Unverified50% confidenceBenchmarkExact time
The paper claims that across eight autoregressive and diffusion language model development environments, LM2LM enables Qwen3.8-27B to surpass GPT-6-sol in performance, even though the latter was given 300 real experiment records in its context.
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50%
Confidence
Medium-term (~90 days)
Relevance
10/19/2026
First Seen
Valid until: 1/17/2027
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Related Claims
UnverifiedOn the Artificial Analysis benchmark, Qwen 3.8 approaches or even surpasses larger models such as GLM 5.2 Max, Kimi K3, and GPT 5.6.70% similarUnverifiedQwen2.5-7B-Instruct's performance on multiple Chinese benchmark tests is close to or even surpasses that of early 70B-level models.68% similarUnverified3,189 successful rollouts were collected from Qwen3.8-27B for supervised fine-tuning (imitation learning), and performance stagnated at 47.5%, below the results of two rounds of RL training.68% similarUnverifiedThe Qwen2.5-Coder series is produced by Alibaba's Tongyi Lab, and its 32B parameter version surpasses GPT-4o on multiple metrics.68% similarUnverifiedLlama 3.1 405B's score on MMLU is already close to the level of GPT-4o, and Qwen 2.5 72B has surpassed GPT-4 Turbo on certain metrics in math and code generation benchmarks.67% similar
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