As KDE irons out its LLM guidelines, a sub-community has sprung up to demand a ban on generative AI
A line is being drawn in the sand.
We haven't written up this one. XDA Developers has the full story — the link below goes straight to it.
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Kinetic-4B vs Claude Haiku 4.5: The 4B Model Wins Tools
Kinetic-4B wins on tool calling. On a 300-sample Composio evaluation, the 4-billion-parameter model from Bengaluru lab Conscious Engines scored 82.33% accuracy at 1.61s p95 latency, against 80.0% and…
- Kinetic-4B model outperforms Claude Haiku 4.5 in tool calling benchmark
- Achieves 82.33% accuracy, 95.33% tool-name accuracy, 1.61-second latency
- Smaller models cost-effective and faster for specific tasks like tool calling
DeepSeek V4.1-Flash Wins on Coding Agent Cost
Verdict: For coding agents, DeepSeek V4.1-Flash is the best open source LLM right now, because it lands level with Claude Opus 5 on software engineering while costing a fraction as much per million…
- DeepSeek V4.1-Flash leads in coding agent performance, scoring 74.2 in DeepSWE v1.1
- V4.1-Flash offers cost-effective pricing at $0.003 per 1M cached input tokens
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Agentic AI vs Generative AI: The 2026 Verdict
Generative AI wins for anyone producing content — drafts, images, code snippets, summaries — because it is cheaper, mature and easy to review.
- Generative AI excels at creating content like drafts, images, and summaries at low cost and ease.
- Agentic AI is ideal for multi-step workflows with verifiable results, such as fixing test suites.
- Only 40% of agentic AI projects are expected to succeed by 2027 due to costs and risks.