Unverified50% confidenceFactExact time
DeepSeek-Infer uses One-step Scheduling, overlapping scheduling decisions with GPU computation to hide scheduling overhead.
1
Sources
50%
Confidence
Long-term
Relevance
10/23/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedDeep mode spends more reasoning budget to trace the complete flow of data, check concurrent race conditions, and uncover defects under specific input combinations.71% similarUnverifiedDeepSeek-Infer specifically optimizes model execution, sampling, and operators, and takes multi-GPU work partitioning and expert load balancing into account.71% similarUnverifiedDeepInfer lets the CPU schedule the next batch of requests in advance while the GPU is running the current batch, enabled by default; expert replicas are rebalanced every 10,000 steps, the most unevenly loaded GPU differs from the average load by only 9%, and batch invariance is achieved.71% similarUnverifiedDeepSeek minimal mode paired with Max tends to elicit the model's strongest reasoning capabilities, at the cost of longer response latency and higher token consumption.69% similarUnverifiedDeepSeek-V2引入Multi-Head Latent Attention（MLA）机制和DeepSeekMoE架构，其每百万token推理成本约为同期GPT-4级别模型的百分之一69% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1088526API
curl https://kongchang.com/api/v1/knowledge/claims/1088526MCP
get_claim(id=1088526)