Gemini 2.5 Pro
1M token context window accommodates extensive retrieved document sets without chunking. Multimodal RAG processes up to 3,000 images, 60 minutes of video, and 8.4 hours of audio alongside text. If you want to compare the best LLMs for your data, try Agentset.
Model Information
- Provider
- License
- Proprietary
- Input Price per 1M
- $1.25
- Output Price per 1M
- $10.00
- Context Window
- 1049K
- Release Date
- 2025-06-17
- Model Name
- gemini-2.5-pro
- Total Evaluations
- 1350
Performance Record
LLMs Are Just One Piece of RAG
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Performance Overview
ELO ratings by dataset
Gemini 2.5 Pro's ELO performance varies across different benchmark datasets, showing its strengths in specific domains.
Gemini 2.5 Pro - ELO by Dataset
Detailed Metrics
Dataset breakdown
Performance metrics across different benchmark datasets, including accuracy and latency percentiles.
PG
Quality Metrics
- Correctness
- 5.00
- Faithfulness
- 5.00
- Grounding
- 5.00
- Relevance
- 5.00
- Completeness
- 5.00
- Overall
- 5.00
Latency Distribution
- Mean
- 17834ms
- Min
- 11067ms
- Max
- 49308ms
MSMARCO
Quality Metrics
- Correctness
- 4.90
- Faithfulness
- 4.93
- Grounding
- 4.93
- Relevance
- 5.00
- Completeness
- 4.90
- Overall
- 4.93
Latency Distribution
- Mean
- 12449ms
- Min
- 7629ms
- Max
- 23066ms
SciFact
Quality Metrics
- Correctness
- 4.70
- Faithfulness
- 4.80
- Grounding
- 4.80
- Relevance
- 4.70
- Completeness
- 4.50
- Overall
- 4.70
Latency Distribution
- Mean
- 15314ms
- Min
- 8817ms
- Max
- 35365ms
Build RAG in Minutes, Not Months
Agentset gives you a complete RAG API with top-ranked LLMs and smart retrieval built in. Upload your data, call the API, and get grounded answers from day one.
import { Agentset } from "agentset";
const agentset = new Agentset();
const ns = agentset.namespace("ns_1234");
const results = await ns.search(
"What is multi-head attention?"
);
for (const result of results) {
console.log(result.text);
}Compare Models
See how it stacks up
Compare Gemini 2.5 Pro with other top llms to understand the differences in performance, accuracy, and latency.