Who ranks #1 on the Repoqa leaderboard?
As of August 31, 2026, Phi-3.5-MoE-instruct by Microsoft ranks #1 on Repoqa at 85%. API pricing is $0.07/M input and $0.14/M output.
As of August 31, 2026, Phi-3.5-MoE-instruct is #1 for Repoqa at 85%. Ranked by the Repoqa score 2 models in this index have a published Repoqa score. Repoqa leaderboard: rank models by Repoqa next to live API token prices.
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As of August 31, 2026, Phi-3.5-MoE-instruct by Microsoft is #1 for Repoqa at 85%. Ranked by the Repoqa score This board also tracks Repoqa. Next on the same board: Phi-3.5-mini-instruct. This repoqa leaderboard ranks models by Repoqa. 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 | Repoqa | Input /M | Output /M |
|---|---|---|---|---|
| 1 | Phi-3.5-MoE-instruct | 85% | $0.07 | $0.14 |
| 2 | Phi-3.5-mini-instruct | 77% | $0.10 | $0.10 |
Rank one eval at a time. All LLM benchmarks.
As of August 31, 2026, Phi-3.5-MoE-instruct by Microsoft ranks #1 on Repoqa at 85%. API pricing is $0.07/M input and $0.14/M output.
The current Repoqa ranking as of August 31, 2026 is 1. Phi-3.5-MoE-instruct at 85%; 2. Phi-3.5-mini-instruct at 77%.
Phi-3.5-mini-instruct is the cheapest scored model on this repoqa leaderboard at $0.10/M input and $0.10/M output ($0.20 blended). Phi-3.5-MoE-instruct still leads Repoqa at 85%.
Not automatically. Phi-3.5-MoE-instruct leads Repoqa, but a cheaper scored model can be the better production choice if the quality gap is small. Use the table to weigh Repoqa 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 31, 2026. Treat it as a current index, not a one-off blog post.
Repoqa is a public LLM eval (the Repoqa score). This page ranks models that have published a score, next to live API prices.
This page is the Repoqa leaderboard. Models are sorted by Repoqa, 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 Repoqa score next to live API $/M so you can pick a production SKU, not only a trophy number.