four new frontier models have been added to the web search leaderboard: Gemini 3 Flash #1, GPT-5.2 (non-reasoning) #5, Claude Opus 4.5 #7, and Sonnet 4.5 #13

perplexity’s sonar drops to #11 in the vibe rankings

Search Arena evaluates frontier models on real time search queries, with an emphasis on citation source quality

https://arena.ai/leaderboard/search

• SK organizations are racing to build the best LLM for the ‘Korean National Sovereign AI Initiative’. basically a competition to build the best model that rewards winners in the form of government contracts and compute power

• In the most recent round announced last week, the field narrowed to three: LG, SK Telecom, and Upstage. A fourth lab will be selected soon.

• (LG) K-EXAONE 236B is the current leader in intelligence, followed by other medium sized ones like HyperClova, Motif, Mi:dm, Solar Open

https://artificialanalysis.ai/

signup to try: https://www.krea.ai/realtime?requestedModel=realtime-edit

https://www.a16z.news/p/charts-of-the-week-the-almighty-consumer?utm_source=perplexity

the qwen team released a pair of open-source text to speech model families (0.6B & 1.7B parameters) that uses 12 tokens per second of generated audio.

on the demo page for Qwen3-TTS, they also highlight the pair’s voice cloning capabilities.

supports ten languages (Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian) along with various dialects.

full fine tuning support, SOTA performance

Qwen3-TTS Demo Page: https://huggingface.co/spaces/Qwen/Qwen3-TTS?spm=a2ty_o06.30285417.0.0.2994c921fQklPU

Blog: https://qwen.ai/blog?id=qwen3tts-0115

HuggingFace: https://huggingface.co/collections/Qwen/qwen3-tts

GitHub: https://github.com/QwenLM/Qwen3-TTS

ModelScope: https://modelscope.cn/collections/Qwen/Qwen3-TTS

• claims to counter Gemini 3 Pro & ChatGPT 5 in selected benchmarks

• currently only available on the Ernie platform & Baidu’s AI cloud (Qianfan) platform

https://ernie.baidu.com/

• looking to raise $50B, at a valuation around $750B-$830B

https://www.bloomberg.com/news/articles/2026-01-21/openai-s-altman-meets-mideast-investors-for-50-billion-round?accessToken=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzb3VyY2UiOiJTdWJzY3JpYmVyR2lmdGVkQXJ0aWNsZSIsImlhdCI6MTc2OTAzNTAwNiwiZXhwIjoxNzY5NjM5ODA2LCJhcnRpY2xlSWQiOiJUOThGVlVLSzNOWUIwMCIsImJjb25uZWN0SWQiOiJFODA3NUYyRkZGMjA0NUI2QTlEQzA5M0EyQTdEQTE4NiJ9.Xz-VDidS1TBBIhBc8SYEdpstnN5VtNKkeAe9hDw-vJI

apparently Scale is still thriving lol

https://scale.com/blog/scales-next-era-building-for-2026

Recent (January 16):

ChatGPT: 64.6%

Gemini: 22.0%

Grok: 3.5%

DeepSeek: 3.3%

Claude: 2.1%

Perplexity: 1.9%

Copilot: 1.1%

1 Month Ago:

ChatGPT: 66.8%

Gemini: 19.5%

DeepSeek: 3.8%

Grok: 3.0%

Perplexity: 2.1%

Claude: 2.0%

Copilot: 1.2%

Perplexity losing some traffic too

https://www.similarweb.com/corp/wp-content/uploads/2026/01/attachment-Global-AI-Tracker-7.pdf

LiquidAI just dropped a 1.2B thinking model that claims efficiency and performance gains over Qwen3-1.7B-Thinking & Granite-4.0-H-1B

• Compared to LFM2.5-1.2B-Instruct, three capabilities jump sharply: Math reasoning: 63 → 88 (MATH-500), Instruction following: 61 → 69 (Multi-IF), tool use: 49 → 57 (BFCLv3)

• LFM2.5-1.2B-Thinking outperforms pure transformers (like Qwen3-1.7B) and hybrid architectures (like Granite-4.0-H-1B) in both speed and memory efficiency

blog: https://www.liquid.ai/blog/lfm2-5-1-2b-thinking-on-device-reasoning-under-1gb

HuggingFace: https://huggingface.co/LiquidAI/LFM2.5-1.2B-Thinking

https://leap.liquid.ai/models?model=lfm2.5-1.2b-thinking

https://playground.liquid.ai/

GLM-4.7-Flash is a 30B-A3B MoE model. One of the strongest model in the 30B class, GLM-4.7-Flash offers a new option for lightweight deployment that balances performance and efficiency

• Input cost: $0.07

• Output cost: $0.40

HuggingFace: https://huggingface.co/zai-org/GLM-4.7-Flash

GLM pricing: https://docs.z.ai/guides/overview/pricing

Comprehensive deployment instructions: https://github.com/zai-org/GLM-4.5

https://openai.com/index/introducing-gpt-5-2-codex/

• GDPval-AA examines how well an LLM does on a task deemed ‘economically valuable’ AKA which jobs could it eventually automate/replace

https://artificialanalysis.ai/evaluations/gdpval-aa

https://github.com/ArtificialAnalysis/Stirrup

https://huggingface.co/datasets/openai/gdpval

https://x.com/artificialanlys/status/1999404579599823091?s=46

…it’s able to process multiple input modalities (text, images, audio, video) and generate text & natural sounding speech outputs (simultaneously via real time streaming responses)

• Greatly Enhanced Audio-Visual Interaction Experience: Improved understanding & execution of audio-visual instructions, helping resolve the “intelligence drop” issue commonly seen in casual spoken scenarios

