
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.
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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.

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Qwen3.6-27B is a 27B dense open-weight multimodal model from Alibaba that scores 77.2% on SWE-bench Verified - beating Alibaba's own 397B MoE - under Apache 2.0.

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.

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Alibaba's first closed-weights flagship Qwen ships with a 256K context window, tops six agentic coding benchmarks, and ranks third on the Artificial Analysis Intelligence Index.

Moonshot AI's Kimi K2.6 is a 1T-parameter MoE with 32B active per token, 256K context, a 300-agent swarm running 4,000 coordinated steps, and the top SWE-Bench Pro score among open-weight models at 58.6%.

Alibaba released Qwen3.6-Max-Preview on April 20 as its first closed-weights flagship, ranking third globally on the Artificial Analysis Intelligence Index while topping six coding benchmarks.

Moonshot AI releases Kimi K2.6 under Modified MIT with open weights on HuggingFace, 300-agent swarm execution, and the highest SWE-Bench Pro score among open models.