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Ai Inference

17 GoKawiil briefs on this topic

Gimlet Labs raises $300M Series B led by Andreessen Horowitz for AI inference optimization

Gimlet Labs has closed a $300 million Series B funding round led by Andreessen Horowitz, with participation from Sapphire Ventures, Menlo Ventures, Arm, Samsung Ventures, Tiger Global and others. The company says it has added billions in contracted revenue and gigawatts of datacenter pipeline since March, and is scaling toward hundreds of megawatts of managed capacity, just five months after its Series A.

Analysts urge enterprises to rearchitect memory and storage for AI inference

Tirias Research founder Jim McGregor argues that AI is not one workload but millions of varied ones, meaning data centers can no longer treat memory and storage as secondary hardware. He says inference and agentic AI demand purpose-built systems capable of continuous, real-time data ingestion, caching, and movement rather than legacy infrastructure designed for training workloads.

Artificial Analysis and Liquid AI launch benchmark for phone-based small AI models

Artificial Analysis has begun benchmarking small AI models that run directly on mobile phones, focusing on models that fit within 8 GB of memory after quantization, including KV cache at 8K context. The effort combines intelligence benchmarks with real on-device inference data gathered in partnership with Liquid AI, whose measurement methodology Artificial Analysis says it has independently validated.

Z.ai unmasks mystery model Ox Alpha as open-weight GLM-5.3-Flash

An unidentified free model called Ox Alpha appeared on OpenRouter and quickly drew massive usage from developers who couldn't determine its origin, sparking days of speculation about which lab built it. Z.ai revealed the model was actually its own GLM-5.3-Flash, running entirely on Chinese chips, and priced at 15 cents per million input tokens and 50 cents per million output tokens, with a launch discount cutting that in half through September 9.

IBM previews mainframe chip that natively runs both Z and Arm instructions

At Hot Chips 2026, IBM unveiled an early look at a future mainframe processor featuring 11 IBM Z cores on a 2-nanometer process, clocked above 5.7 GHz, capable of natively executing both z/Architecture and AArch64 instructions on the same cores without emulation. The chip will include specialized accelerators for AI fraud detection, I/O, compression, cryptography and sorting, plus a large cache hierarchy topping out near 3.5 GB of virtual L4 cache. IBM hasn't named the chip or its host system but expects it around 2028, likely powering a future z18-class mainframe.