Qwen: Qwen2.5 7B Instruct Rank
Qwen2.5 7B Instruct has an overall score of 49 out of 100, tied for rank 272 of 291. The published scores are price 88, context 27, parameters 21, and freshness 60. 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 272 of 291
Component scores
| Score | Result | Published value | Source |
|---|---|---|---|
| Freshness | 60 | AI Knowledge Cutoff | |
| Recency | — | — | AI Release Date |
| Context | 27 | 32.8K tokens, output 29.5K | AI Context Window |
| Parameters | 21 | 7B total | AI Parameter Count |
| Price | 88 | $0.125 / 1M blended, $0.1 / 1M input, $0.2 / 1M output | AI Token Price |
271 listed models have a higher overall score. Among Qwen models, it ranks 37 of 38.
Qwen2.5 7B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and...
Higher overall scores
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Frequently asked questions
What is the Qwen2.5 7B Instruct rank?
Qwen2.5 7B Instruct has an overall score of 49 out of 100, tied for rank 272 of 291. The published scores are price 88, context 27, parameters 21, and freshness 60. The overall score is their average. recency is not published and is left out of the average.
Where does Qwen2.5 7B Instruct rank?
Qwen2.5 7B Instruct is tied for rank 272 of 291. 271 listed models have a higher overall score. Among Qwen models, it ranks 37 of 38.
What scores make up Qwen2.5 7B Instruct?
Qwen2.5 7B Instruct scores price 88 (AI Token Price), context 27 (AI Context Window), parameters 21 (AI Parameter Count), and freshness 60 (AI Knowledge Cutoff). The overall score of 49 is the average of those 4.