Unverified50% confidenceTradeoffExact time
The model scale that local devices can run smoothly is typically between 7 billion and 34 billion parameters, which significantly lags behind top-tier cloud models in capabilities such as complex reasoning and long-context understanding.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
9/1/2026
First Seen
Valid until: 11/30/2026
Sources
Related Entities
Related Claims
Unverified端侧模型推理需为KV缓存、中间激活值和系统开销预留内存,实际可支撑的上下文长度可能远低于云端版本的128K窗口71% similarUnverifiedWhen running local LLMs, VRAM capacity is often more critical than computational speed, as VRAM capacity directly determines which models can be run.69% similarVerifiedRunning local large models with more than 7 billion parameters typically requires a GPU with at least 16GB of VRAM.68% similarVerifiedIn FP16 precision, large models require approximately 2 GB of VRAM per 1 billion parameters.68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/840446API
curl https://kongchang.com/api/v1/knowledge/claims/840446MCP
get_claim(id=840446)