Trade.xyz Acquires Code NU for 578.7 HYPE

Beating AI News Brief: AI startup Xplore has launched RWE-Bench, a benchmark to test large language models (LLMs)’ ability to solve real-world engineering problems. 11 models were evaluated on 20 tasks spanning mechanical, electrical, and aerospace engineering. GPT-6 Astra ranked first with a 37% single-attempt average pass rate, followed by Claude Opus 5.5 at 29% and GPT-6.1 Sol at 25%. Five models, including DeepSeek V4.1 Flash, GLM-5.3, and Grok 4.7, failed all tasks. The tasks covered engine crankshaft design, circuit board routing, and turbine blade thermal simulation: crankshaft design requires balancing size, weight, strength, and fatigue life; routing an 8-layer circuit board with nearly 300 installed components demands connecting 71 signal lines while controlling timing errors and impedance; turbine blade thermal simulation needs accurate calculation of heat transfer between high-temperature airflow and the blade. Each model used its respective Agent toolchain to operate professional engineering software directly. Each test ran for a maximum of 24 hours, with 5 independent attempts per task. Submitted designs were automatically validated via engineering software and physical solvers; any unmet hard requirement resulted in a failure. Out of 1,100 total tests, 4 tasks remained unsolved. However, after allowing 5 attempts per task, Claude Opus 5.5’s task pass rate rose to 70%, overtaking GPT-6 Astra’s 60%. Xplore aims to turn such engineering tasks into reinforcement learning training environments, enabling AI to improve engineering capabilities through repeated design, simulation, and error correction.

Unitree Technology announced that its operating revenue for the third quarter of 2026 reached 665 million yuan, up 69.93% year-on-year; net profit attributable to shareholders of the parent company stood at 113 million yuan, down 17.37% year-on-year; non-recurring net profit was 105 million yuan, a year-on-year decrease of 17.42%. For the first three quarters of 2026, its operating revenue totaled 1.817 billion yuan, up 55.71% year-on-year; net profit attributable to the parent company was 387 million yuan, a year-on-year increase of 270.54%; non-recurring net profit came in at 349 million yuan, down 18.78% year-on-year.

Beating AI Express News: Liquid AI has launched its third-generation base model LFM3, rolling out six small models each with around 2 billion parameters, covering text, vision, speech and decision-making tasks. The 1.7B text model supports a 256K context window, with 4-bit quantized weights weighing only about 1GB. All six models support single-GPU fine-tuning, allowing enterprises to train them on their own data before deploying to mobile devices, personal computers or private servers. Liquid AI redesigned the model architecture, combining short convolutions, local attention and global attention, and specialized training for agent tasks such as tool calls and web operations. Compared to the previous LFM2.5-2.6B, the new models have around 35% fewer parameters but deliver significant performance improvements on some tasks. In official tests, LFM3-1.7B scored 38.42 on the WebArena-Verified browser operation task, versus just 3.02 for the prior generation, and outperformed Qwen3.5-9B (28.94), which has roughly 5 times more parameters. In the AutomationBench enterprise workflow test, its task success rate reached 41.29%, while Qwen3.5-9B scored 15.10%. However, results reversed for complex programming and long text tasks: in the SWE-bench Verified programming test, LFM3-1.7B scored 43.4, lower than Qwen3.5-9B's 51.2. In the 128K long text test, the two models notched scores of 65.6 and 87.1 respectively. Liquid AI also explicitly noted in its model card that this small model is not recommended for complex agent programming tasks.

On-chain analyst Specter has detected that the attacker linked to Bloom Trading is engaged in large-scale money laundering activities. Their transfer behavior exhibits automated traits, including repeated splitting, merging, and cross-chain movements across thousands of addresses. The attacker has utilized 2,152 unique routes and target addresses: 1,326 on Solana, 822 on EVM, and 5 on Zcash. To date, they have cross-transferred 26.099 ZEC to the Sapling shielded pool.

Meet the recent "king of liquidations" — $ETH short 0xb15b! 9 days ago, this trader created wallet 0xb15b, deposited 1.25M $USDC, and started shorting $ETH. Since then, he's been liquidated 13 times, with a total of 18,080 $ETH ($43.9M) liquidated and $1.14M lost.

According to Lookonchain's monitoring, 9 hours ago, Bitcoin mining company MARA Holdings transferred another 1,000 BTC (worth approximately $80.66 million) to BitGo.