Cloud-Plattformen · 11.08.2026, 01:10 UTC
langcache-embed-v3-small, Mellum2-12B-A2.5B-Thinking, and LightOnOCR-2-1B models now available on Amazon SageMaker JumpStart
| Schweregrad | info |
|---|---|
| Kategorie | Cloud-Plattformen |
| Quelle | AWS What's New ↗ |
| Veröffentlicht | 11.08.2026 UTC |
Sicherheitsmeldung mit Schweregrad noch nicht bewertet. Technische Details im Tab „Originaltext“; empfohlene Schritte in der Checkliste.
Redis's langcache-embed-v3-small, JetBrains' Mellum2-12B-A2.5B-Thinking, and LightOn's LightOnOCR-2-1B models are now available on Amazon SageMaker JumpStart, expanding the portfolio of foundation models available to AWS customers. These three models bring specialized capabilities spanning semantic caching optimization, code-focused reasoning, and end-to-end document OCR, enabling customers to deploy high-performance, scalable AI solutions on AWS infrastructure. langcache-embed-v3-small is optimized for semantic caching in LLM applications. It maps sentences and paragraphs into a dense vector space purpose-built for identifying semantically equivalent queries regardless of phrasing, enabling intelligent cache hits that reduce redundant LLM calls and accelerate response times in high-volume inference workloads. Mellum2-12B-A2.5B-Thinking excels in code generation, debugging, multi-step reasoning, and agentic coding workflows. It uses a Mixture-of-Experts architecture (64 experts, 8 activated per token), activating only 2.5B of its 12B total parameters per forward pass with a 131,072-token context length. It emits explicit chain-of-thought reasoning traces before final answers, delivering high-throughput, low-latency inference ideal for routing, RAG, sub-agents, and private deployments. LightOnOCR-2-1B provides end-to-end multilingual document-to-text conversion for PDFs, scans, and images without brittle OCR pipelines. This 1B-parameter vision-language model directly transduces page images into clean, naturally ordered text, achieving state-of-the-art performance on …