Model Comparison
Gemini 1.5 Pro vs Llama 3.2 11B InstructWhich is better in 2026?
Gemini 1.5 Pro significantly outperforms across most benchmarks. Llama 3.2 11B Instruct is 87.5x cheaper per token.
Verdict: Gemini 1.5 Pro vs Llama 3.2 11B Instruct — which is better?
Gemini 1.5 Pro (by Google) and Llama 3.2 11B Instruct (by Meta) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
Gemini 1.5 Pro outperforms in 6 benchmarks (GPQA, MATH, MathVista, MGSM, MMLU, MMMU), while Llama 3.2 11B Instruct is better at 0 benchmarks. Gemini 1.5 Pro significantly outperforms across most benchmarks.
On price, Llama 3.2 11B Instruct is roughly 87.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 1.5 Pro also accepts a larger context window (2,097,152 input tokens), making it the stronger choice for long documents and large codebases.
Choose Gemini 1.5 Pro if…
- you want the strongest raw capability — it leads on 6 of 6 shared benchmarks
- you process long inputs — it offers a 2,097,152 token context window
Choose Llama 3.2 11B Instruct if…
- cost matters — it's about 87.5x cheaper per token
- you want the most recent training data — it shipped Sep 2024
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
Gemini 1.5 Pro outperforms in 6 benchmarks (GPQA, MATH, MathVista, MGSM, MMLU, MMMU), while Llama 3.2 11B Instruct is better at 0 benchmarks.
Gemini 1.5 Pro significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 1.5 Pro ($2.50/1M tokens) is 50.0x more expensive than Llama 3.2 11B Instruct ($0.05/1M tokens).
For output processing, Gemini 1.5 Pro ($10.00/1M tokens) is 200.0x more expensive than Llama 3.2 11B Instruct ($0.05/1M tokens).
In conclusion, Gemini 1.5 Pro is more expensive than Llama 3.2 11B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 1.5 Pro accepts 2,097,152 input tokens compared to Llama 3.2 11B Instruct's 128,000 tokens. Llama 3.2 11B Instruct can generate longer responses up to 128,000 tokens, while Gemini 1.5 Pro is limited to 8,192 tokens.
Input Capabilities
Supported data types and modalities
Both Gemini 1.5 Pro and Llama 3.2 11B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemini 1.5 Pro
Llama 3.2 11B Instruct
License
Usage and distribution terms
Gemini 1.5 Pro is licensed under a proprietary license, while Llama 3.2 11B Instruct uses Llama 3.2 Community License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Llama 3.2 Community License
Open weights
Release Timeline
When each model was launched
Gemini 1.5 Pro was released on 2024-05-01, while Llama 3.2 11B Instruct was released on 2024-09-25.
Llama 3.2 11B Instruct is 5 months newer than Gemini 1.5 Pro.
May 1, 2024
2.1 years ago
Sep 25, 2024
1.7 years ago
4mo newerKnowledge Cutoff
When training data ends
Gemini 1.5 Pro has a knowledge cutoff of 2023-11-01, while Llama 3.2 11B Instruct has a cutoff of 2023-12-31.
Llama 3.2 11B Instruct has more recent training data (up to 2023-12-31), making it potentially better informed about events through that date compared to Gemini 1.5 Pro (2023-11-01).
Nov 2023
Dec 2023
1 mo newerProvider Availability
Gemini 1.5 Pro is available from Google. Llama 3.2 11B Instruct is available from DeepInfra, Sambanova, Bedrock, Groq, Together, Fireworks.
Gemini 1.5 Pro
Llama 3.2 11B Instruct
Outputs Comparison
Key Takeaways
Detailed Comparison
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FAQ
Common questions about Gemini 1.5 Pro vs Llama 3.2 11B Instruct.