DeepSeek's lightweight fast model variant offered with discounted credits on Workbuddy.
Google has published the first Android Bench results for Kimi K3.1 Pro and DeepSeek V4.1 Flash, with Kimi reaching a 24.0% pass rate above Claude and Gemini entries while DeepSeek delivers strong cost efficiency at $9.9 per run. The benchmark targets real Android engineering tasks, giving developers a quantified reference for long-horizon agent capability.
Meta Superintelligence Lab released Muse Ember, its lightest and most cost-efficient model yet, built for the repetitive work agents do all day: tool calls, coding subtasks, routing, extraction, and long document parsing. At 10 cents per million input tokens, Meta positions Ember as cheaper and smarter than Anthropic's Haiku and OpenAI's Luna on Artificial Analysis's composite benchmark, while staying price-competitive with open-source rivals DeepSeek V4.1 Flash and GLM 5.3 Flash. Ember is designed to pair with a larger model such as Muse Wonder inside an agentic harness.
Tencent Workbuddy apologized for failing to announce the end of its DeepSeek-V4.1 Flash discount, and will settle credits consumed between Nov 5 and Nov 8 at 50% of list price, auto-refunding the difference. The incident is an operational pricing-communication misstep rather than a change in model capability or product features.