Meta: Llama 3.1 70B Instruct Rank
Llama 3.1 70B Instruct has an overall score of 54 out of 100, tied for rank 250 of 291. The published scores are price 73, context 44, parameters 46, 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 250 of 291
Component scores
| Score | Result | Published value | Source |
|---|---|---|---|
| Freshness | 51 | AI Knowledge Cutoff | |
| Recency | — | — | AI Release Date |
| Context | 44 | 131K tokens, output 16.4K | AI Context Window |
| Parameters | 46 | 70B total | AI Parameter Count |
| Price | 73 | $0.4 / 1M blended, $0.4 / 1M input, $0.4 / 1M output | AI Token Price |
249 listed models have a higher overall score. Among Meta models, it ranks 5 of 8.
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases. It has demonstrated strong...
Higher overall scores
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Frequently asked questions
What is the Llama 3.1 70B Instruct rank?
Llama 3.1 70B Instruct has an overall score of 54 out of 100, tied for rank 250 of 291. The published scores are price 73, context 44, parameters 46, and freshness 51. The overall score is their average. recency is not published and is left out of the average.
Where does Llama 3.1 70B Instruct rank?
Llama 3.1 70B Instruct is tied for rank 250 of 291. 249 listed models have a higher overall score. Among Meta models, it ranks 5 of 8.
What scores make up Llama 3.1 70B Instruct?
Llama 3.1 70B Instruct scores price 73 (AI Token Price), context 44 (AI Context Window), parameters 46 (AI Parameter Count), and freshness 51 (AI Knowledge Cutoff). The overall score of 54 is the average of those 4.