# Amazon — Amazon SageMaker JumpStart: 2026 year-to-date in review

- Company: Amazon (amazon.com)
- Announced: 2026-10-19T21:14:44+00:00
- Category: not stated
- Coverage: not counted
- Announcement: no
- Group: routine
- Source: https://aws.amazon.com/blogs/machine-learning/amazon-sagemaker-jumpstart-2026-year-to-date-in-review/
- Record: https://forck.live/items/24775-amazon-sagemaker-jumpstart-2026-year-to-date-in-review
- Subject: Bedrock / Nova
- Models affected: Qwen 3.8-27B, Qwen3.5-122B-A10B, Qwen-AgentWorld-35B-A3B, Qwen3-Coder-Next, Qwen 3 Coder 30B, Qwen3-ASR-1.7B, Qwen3-TTS, Qwen3-VL-Embedding-2B, Qwen3-Reranker-4B, Cosmos3, Cosmos Reason 7B, MSA-Search, Nemotron 3.5 Lightning, Nemotron-3-Super-120B, Nemotron3 Ultra, Nemotron-Nano-12B-v2, Nemotron 3 Nano Omni, Nemotron 3.5 Super VL, Ministral-3, Voxtral-Mini-4B-Realtime, gemma-4-31B-it, Granite 4.0, granite-speech-4.1-2b, Command A, Rerank v3.5, FLUX.2 Small Decoder, FLUX.2-klein-base-4B, Muse-Glimmer-30B, GLM-5.2 FP8, Mellum2-12B

Amazon says SageMaker JumpStart onboarded more than 100 new models from 30 providers between January and September 2026, widening the catalog customers can deploy from its machine learning hub. The company attributes the expansion to faster open source releases and customer demand for choice across architectures, sizes and capabilities. Alibaba's Qwen accounts for 29 of the additions, spanning reasoning, mixture-of-experts, agentic, code, speech, embedding and reranking models, while NVIDIA contributes 17, including the Cosmos3 world foundation models and Nemotron variants. Mistral added 7 models, Google 6 Gemma 4 variants, IBM 4 Granite models and Cohere 4, with 33 more from providers such as MiniMax, Zhipu AI, DeepSeek, Moonshot AI and Black Forest Labs. Amazon says it prioritized multimodal models that handle vision, speech and documents natively, so customers can avoid chaining separate preprocessing models. It also onboarded quantized and compact models, such as Zhipu AI's GLM-5.2 FP8 and JetBrains' Mellum2-12B, for customers working to cut inference costs in production.

## Evidence

Verbatim from https://aws.amazon.com/blogs/machine-learning/amazon-sagemaker-jumpstart-2026-year-to-date-in-review/:

> From January through September 2026, SageMaker JumpStart onboarded over 100 new models across 30 distinct providers. This represents a significant expansion of the catalog, driven by the accelerating pace of open source model releases and growing customer demand for choice across model architectures, sizes, and capabilities.

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Record: https://forck.live/items/24775-amazon-sagemaker-jumpstart-2026-year-to-date-in-review
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