Qwen3.6-27B
Qwen3.6-27B is a 27B dense open-weight multimodal model from Alibaba that scores 77.2% on SWE-bench Verified - beating Alibaba's own 397B MoE - under Apache 2.0.
Models
GLM-5.1
Z.ai's GLM-5.1 is an open-weight 754B MoE model that tops SWE-Bench Pro with 58.4, sustains 8-hour autonomous coding sessions, and runs under MIT license at $0.95/M input tokens.
GPT Image 2
GPT Image 2 (ChatGPT Images 2.0) brings 99%+ text accuracy, 2K resolution, web-search grounding, and a Thinking mode for character-consistent storyboards.
ERNIE 5.0
Baidu's ERNIE 5.0 combines 2.4 trillion parameters with native omni-modal design, landing at LMArena's top-10 globally and outpacing GPT-5 High on chart and document benchmarks.
EXAONE 4.5
LG AI Research's first open-weight vision-language model packs 33B parameters, 262K context, and STEM scores above GPT-5-mini - but ships under a non-commercial license.
Qwen3.5-Omni
Alibaba's Qwen3.5-Omni takes text, images, audio, and video as input and streams both text and speech output in a single end-to-end model with a 256K context window.
GPT-5.4-Cyber
OpenAI's GPT-5.4-Cyber is a cyber-permissive fine-tune of GPT-5.4 Thinking with binary reverse engineering, 88.23% on professional CTFs, and access gated through the Trusted Access for Cyber program.
Gemini 3.1 Flash TTS
Google's Gemini 3.1 Flash TTS ships in preview with 30 voices, 70-plus languages, 200-plus inline audio tags, and Elo 1,211 on the Artificial Analysis TTS Arena.
Veo 3.1
Google DeepMind's Veo 3.1 generates 4K video with native audio and is now free for every Google account at 10 clips per month via Google Vids.
Qwen3.6-Max-Preview
Alibaba's first closed-weights flagship Qwen ships with a 256K context window, tops six agentic coding benchmarks, and ranks third on the Artificial Analysis Intelligence Index.
GPT-Rosalind
OpenAI's first domain-specific reasoning model for biology and drug discovery, launched April 16 2026 as a US-only research preview with a 0.751 BixBench score.
Kimi K2.6
Moonshot AI's Kimi K2.6 is a 1T-parameter MoE with 32B active per token, 256K context, a 300-agent swarm running 4,000 coordinated steps, and the top SWE-Bench Pro score among open-weight models at 58.6%.
