Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Google

Gemini 2.5 Pro Preview 06-05

Google

Gemini 2.5 Pro Preview 06-05 is a multimodal language model developed by Google. It achieves strong performance with an average score of 68.8% across 13 benchmarks. It excels particularly in Global-MMLU-Lite (89.2%), AIME 2025 (88.0%), FACTS Grounding (87.8%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.

Meta

Llama 4 Maverick

Meta

Llama 4 Maverick is a multimodal language model developed by Meta. It achieves strong performance with an average score of 71.8% across 13 benchmarks. It excels particularly in DocVQA (94.4%), MGSM (92.3%), ChartQA (90.0%). The model shows particular specialization in vision tasks with an average performance of 75.8%. With a 2.0M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 7 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Meta's latest advancement in AI technology.

Meta

Llama 4 Maverick

Meta

2025-04-05

Google

Gemini 2.5 Pro Preview 06-05

Google

2025-06-05

2 months newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemini 2.5 Pro Preview 06-05

Input:$1.25
Output:$10.00
Meta

Llama 4 Maverick

$10.48 cheaper
Input:$0.17
Output:$0.60

Performance Metrics

Context window and performance specifications

Google

Gemini 2.5 Pro Preview 06-05

Max Context:1.1M
Meta

Llama 4 Maverick

Larger context
Max Context:2.0M
Parameters:400.0B

Average performance across 3 common benchmarks

Google

Gemini 2.5 Pro Preview 06-05

+16.9%
Average Score:79.1%
Meta

Llama 4 Maverick

Average Score:62.2%

Performance comparison across key benchmark categories

Google

Gemini 2.5 Pro Preview 06-05

vision
+7.0%
82.8%
general
69.8%
code
+7.6%
68.1%
Meta

Llama 4 Maverick

vision
75.8%
general
+1.7%
71.5%
code
60.5%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemini 2.5 Pro Preview 06-05

2025-01-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemini 2.5 Pro Preview 06-05

1 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms
Meta

Llama 4 Maverick

7 providers

Sambanova

Throughput: 638.7 tok/s
Latency: 2.04ms

Together

Throughput: 97.93 tok/s
Latency: 0.2ms

DeepInfra

Throughput: 83.59 tok/s
Latency: 0.38ms

Fireworks

Throughput: 63.03 tok/s
Latency: 0.62ms

Groq

Throughput: 307.3 tok/s
Latency: 0.27ms

Novita

Throughput: 69.42 tok/s
Latency: 0.62ms

Lambda

Throughput: 93.69 tok/s
Latency: 0.65ms
Google

Gemini 2.5 Pro Preview 06-05

+16.9%
Avg Score:79.1%
Providers:1
Meta

Llama 4 Maverick

Avg Score:62.2%
Providers:7