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The LLM benchmark aggregator.
SmolLM2 360M Instruct
Hugging Face
Strongest in Fairness (#47 of 290, on 1 of its 2 boards), weakest in Safety (#306 of 327). Above par in 1 of 6 scopes. Among the models it meets almost everywhere, it finishes behind Claude Sonnet 5 and Claude 3.5 Sonnet and ahead of RakutenAI 7B Instruct and Grok 3.
§ 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.
Safety42.3−19.1#306/3271/3
Fairness57.3−12.7#47/2901/2
Jailbreak resistance41.8−23.2#207/2661/1
Harm refusal44.6−16.9#246/2901/2
Toxicity avoidance32.1−26.9#247/2661/1
Secure code26.1−40.1#253/2681/1
§ 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 SmolLM2 360M 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 19.7%Enkrypt · Harmful content risk 66.7%Enkrypt · CBRN risk 11.5%Enkrypt · Toxicity risk 18.5%Enkrypt · Bias risk 66.4%Enkrypt · Insecure code risk 82.2%
Badge
[](https://publicai.io/model-index/m/smollm2-360m-instruct)