Model Comparison
Gemini 3.1 Pro vs Llama 3.2 90B InstructWhich is better in 2026?
Gemini 3.1 Pro significantly outperforms across most benchmarks. Llama 3.2 90B Instruct is 15.5x cheaper per token.
Verdict: Gemini 3.1 Pro vs Llama 3.2 90B Instruct — which is better?
Gemini 3.1 Pro (by Google) and Llama 3.2 90B 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 3.1 Pro outperforms in 2 benchmarks (GPQA, MMMU-Pro), while Llama 3.2 90B Instruct is better at 0 benchmarks. Gemini 3.1 Pro significantly outperforms across most benchmarks.
On price, Llama 3.2 90B Instruct is roughly 15.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 3.1 Pro also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose Gemini 3.1 Pro if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Feb 2026
Choose Llama 3.2 90B Instruct if…
- cost matters — it's about 15.5x cheaper per token
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
Gemini 3.1 Pro outperforms in 2 benchmarks (GPQA, MMMU-Pro), while Llama 3.2 90B Instruct is better at 0 benchmarks.
Gemini 3.1 Pro significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 3.1 Pro ($2.50/1M tokens) is 7.1x more expensive than Llama 3.2 90B Instruct ($0.35/1M tokens).
For output processing, Gemini 3.1 Pro ($15.00/1M tokens) is 37.5x more expensive than Llama 3.2 90B Instruct ($0.40/1M tokens).
In conclusion, Gemini 3.1 Pro is more expensive than Llama 3.2 90B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 3.1 Pro accepts 1,048,576 input tokens compared to Llama 3.2 90B Instruct's 128,000 tokens. Llama 3.2 90B Instruct can generate longer responses up to 128,000 tokens, while Gemini 3.1 Pro is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Both Gemini 3.1 Pro and Llama 3.2 90B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemini 3.1 Pro
Llama 3.2 90B Instruct
License
Usage and distribution terms
Gemini 3.1 Pro is licensed under a proprietary license, while Llama 3.2 90B Instruct uses Llama 3.2.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Llama 3.2
Open weights
Release Timeline
When each model was launched
Gemini 3.1 Pro was released on 2026-02-19, while Llama 3.2 90B Instruct was released on 2024-09-25.
Gemini 3.1 Pro is 17 months newer than Llama 3.2 90B Instruct.
Feb 19, 2026
3 months ago
1.4yr newerSep 25, 2024
1.7 years ago
Knowledge Cutoff
When training data ends
Gemini 3.1 Pro has a documented knowledge cutoff of 2025-01-31, while Llama 3.2 90B Instruct's cutoff date is not specified.
We can confirm Gemini 3.1 Pro's training data extends to 2025-01-31, but cannot make a direct comparison without Llama 3.2 90B Instruct's cutoff date.
Jan 2025
—
Provider Availability
Gemini 3.1 Pro is available from Google. Llama 3.2 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic.
Gemini 3.1 Pro
Llama 3.2 90B Instruct
Outputs Comparison
Key Takeaways
Detailed Comparison
| Feature | | |
|---|
FAQ
Common questions about Gemini 3.1 Pro vs Llama 3.2 90B Instruct.