对比

对比本地 AI 硬件，获取感知工作负载的分析结果。

硬件 A

硬件 B工作负载Operating mode

Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.

Operating mode: Balanced. Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.

RTX 4090 24GB 胜出 for coding in balanced mode

基于顶级推荐中的模型适配度、速度和质量综合评判。

SQwen 3.5 9B

llama.cppq4-k-mRuns well

9.8 GB / 12.0 GB

72.0 tok/s32K ctx

ACodeGeeX 4 9B

llama.cppq4-k-mRuns well

8.2 GB / 12.0 GB

75.3 tok/s116K ctx

AGemma 4 E4B

llama.cppq4-k-mRuns well

8.3 GB / 12.0 GB

63.1 tok/s63K ctx

胜出

SCodestral 2 25.08

llama.cppq4-k-mRuns well

19.2 GB / 24.0 GB

42.0 tok/s48K ctx

SQwen 3.6 27B

llama.cppq4-k-mTight fit

20.7 GB / 24.0 GB

31.7 tok/s69K ctx

SDevstral Small 2 24B Instruct

llama.cppq4-k-mTight fit

20.4 GB / 24.0 GB

40.0 tok/s40K ctx

快速对比