Seed-OSS 36B: Revolutionizing Open-Source AI with Unmatched Context and Performance
10 days ago 高效码农ByteDance Seed-OSS 36B: A Practical Guide for Global Developers No hype, no jargon—just everything you need to decide whether ByteDance’s new 36-billion-parameter open-source model deserves a place on your GPU. 1. What Exactly Is Seed-OSS 36B? In plain English, Seed-OSS 36B is a family of open-source large language models created by ByteDance’s Seed Team. 36 B parameters 512 K native context length Apache 2.0 license 12 T training tokens Think of it as a midsize car that somehow offers the leg-room of a limousine. 2. Three Headline Features 2.1 Context Window That Swallows a Novel You can feed the model …
OLMo 2: Revolutionizing Open-Source Language Models with EEAT-Optimized Efficiency
1 months ago 高效码农OLMo 2: 2025’s Open-Source Language Model Benchmark TL;DR (200 words) OLMo 2 7B/13B models achieve 40% better training efficiency at 6M FLOPs, with GSM8K math accuracy reaching 67.5% (7B) and 75.1% (13B)[citation:2][citation:6]. The Dolmino Mix 1124 strategy boosts math capabilities by 300% through strategic data blending[citation:2][citation:9]. Architectural innovations (QK-norm + RMSNorm) improve training stability by 85% and reduce gradient spikes by 92%[citation:3][citation:7]. Inference speed exceeds Llama 3.1 by 18% while maintaining comparable performance[citation:6][citation:10]. Training efficiency comparison: OLMo 2 vs equivalent open-source models 1. Architectural Innovations (Core Keyword: Open-Source Language Model/Architecture Optimization) 1.1 Dynamic Architecture Upgrades OLMo 2 retains a decoder-only …