16, 2026, built on what xAI calls a V9 foundation, and is explicitly positioned around coding and long, multi-step agentic work rather than general chat — reporting indicates it was trained in part on large volumes of real developer-agent session data through xAI’s integration with Cursor. According to figures cited by Basenor, it runs at 80 transactions per second and scores 29.0% on the SWE Marathon coding benchmark, ahead of the 26.0% reported for Claude Opus 4.8 — a comparison worth noting but treating as one outlet’s benchmark read rather than an independently verified head-to-head. Pricing sits at $2 per million input tokens and $6 per million output tokens.

Grok Voice Think Fast 2.0 is the part that’s actually shipping now

While the 4.6 and 4.7 timelines are still forward-looking, xAI’s own release notes confirm Grok Voice Think Fast 2.0 is available today, with meaningful gains in speech reasoning, transcription accuracy, and tool-use reliability over its predecessor. The company says the update is designed to improve performance across nearly all use cases without requiring any prompt changes. Starting August 5, 2026, the default “grok-voice-latest” routing moves from Think Fast 1.0 to 2.0 automatically; anyone who wants to stay on the older version needs to explicitly pin “grok-voice-think-fast-1.0” before that date. Pricing is transparent and flat at $0.08 per minute of audio.

xAI says early A/B testing on Starlink’s customer support line showed a meaningful increase in both sales conversion and support containment rates — a real-world enterprise use case rather than a benchmark score, though the specific figures haven’t been published.

Why xAI is moving this fast

A near-monthly cadence across model families is a deliberate competitive posture, not an accident. xAI is now backed by SpaceX, which announced its acquisition of xAI on April 17, 2026, giving the company deeper capital and infrastructure ties heading into a period where Google and OpenAI are both shipping updates on a similarly aggressive schedule. Fast, frequent releases let xAI respond to competitive pressure in smaller increments instead of waiting for a single, large flagship launch — at the cost of asking developers to keep re-benchmarking their own workloads every few weeks.

Common questions

Do I need to do anything before August 5? Only if you’re calling “grok-voice-latest” and specifically depend on Think Fast 1.0’s current behavior. Otherwise the upgrade to Think Fast 2.0 happens automatically with no code changes required.

Is Grok 4.6 available yet? No — as of publication it’s a stated target of around August 7, 2026, not a shipped model. Treat the date as Musk’s public commitment rather than a guaranteed release.

What’s actually different about Grok 4.5 versus a general chatbot? xAI has leaned specifically into coding and long, multi-step agentic workflows for this model line, rather than optimizing primarily for conversational chat — reflected in its Cursor integration and its benchmark focus on tasks like SWE Marathon.

How does the voice pricing compare? At $0.08 per minute, Grok Voice Think Fast 2.0 is priced flat per minute of audio rather than per token, which makes cost easier to predict for high-volume voice applications like customer support lines.

Key takeaway

If you’re building on Grok, the near-term action item is the voice model, not the frontier ones: the automatic switch to Grok Voice Think Fast 2.0 lands August 5, 2026, so pin the old version now if your application depends on Think Fast 1.0’s exact behavior. Grok 4.6 and 4.7 are worth watching but still subject to change — treat specific numbers as directional until xAI confirms them officially.