Who ranks #1 on the Labbench2 leaderboard?
As of August 20, 2026, Gemini 3.7 Flash by Google ranks #1 on Labbench2 at 82.1%. API pricing is $0.75/M input and $3.75/M output.
As of August 20, 2026, Gemini 3.7 Flash is #1 for Labbench2 at 82.1%. Ranked by the Labbench2 score 1 models in this index have a published Labbench2 score. Labbench2 leaderboard: rank models by Labbench2 next to live API token prices.
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As of August 20, 2026, Gemini 3.7 Flash by Google is #1 for Labbench2 at 82.1%. Ranked by the Labbench2 score This board also tracks Labbench2. This labbench2 leaderboard ranks models by Labbench2. 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 | Labbench2 | Input /M | Output /M |
|---|---|---|---|---|
| 1 | Gemini 3.7 Flash | 82.1% | $0.75 | $3.75 |
Rank one eval at a time. All LLM benchmarks.
As of August 20, 2026, Gemini 3.7 Flash by Google ranks #1 on Labbench2 at 82.1%. API pricing is $0.75/M input and $3.75/M output.
Gemini 3.7 Flash currently leads Labbench2 and is also the cheapest scored model on this page, at $0.75/M input and $3.75/M output ($4.50 blended).
Not automatically. Gemini 3.7 Flash leads Labbench2, but a cheaper scored model can be the better production choice if the quality gap is small. Use the table to weigh Labbench2 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.
Labbench2 is a public LLM eval (the Labbench2 score). This page ranks models that have published a score, next to live API prices.
This page is the Labbench2 leaderboard. Models are sorted by Labbench2, 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 Labbench2 score next to live API $/M so you can pick a production SKU, not only a trophy number.