All tags
Topic: "token-consumption"
not much happened today
glm-5.2 glm-5.2-max opus-4.8 claude-fable-5 ornith-1.0 gemma-4 qwen-3.5 lfm2.5-230m gemini-3.5-flash codex z.ai databricks liquid-ai google-deepmind google sail hyperagent openai langchain coding-benchmarks agentic-ai reinforcement-learning model-optimization speculative-decoding hardware-optimization long-running-agents agent-persistence cost-efficiency computer-use safety-controls developer-tools token-consumption concurrent-agents philschmid gdb reach_vb eliebakouch
Z.ai's GLM-5.2 leads in coding and agent benchmarks with top scores like 1595 on Code Arena: Frontend and 34.29% reasoning accuracy with zero failures. Databricks improved GLM-5.2 speed to 392 tok/s using hardware and optimizations. Ornith-1.0, a new MIT-licensed coding model family, spans 9B to 397B parameters with strong benchmark results and a self-improving RL training method. Liquid AI released a small model for low-latency robotics/e-commerce use. Google integrated computer use into Gemini 3.5 Flash with safety controls and developer tools for device control. Startups like Sail and Hyperagent focus on long-running agents with persistent execution and cost efficiency. OpenAI reports growing internal Codex use for complex, cross-functional tasks, highlighting agent skill concurrency.