swe-bench

Poolside has released Laguna XS.2, a 33B total parameter Mixture-of-Experts model with 3B activated parameters per token, designed for agentic coding. The model features a 131,072-token context window, scores 68.2% on SWE-bench Verified, and is available under Apache 2.0 license with free API access.

Zhipu AI has released GLM-5.1, a freely available open-weight model designed for long-running programming tasks that achieves 58.4% on SWE-Bench Pro, edging out GPT-5.4 (57.7%) and Claude Opus 4.6 (57.3%). The model's core capability is iterative strategy refinement—it rethinks its approach across hundreds of iterations and thousands of tool calls, recognizing dead ends and shifting tactics without human intervention. However, GLM-5.1 trails on reasoning and knowledge benchmarks, scoring 31% on Humanity's Last Exam compared to Gemini 3.1 Pro's 45%.

Alibaba released Qwen3.6 Plus on April 2, 2026, featuring a 1 million token context window at $0.50 per million input tokens and $3 per million output tokens. The model combines linear attention with sparse mixture-of-experts routing to achieve a 78.8 score on SWE-bench Verified, with significant improvements in agentic coding, front-end development, and reasoning tasks.

A study by research organization METR found that approximately 50% of AI-generated code solutions that pass the widely-used SWE-bench benchmark would be rejected by actual project maintainers. The finding exposes a significant gap between industry-standard code generation benchmarks and real-world code review standards.