Who ranks #1 on the Infovqa leaderboard?
As of August 20, 2026, Phi-4-multimodal-instruct by Microsoft ranks #1 on Infovqa at 72.7%. API pricing is $0.05/M input and $0.10/M output.
As of August 20, 2026, Phi-4-multimodal-instruct is #1 for Infovqa at 72.7%. Ranked by the Infovqa score 4 models in this index have a published Infovqa score. Infovqa leaderboard: rank models by Infovqa next to live API token prices.
Next step
Auth, billing, and the API layer are already decided. Fork 8 finished AI apps, or have us build the first version with you.
The index
282 models across 33 providers. Search or jump to a lab — every model page stays linked here.







As of August 20, 2026, Phi-4-multimodal-instruct by Microsoft is #1 for Infovqa at 72.7%. Ranked by the Infovqa score This board also tracks Infovqa. Next on the same board: Gemma 3 27B and Gemma 3 12B. This infovqa leaderboard ranks models by Infovqa. 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 | Infovqa | Input /M | Output /M |
|---|---|---|---|---|
| 1 | Phi-4-multimodal-instruct | 72.7% | $0.05 | $0.10 |
| 2 | Gemma 3 27B | 70.6% | $0.10 | $0.20 |
| 3 | Gemma 3 12B | 64.9% | $0.05 | $0.10 |
| 4 | Gemma 3 4B | 50% | $0.02 | $0.04 |
Rank one eval at a time. All LLM benchmarks.
As of August 20, 2026, Phi-4-multimodal-instruct by Microsoft ranks #1 on Infovqa at 72.7%. API pricing is $0.05/M input and $0.10/M output.
The current Infovqa ranking as of August 20, 2026 is 1. Phi-4-multimodal-instruct at 72.7%; 2. Gemma 3 27B at 70.6%; 3. Gemma 3 12B at 64.9%.
Gemma 3 4B is the cheapest scored model on this infovqa leaderboard at $0.02/M input and $0.04/M output ($0.06 blended). Phi-4-multimodal-instruct still leads Infovqa at 72.7%.
Not automatically. Phi-4-multimodal-instruct leads Infovqa, but a cheaper scored model can be the better production choice if the quality gap is small. Use the table to weigh Infovqa 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.
Infovqa is a public LLM eval (the Infovqa score). This page ranks models that have published a score, next to live API prices.
This page is the Infovqa leaderboard. Models are sorted by Infovqa, 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 Infovqa score next to live API $/M so you can pick a production SKU, not only a trophy number.