Meta: Llama 3.2 1B Instruct Rank
Llama 3.2 1B Instruct has an overall score of 45 out of 100, tied for rank 282 of 291. The published scores are price 95, context 34, parameters 0, and freshness 51. The overall score is their average. recency is not published and is left out of the average.
Data sourced from OpenRouter API and manual data collection | Last updated: Nov 3, 2026, 8:01 AM UTC
Component scores are ranked in
tied for rank 282 of 291
Component scores
| Score | Result | Published value | Source |
|---|---|---|---|
| Freshness | 51 | AI Knowledge Cutoff | |
| Recency | — | — | AI Release Date |
| Context | 34 | 60K tokens, output 54K | AI Context Window |
| Parameters | 0 | 1B total | AI Parameter Count |
| Price | 95 | $0.0705 / 1M blended, $0.027 / 1M input, $0.201 / 1M output | AI Token Price |
281 listed models have a higher overall score. Among Meta models, it ranks 8 of 8.
Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate...
Higher overall scores
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Frequently asked questions
What is the Llama 3.2 1B Instruct rank?
Llama 3.2 1B Instruct has an overall score of 45 out of 100, tied for rank 282 of 291. The published scores are price 95, context 34, parameters 0, and freshness 51. The overall score is their average. recency is not published and is left out of the average.
Where does Llama 3.2 1B Instruct rank?
Llama 3.2 1B Instruct is tied for rank 282 of 291. 281 listed models have a higher overall score. Among Meta models, it ranks 8 of 8.
What scores make up Llama 3.2 1B Instruct?
Llama 3.2 1B Instruct scores price 95 (AI Token Price), context 34 (AI Context Window), parameters 0 (AI Parameter Count), and freshness 51 (AI Knowledge Cutoff). The overall score of 45 is the average of those 4.