Unverified50% confidenceSolutionExact time
Keeping stable models such as DeepSeek as a fallback in critical workflows and quickly switching when GLM frequently interrupts is a mitigation approach.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
8/17/2026
First Seen
Valid until: 11/15/2026
Sources
Ollama Cloud GLM在OpenCode中频繁中断的原因与解决方案
Related Claims
VerifiedDeepSeek addresses the expert collapse problem by introducing auxiliary loss functions to force balanced load distribution across experts65% similarUnverifiedGLM 5.2 relies on extremely long chains of thought, with token output that even exceeds that of DeepSeek version 2.6.64% similarUnverifiedThe gap between domestic models (Zhipu GLM, DeepSeek, etc.) and foreign models has narrowed significantly, and they are capable of handling everyday programming assistance tasks.64% similarVerifiedDeepSeek-V3 uses dynamic bias terms rather than additional loss functions to achieve load balancing, avoiding the negative impact of auxiliary losses on model quality.63% similarUnverifiedModels such as DeepSeek-R1 are viewed by some researchers as achieving a "dimensional breakthrough" through algorithmic innovation under compute-constrained conditions, approaching the international frontier in parameter efficiency and reasoning capability.63% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/759884API
curl https://kongchang.com/api/v1/knowledge/claims/759884MCP
get_claim(id=759884)