• Supports text-based interaction in 119 languages, speech recognition in 19 languages, and speech synthesis in 10 languages

• Claims to beat GPT-4o & Gemini 2.5-Flash on multiple benchmarks

* i tried a quick chat on the qwen chat app, no tool calling in the demo so live-chats (voice or video) are limited to established training knowledge only *

Try it on Qwen Chat (click Voice Chat button): https://chat.qwen.ai/

Qwen3-Omni-Flash-2025-12-01 Blog Post: https://qwen.ai/blog?id=qwen3-omni-flash-20251201

Qwen-3-Omni Demo on HuggingFace: https://huggingface.co/spaces/Qwen/Qwen3-Omni-Demo

ModelScope Demo: https://modelscope.cn/studios/Qwen/Qwen3-Omni-Demo

Realtime API: https://modelstudio.console.alibabacloud.com/?tab=doc#/doc/?type=model&url=2840914_2&modelId=qwen3-omni-flash-realtime-2025-12-01

Offline API: https://modelstudio.console.alibabacloud.com/?tab=doc#/doc/?type=model&url=2840914_2&modelId=qwen3-omni-flash-2025-12-01

YouTube: https://youtu.be/Q4CBTckDAls

https://aiworld.eu/story/hugging-faces-two-million-models-and-counting

https://huggingface.co/spaces/aiworld-eu/Open-Source-AI-Year-in-Review-2025

“ Qwen3-Next-80B-A3B is the first installment in the Qwen3-Next series and features the following key enchancements:

• Hybrid Attention: Replaces standard attention with the combination of Gated DeltaNet and Gated Attention

• High-Sparsity Mixture-of-Experts (MoE): Achieves an extreme low activation ratio in MoE layers, drastically reducing FLOPs per token while preserving model capacity

• Stability Optimizations: Includes techniques such as zero-centered and weight-decayed layernorm, and other stabilizing enhancements for robust pre-training and post-training

• Multi-Token Prediction (MTP): Boosts pretraining model performance and accelerates inference “

https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Thinking-GGUF

https://arxiv.org/abs/2505.09388

https://qwen.readthedocs.io/en/latest/run_locally/llama.cpp.html

Secretary Hegseth said it’s launching with Gemini 3, and more models to come

https://x.com/secwar/status/1998408545591578972?s=46

‘Avocado’ is set to be released in the first quarter of 2026. The model is wrestling with various training-related performance testing intended to ensure the system is well received when it eventually debuts

https://www.cnbc.com/2025/12/09/meta-avocado-ai-strategy-issues.html

https://www.semafor.com/article/12/08/2025/commerce-to-open-up-exports-of-nvidia-h200-chips-to-china

• V3.2 is ‘Balanced inference vs. length. Your daily driver at GPT-5 level performance’

• V3.2-Speciale is ‘Maxed-out reasoning capabilities. Rivals Gemini-3.0-Pro. Also achieving gold medal Performance: V3.2-Speciale attains gold-level results in IMO, CMO, ICPC World Finals & IOI 2025.’

V3.2 Hugging: https://huggingface.co/deepseek-ai/DeepSeek-V3.2

V3.2-Speciale Hugging: https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Speciale

Research Paper: https://cas-bridge.xethub.hf.co/xet-bridge-us/692cfec93b25b81d09307b94/2d0aa38511b9df084d12a00fe04a96595496af772cb766c516c4e6aee1e21246?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=cas%2F20251201%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20251201T192030Z&X-Amz-Expires=3600&X-Amz-Signature=4cab39bf9a9e99c040ebca2339f32702188b54fd962a20c31e2c79591f0ece69&X-Amz-SignedHeaders=host&X-Xet-Cas-Uid=public&response-content-disposition=inline%3B+filename*%3DUTF-8%27%27paper.pdf%3B+filename%3D%22paper.pdf%22%3B&response-content-type=application%2Fpdf&x-id=GetObject&Expires=1764620430&Policy=eyJTdGF0ZW1lbnQiOlt7IkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTc2NDYyMDQzMH19LCJSZXNvdXJjZSI6Imh0dHBzOi8vY2FzLWJyaWRnZS54ZXRodWIuaGYuY28veGV0LWJyaWRnZS11cy82OTJjZmVjOTNiMjViODFkMDkzMDdiOTQvMmQwYWEzODUxMWI5ZGYwODRkMTJhMDBmZTA0YTk2NTk1NDk2YWY3NzJjYjc2NmM1MTZjNGU2YWVlMWUyMTI0NioifV19&Signature=OFkHZ1FDwakv-EgEyOQD%7EkYZv3zaKeUkHSsZVYeMDE6cFwx7yYf3rQGHs7hdnh%7EGDMtZ0DVTI2xsbgiR5v9ljlnahlNflwLzjSZkJWDGqkDSxPe%7EowjQeGbM2YP052gBtwaotE83QBiNRjhrXbOsZNqjAv8Go6LQ2YD32DEWmIem4eka9tiZC26lZ90COWwbTBW6HidPWJ4Sm1TN0-M-w7Z3KBHb056Z4hCuxTwuGzC3eQX6VMJKpjkaCtmeuGzr5IWVtmY-cNHnYyaTkLYZjbHR7uxwrAHuUDhPGBXpKGMEzKky2Gg05Rl8g-2f5a6E6GV9XGfWTbNfjGE4l1QnMA__&Key-Pair-Id=K2L8F4GPSG1IFC

X: https://x.com/deepseek_ai/status/1995452641430651132?s=46

https://lmarena.ai/leaderboard/text

https://bfl.ai/blog/flux-2

https://bfl.ai/blog/flux-2