Qwen3-Coder-Next
Qwen3-Coder-Next is an 80B MoE coding model from Alibaba that activates just 3B parameters per forward pass, scoring over 70% on SWE-Bench Verified with agent scaffolding under Apache 2.0.
Articles Tagged "MoE"
SU-01
SU-01 is a 30B-A3B MoE reasoning model from Shanghai AI Lab that achieves gold-medal performance on IMO 2025, USAMO 2026, and IPhO 2024/2025 using a three-stage training recipe and test-time scaling.
ZAYA1-8B
Zyphra's ZAYA1-8B is an 8.4B-parameter MoE reasoning model with only 760M active parameters that matches DeepSeek-R1-0528 on math and coding benchmarks while running at a fraction of the compute cost.
Nemotron 3 Nano Omni Unifies Vision, Audio, Language
NVIDIA's new open omni model activates 3B of 30B parameters, processes video, audio, and documents in one pass, and delivers up to 9.2x higher throughput than other open omni models.
Nemotron 3 Nano Omni
NVIDIA's first open omni-modal model: 30B total / 3B active hybrid Mamba-MoE that processes text, images, audio, and video in a single inference loop, with 9x higher throughput than comparable open omni models.
DeepSeek V4
DeepSeek V4 ships in two open-weight MoE variants - V4-Pro at 1.6T/49B active and V4-Flash at 284B/13B active - both with 1M-token context and MIT license, released April 24, 2026.
DeepSeek V4-Pro Review: Frontier Power, Penny Prices
DeepSeek V4-Pro matches Claude Opus 4.6 on SWE-bench at a fraction of the cost - a thorough review of what it gets right, where it still trails, and whether the price gap justifies the switch.
OpenAI Open-Sources Privacy Filter: 96% F1 PII Masker
OpenAI released Privacy Filter today, a 1.5B MoE with 50M active parameters that tags eight categories of PII in text. Apache 2.0, 128K context, runs in a browser via WebGPU.
Alibaba's Qwen3.6 Coder: 73.4 SWE-bench, 22GB VRAM
Qwen3.6-35B-A3B lands with 73.4 on SWE-bench Verified and Apache 2.0 weights, all from 3 billion active parameters routed through a 256-expert MoE. Fits on a single consumer GPU.
GLM-5.1
Z.ai's GLM-5.1 is an open-weight 754B MoE model that tops SWE-Bench Pro with 58.4, sustains 8-hour autonomous coding sessions, and runs under MIT license at $0.95/M input tokens.
ERNIE 5.0
Baidu's ERNIE 5.0 combines 2.4 trillion parameters with native omni-modal design, landing at LMArena's top-10 globally and outpacing GPT-5 High on chart and document benchmarks.
Qwen3.5-Omni
Alibaba's Qwen3.5-Omni takes text, images, audio, and video as input and streams both text and speech output in a single end-to-end model with a 256K context window.
