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The LLM benchmark aggregator.
Phi 3.5 MoE Instruct
Microsoft
Strongest in Secure code (#49 of 274), weakest in Fairness (#188 of 299). Above par in 5 of 6 scopes. Among the models it meets almost everywhere, it finishes behind Claude Sonnet 5 and Grok 4.7 and ahead of Qwen3.5 122B A10B and GPT-6 Luna.
§ 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.
Safety53.6−7.9#82/3361/3
Secure code62.1−4.4#49/2741/1
Toxicity avoidance56.6−2.4#59/2721/1
Jailbreak resistance55.5−9.4#111/2721/1
Harm refusal52.7−8.9#115/2991/2
Fairness45.4−24.6#188/2991/2
§ 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 Phi 3.5 MoE 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 8.1%Enkrypt · Harmful content risk 23.9%Enkrypt · CBRN risk 12.7%Enkrypt · Toxicity risk 1.7%Enkrypt · Bias risk 85%Enkrypt · Insecure code risk 8.9%
Badge
[](https://publicai.io/model-index/m/phi-3-5-moe-instruct)