DeepSeek new model/V4/GLM-5.1/MiniMax M2.7/TCO: open MoE #1 SWE/Huawei/US adoption
Key Questions
What is DeepSeek V4 and how does it relate to Huawei Ascend?
DeepSeek V4-Pro and Flash models run on Huawei Ascend chips and deliver a 75% price reduction. This supports broader domestic chip adoption and shifts total cost of ownership for AI workloads.
Which model leads in SWE-Pro benchmarks according to the highlight?
GLM-5.1 ranks first on SWE-Pro via OrcaRouter. It outperforms other open models in software engineering tasks.
What are the key features of Qwen3.7-Max?
Qwen3.7-Max supports 35 hours of autonomous operation and over 1,000 tool calls. It ranks 13th globally and beats several Western models in independent tests.
How does MiniMax M2.7 differ from other models mentioned?
MiniMax M2.7 is described as self-evolving. This capability sets it apart in ongoing model improvement without external intervention.
What impact do domestic chips have on TCO?
The shift to domestic chips such as Huawei Ascend is changing total cost of ownership calculations. It enables lower inference costs for Chinese AI deployments.
Which open MoE model leads in SWE benchmarks?
DeepSeek's open MoE model currently holds the top SWE position. It benefits from cost reductions and hardware optimizations on Ascend.
Is Qwen3.7-Max available for US adoption?
The highlight notes growing interest in Chinese models including Qwen3.7-Max outside China. Performance and cost advantages drive potential US evaluation.
What autonomy duration does Qwen3.7-Max demonstrate?
Alibaba reports Qwen3.7-Max completed a 35-hour autonomous code optimization run for its own custom chip. This showcases long-horizon agent capabilities.
DeepSeek V4-Pro/Flash on Huawei Ascend; 75% price cut. GLM-5.1 #1 SWE-Pro on OrcaRouter; MiniMax M2.7 self-evolving; Qwen3.7-Max (35hr autonomy/1000+ tools) ranks 13th, beats Claude/GPT in tests. Domestic chips shift TCO.