Jev model queries Opus for help, matches accuracy at 4x lower cost
A developer demonstrated a Jev model that queries Opus for assistance, achieving Opus-level accuracy at 4x lower cost. The approach highlights a potential strategy for reducing inference expenses while maintaining high performance.
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OpenAI makes Decisions API generally available with voice, visual modalities
OpenAI has made its Decisions API, a competitor to Jev, generally available for the first time, according to TechCrunch. The API now includes new voice and visual modalities and is priced at $0.10 per 1 million input tokens with no output-token charges, intensifying competition in the decision-model API market.
2 reports · 2 sources
DeepSeek open-sources Super-agent architecture for autonomous bug-fixing agents
DeepSeek has publicly released the architectural blueprint for its Super-agent, a research prototype of a personal agent that maintains cross-session context to handle multi-task coordination. Internal tests show the agent can autonomously identify bugs and submit pull requests without being explicitly prompted, with a median task completion time of 12.4 minutes in simulated multi-task environments. DeepSeek positions this as a step toward reducing human attention bottlenecks in multi-task workflows.
Google launches Gemini 4 Argon frontier model with API rollout
Google DeepMind has released Gemini 4 Argon, the first frontier model in the Gemini 4 series, claiming it outperforms rivals like GPT-6 Astra and Claude Opus 5.5 across benchmarks in coding, cybersecurity, science, finance, and law. The model is available globally via the Gemini API, to Google AI Pro subscribers in the Gemini app and AI Mode, and in Antigravity for Ultra users. Launch pricing is $2 per million input tokens and $10 per million output tokens, with a 50% discount until November 30, after which prices double on December 1.
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DeepSeek releases V4.1-Flash-1017 open-weight model with faster, cheaper agent tasks
DeepSeek released V4.1-Flash-1017, an open-weight model checkpoint with 763B parameters, now live on its website, app, and API. The update claims stronger benchmark performance, faster task completion, and shorter outputs than its predecessor, achieved via reinforcement learning with self-feedback for end-to-end project development. DeepSeek also opened its Search & Fetch APIs to everyone, priced at $0.75 per 1000 successful requests, and requires DeepSeek Harness v0.2.1-rc.1 or later for optimal use.
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