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The Model That Barely Slows Down: Gemma 4 26B vs Qwen 3.6 35B at Long Context
We ran Gemma 4 26B and Qwen 3.6 35B-A3B head-to-head on the same server, same quantization, same protocol. Gemma 4 is 3.7× faster at 32k context — and 7.2× faster at 128k. The gap widens with context, and the reason reveals something important about model selection for long-context workloads.
Same AI Model, Two Hardware Tiers — And Why Context Length Is the Hidden Variable
We put Qwen 3.6 35B-A3B on a developer laptop and a dual-GPU server. The speed gap grows from 2.4× to 5.3× as context grows — and the real bottleneck turns out not to be compute.
Meet AgentWorks: Your Business’s Most Valuable Employee Never Calls in Sick
Enterprise-grade AI agents designed specifically for businesses that value data privacy and operational efficiency. Unlike ChatGPT, AgentWorks agents are trained on your business and keep your data completely private.
The AWS Outage That Broke AI: What March’s Infrastructure Crisis Reveals About Cloud Dependencies
On March 1st, 2026, a catastrophic failure at Amazon Web Services' data centers in the United Arab Emirates sent shockwaves through the global AI ecosystem. What began as fires and emergency power shutdowns at AWS facilities quickly cascaded into a worldwide infrastructure crisis that exposed a uncomfortable truth: our AI future is [Read more...]
Three Security Incidents in Three Weeks: Why Private AI Is No Longer Optional
The last few weeks have delivered a masterclass in why trusting your most sensitive data to someone else's cloud is a gamble — and the house is starting to win. What Happened Three separate incidents. Three different organizations. One common thread: loss of control over data sent to cloud AI platforms. The [Read more...]
Private AI Without Compromise: Why Data Control Is Becoming the Enterprise Baseline
Artificial intelligence is rapidly becoming part of everyday work: drafting documents, analyzing data, summarizing research, and accelerating decision-making. But alongside that adoption, a critical question is emerging for organizations that handle sensitive information: Where does our data actually go when we use AI? Recent reporting and industry discussion have exposed an uncomfortable [Read more...]
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