Model profile
Llama 3.2 1B Instruct
Evidence summary
Llama 3.2 1B Instruct has an estimated overall rank of #253; its 90% source-sensitivity interval is #191–#266. Its behavior-only rank is #244; company governance moves the combined estimate to #253. Published evidence spans 7 evals and 6 of 7 behavior components. Its strongest relative result is Enkrypt AI Safety Leaderboard (toxicity_attack_non_success_rate, #53 of 258); its weakest is Enkrypt AI Safety Leaderboard (bias_attack_non_success_rate, #250 of 260).
Compare this model
Only models sharing at least one published sub-eval are listed.
Official and reference links
- Artificial Analysis ↗llama-3-2-instruct-1b
- Hugging Face ↗meta-llama/Llama-3.2-1B-Instruct
- NVIDIA ↗qc69jvmznzxy/llama-3.2-1b-instruct
- OpenRouter ↗meta-llama/llama-3.2-1b-instruct
- Official model page ↗Exact model document · Reviewed official Hugging Face owner · official repository
- Release source ↗direct research preview identity date
Published eval results
Rank is within that sub-eval. Black marks the observed result; the grey dot marks the value implied by the global rank. Values stay on each source’s native scale.
| Eval / sub-eval | Rank | Value | Distribution | Better | Source |
|---|---|---|---|---|---|
| AA-Omnisciencehallucination_rate | #275 / 311 | 0.9155 | ↓ lower | Source ↗official | |
| BlueBench AttaQ-100attaq_harmlessness_reward_pct | #14 / 18 | 83 | ↑ higher | Source ↗official | |
| Cisco AI Defense Rolling Single-Turn Leaderboardsingle_turn_attack_success_rate | #38 / 105 | 21.39 | ↓ lower | Source ↗official | |
| Enkrypt AI Safety Leaderboardbias_attack_non_success_rate | #250 / 260 | 4.13 | ↑ higher | Source ↗official | |
| Enkrypt AI Safety Leaderboardcbrn_attack_non_success_rate | #131 / 260 | 88.33 | ↑ higher | Source ↗official | |
| Enkrypt AI Safety Leaderboardharmful_attack_non_success_rate | #54 / 260 | 91.11 | ↑ higher | Source ↗official | |
| Enkrypt AI Safety Leaderboardtoxicity_attack_non_success_rate | #53 / 258 | 98.82 | ↑ higher | Source ↗official | |
| Large-scale Moral Machine experiment on LLMshuman_choice_distance | #25 / 39 | 1.182 | ↓ lower | Source ↗official | |
| Open LLM Safety Indexjailbreakbench_safety_rate | #14 / 21 | 0.2667 | ↑ higher | Source ↗official | |
| Open LLM Safety Indexstrongreject_safety_rate | #14 / 21 | 0.1333 | ↑ higher | Source ↗official | |
| PandaBench JBB direct-request panelsafety_rate | #14 / 46 | 0.99 | ↑ higher | Source ↗official |
Values evaluations
Descriptive values and political-framing results are separate from safety/ethics ranks. Each strip shows the evaluation’s observed model range; its endpoint labels state what lower and higher values mean.