LLMs1 min read
We ran 904 DeepSWE rollouts on DeepSeek V4 Pro 0813 and GPT-5.6 Sol. Sol leads pass@1 by 10 points at 35x the cost; Pro wins pass@4, and a Pro-first cascade hits 83.0%.
By OpenSmartRoute editorial · attributed excerpt
From Together AI blog
We ran 904 DeepSWE rollouts on DeepSeek V4 Pro 0813 and GPT-5.6 Sol. Sol leads pass@1 by 10 points at 35x the cost; Pro wins pass@4, and a Pro-first cascade hits 83.0%.
Read the original at Together AI blog: https://www.together.ai/blog/deepseek-v4-pro-0813-vs-gpt-5-6-sol-on-deepswe-cost-coding-and-routing
Source: https://www.together.ai/blog/deepseek-v4-pro-0813-vs-gpt-5-6-sol-on-deepswe-cost-coding-and-routing
Keep reading
LLMs1 min read
arXiv:2609.13389v1 Announce Type: new Abstract: Mapping textual specifications into formal representations is essential for ensuring the correctness of protocol designs and implementations. LLM-generated mappings, used for networking sec...
LLMs1 min read
arXiv:2609.13709v1 Announce Type: new Abstract: Human corrections identify editable spans, but the examples receiving corrections may come from a selective feedback channel. We analyze this interaction at a fixed model checkpoint by deco...
https://www.together.ai/blog/deepseek-v4-pro-0813-vs-gpt-5-6-sol-on-deepswe-cost-coding-and-routing
LLMs1 min read
arXiv:2609.13445v1 Announce Type: new Abstract: Speech-to-speech LLMs like Moshi, and its derivative PersonaPlex, can listen and speak concurrently through full-duplex generation. However, they can begin speaking inappropriately during p...
