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“AWS” — 4 articles ✕

Models· Important· 🧪 Worth Testing

AWS and i14 ditch the KV cache with a 3B linear-attention model on Trainium2

AI research company i14 partnered with AWS to port its Laplace 3B model, a 24-layer architecture built on Gated Linear Attention (GLA) instead of standard transformer attention, onto AWS Trainium2 using native PyTorch (TorchNeuron Native). Rather than a KV cache that expands with every token, the model keeps a constant 29.5 MB recurrent state per sequence. On a single trn2.48xlarge instance, the team reached about 120,000 training tokens per second and served 11,544 output tokens per second across 1,280 simultaneous sequences through an unmodified vLLM engine.

AWS Machine Learning
Models

AWS Bedrock adds TwelveLabs' Pegasus 1.5 for structured video search

AWS has rolled out Pegasus 1.5, a video-language model built by TwelveLabs, as a fully managed option inside Amazon Bedrock. Unlike earlier versions that answered one question per clip, this release scans an entire video and outputs a JSON list of every moment matching criteria you define, complete with start and end times. It also handles longer recordings — up to two hours in one call — and lets you feed in a video straight from an S3 bucket or as a base64 string, skipping any indexing step.

AWS Machine Learning
Models· Important· 🧪 Worth Testing

Anthropic releases Claude Haiku 5.5 with 1M token context and adaptive thinking

Anthropic has launched Claude Haiku 5.5 (claude-haiku-5-5), positioned as its most capable Haiku model for high-volume, latency-sensitive work. It supports a 1 million token context window, up to 128k max output tokens, and adaptive thinking controlled via a new effort parameter. The model is available on the Claude API, Amazon Bedrock, Claude Platform on AWS, Google Cloud, and Microsoft Foundry. Anthropic warns that code written for the previous Haiku 4.5 model may break on the new version.

Claude Platform Release Notes
Models· Important· 🧪 Worth Testing

GLM 5.3 (753B MoE) from Z.ai launches on Amazon Bedrock with strong coding and security benchmarks

Z.ai's GLM 5.3, a 753-billion-parameter mixture-of-experts model optimized for coding and long-horizon agentic tasks, is now available as a fully managed model on Amazon Bedrock. It builds on GLM 5 with improved coding benchmark results, standout cybersecurity capabilities (CyberGym score of 84.5), and deeper Bedrock integration including OpenAI-compatible APIs, prompt caching, cross-Region inference and service tiers. AWS also demonstrates using GLM 5.3 with the open-source Strix agent for authorized penetration testing of your own applications.

AWS Machine Learning