Who ranks #1 on the Omnibench leaderboard?
As of August 30, 2026, Qwen2.5-Omni-7B by Qwen ranks #1 on Omnibench at 56.1%. API pricing is $0.10/M input and $0.40/M output.
As of August 30, 2026, Qwen2.5-Omni-7B is #1 for Omnibench at 56.1%. Ranked by the Omnibench score 1 models in this index have a published Omnibench score. Omnibench leaderboard: rank models by Omnibench next to live API token prices.
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As of August 30, 2026, Qwen2.5-Omni-7B by Qwen is #1 for Omnibench at 56.1%. Ranked by the Omnibench score This board also tracks Omnibench. This omnibench leaderboard ranks models by Omnibench. 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 | Omnibench | Input /M | Output /M |
|---|---|---|---|---|
| 1 | Qwen2.5-Omni-7B | 56.1% | $0.10 | $0.40 |
Rank one eval at a time. All LLM benchmarks.
As of August 30, 2026, Qwen2.5-Omni-7B by Qwen ranks #1 on Omnibench at 56.1%. API pricing is $0.10/M input and $0.40/M output.
Qwen2.5-Omni-7B currently leads Omnibench and is also the cheapest scored model on this page, at $0.10/M input and $0.40/M output ($0.50 blended).
Not automatically. Qwen2.5-Omni-7B leads Omnibench, but a cheaper scored model can be the better production choice if the quality gap is small. Use the table to weigh Omnibench 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 30, 2026. Treat it as a current index, not a one-off blog post.
Omnibench is a public LLM eval (the Omnibench score). This page ranks models that have published a score, next to live API prices.
This page is the Omnibench leaderboard. Models are sorted by Omnibench, 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 Omnibench score next to live API $/M so you can pick a production SKU, not only a trophy number.