+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
Gemini 2.5 Pro vs Llama 3.2 90B Instruct
Comprehensive side-by-side LLM comparison
Gemini 2.5 Pro leads with 6.9% higher average benchmark score. Gemini 2.5 Pro offers 858.1K more tokens in context window than Llama 3.2 90B Instruct. Llama 3.2 90B Instruct is $10.50 cheaper per million tokens. Llama 3.2 90B Instruct is available on 5 providers. Overall, Gemini 2.5 Pro is the stronger choice for coding tasks.
+
+
+
+
Gemini 2.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 69.6% across 16 benchmarks. It excels particularly in MRCR (93.0%), AIME 2024 (92.0%), Global-MMLU-Lite (88.6%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 2 API providers. 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 3.2 90B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 71.3% across 13 benchmarks. It excels particularly in AI2D (92.3%), DocVQA (90.1%), MGSM (86.9%). It supports a 256K token context window for handling large documents. The model is available through 5 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Meta's latest advancement in AI technology.
7 months newer
Llama 3.2 90B Instruct
Meta
2024-09-25
Gemini 2.5 Pro
2025-05-20
Pricing Comparison
Cost per million tokens (USD)
+
+
+
+
Gemini 2.5 Pro
Input:$1.25
Output:$10.00
+
+
+
+
Llama 3.2 90B Instruct
Input:$0.35
Output:$0.40($10.50 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 27 common benchmarks
+
+
+
+
Gemini 2.5 Pro
Average Score:41.3%(+6.9%)
+
+
+
+
Llama 3.2 90B Instruct
Average Score:34.3%
+
+
+
+
Knowledge Cutoff
Training data recency comparison
Gemini 2.5 Pro
2025-01-31
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
+
+
+
+
Gemini 2.5 Pro
2 providers
Throughput: 85 tok/s
Latency: 0.7ms
ZeroEval
Throughput: 85 tok/s
Latency: 0.7ms
+
+
+
+
+
+
+
+
Gemini 2.5 Pro
Avg Score:41.3%(+6.9%)
Providers:2
+
+
+
+
Llama 3.2 90B Instruct
Avg Score:34.3%
Providers:5