Who ranks #1 on the Qasper leaderboard?
As of August 20, 2026, Phi-3.5-mini-instruct by Microsoft ranks #1 on Qasper at 41.9%. API pricing is $0.10/M input and $0.10/M output.
As of August 20, 2026, Phi-3.5-mini-instruct is #1 for Qasper at 41.9%. Ranked by the Qasper score 1 models in this index have a published Qasper score. Qasper leaderboard: rank models by Qasper next to live API token prices.
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As of August 20, 2026, Phi-3.5-mini-instruct by Microsoft is #1 for Qasper at 41.9%. Ranked by the Qasper score This board also tracks Qasper. This qasper leaderboard ranks models by Qasper. Scores come from public evals. Prices are the live API rates in the table above.
Sources: OpenAI API pricing (https://developers.openai.com/api/docs/pricing); Anthropic Claude API pricing (https://platform.claude.com/docs/en/about-claude/pricing); Gemini API pricing (https://ai.google.dev/gemini-api/docs/pricing)
| Rank | Model | Qasper | Input /M | Output /M |
|---|---|---|---|---|
| 1 | Phi-3.5-mini-instruct | 41.9% | $0.10 | $0.10 |
Rank one eval at a time. All LLM benchmarks.
As of August 20, 2026, Phi-3.5-mini-instruct by Microsoft ranks #1 on Qasper at 41.9%. API pricing is $0.10/M input and $0.10/M output.
Phi-3.5-mini-instruct currently leads Qasper and is also the cheapest scored model on this page, at $0.10/M input and $0.10/M output ($0.20 blended).
Not automatically. Phi-3.5-mini-instruct leads Qasper, but a cheaper scored model can be the better production choice if the quality gap is small. Use the table to weigh Qasper against input/output price, context window, and related evals.
Scores and API prices on this page are refreshed from published evals and provider rates. The snapshot is labeled August 20, 2026. Treat it as a current index, not a one-off blog post.
Qasper is a public LLM eval (the Qasper score). This page ranks models that have published a score, next to live API prices.
This page is the Qasper leaderboard. Models are sorted by Qasper, with input and output token prices on the same row so you can weigh score against cost. Official boards often omit price; that comparison is the point of this index.
Official eval pages own the methodology. This page keeps the published Qasper score next to live API $/M so you can pick a production SKU, not only a trophy number.