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The LLM benchmark aggregator.
Qwen2.5 14B Instruct
Alibaba · 14B
Strongest in Toxicity avoidance (#90 of 266), weakest in Fairness (#210 of 290). Above par in 4 of 6 scopes. Among the models it meets almost everywhere, it finishes behind Claude Sonnet 5 and Claude 3.5 Sonnet and ahead of Granite 3.2 2B Instruct and Sarvam 30B.
§ 1 · Profile
What it is good at
Bars run from 50 — the average of the models each source lists — so right of the line is above par. The middle column is the gap to whoever leads that scope.
Safety51.3−10.1#147/3271/3
Toxicity avoidance55.6−3.4#90/2661/1
Jailbreak resistance56−9#100/2661/1
Harm refusal52.1−9.4#121/2901/2
Secure code49.5−16.7#157/2681/1
Fairness44−26#210/2901/2
§ 2 · Head to head
What it beats, and what beats it
The same models turn up scope after scope. Counted once: where both were placed, who finished higher. Bars run right for Qwen2.5 14B Instruct, left for the other.
§ 3 · Sources
Where the numbers come from
1 publication, 6 figures. Every one links to the page it was read from.
Enkrypt · Jailbreak risk 7.8%Enkrypt · Harmful content risk 30.6%Enkrypt · CBRN risk 10.8%Enkrypt · Toxicity risk 2.3%Enkrypt · Bias risk 87.1%Enkrypt · Insecure code risk 34.2%
Badge
[](https://publicai.io/model-index/m/qwen2-5-14b-instruct)