This leap is made possible by near-lossless accuracy under 4-bit weight and KV cache quantization, allowing developers to process massive datasets without server-grade infrastructure.

These models match or surpass leading U.S. alternatives like OpenAI’s GPT-5-mini and Anthropic’s Claude Sonnet 4.5 in ...

Users running a quantized 7B model on a laptop expect 40+ tokens per second. A 30B MoE model on a high-end mobile device ...

The shift from training-focused to inference-focused economics is fundamentally restructuring cloud computing and forcing ...

Here is a blueprint for architecting real-time systems that scale without sacrificing speed. A common mistake I see in ...

The startup Taalas wants to deliver a hardwired Llama 3.1 8B with almost 17,000 tokens/s with the HC1 – almost 10 times faster than previous solutions.

Multiverse’s flagship product is a platform called CompactifAI that reduces the amount of infrastructure needed to run AI models. According to the company, the software can halve training times and ...

For customers who must run high-performance AI workloads cost-effectively at scale, neoclouds provide a truly purpose-built solution.

This mini PC is small and ridiculously powerful.

Alibaba’s Qwen AI team has introduced a new Qwen3.5 Medium model series, adding fresh competition to the large language model ...

The chip industry built its identity on a single promise: transistor counts would double roughly every two years, delivering faster and cheaper computing in a reliable cadence. That promise, known as ...

The AI revolution has led to many ‘wow‘ moments for the tech world, but this one ranks right up there. Toronto-based AI ...