Model Comparison

Gemini 1.0 Pro vs Llama 3.2 11B Instruct

Llama 3.2 11B Instruct significantly outperforms across most benchmarks. Llama 3.2 11B Instruct is 15.0x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

Gemini 1.0 Pro outperforms in 0 benchmarks, while Llama 3.2 11B Instruct is better at 5 benchmarks (GPQA, MATH, MathVista, MMLU, MMMU).

Llama 3.2 11B Instruct significantly outperforms across most benchmarks.

Sun Mar 29 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Llama 3.2 11B Instruct costs less

For input processing, Gemini 1.0 Pro ($0.50/1M tokens) is 10.0x more expensive than Llama 3.2 11B Instruct ($0.05/1M tokens).

For output processing, Gemini 1.0 Pro ($1.50/1M tokens) is 30.0x more expensive than Llama 3.2 11B Instruct ($0.05/1M tokens).

In conclusion, Gemini 1.0 Pro is more expensive than Llama 3.2 11B Instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sun Mar 29 2026 • llm-stats.com
Google
Gemini 1.0 Pro
Input tokens$0.50
Output tokens$1.50
Best providerGoogle
Meta
Llama 3.2 11B Instruct
Input tokens$0.05
Output tokens$0.05
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Llama 3.2 11B Instruct accepts 128,000 input tokens compared to Gemini 1.0 Pro's 32,760 tokens. Llama 3.2 11B Instruct can generate longer responses up to 128,000 tokens, while Gemini 1.0 Pro is limited to 8,192 tokens.

Google
Gemini 1.0 Pro
Input32,760 tokens
Output8,192 tokens
Meta
Llama 3.2 11B Instruct
Input128,000 tokens
Output128,000 tokens
Sun Mar 29 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Llama 3.2 11B Instruct supports multimodal inputs, whereas Gemini 1.0 Pro does not.

Llama 3.2 11B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 1.0 Pro

Text
Images
Audio
Video

Llama 3.2 11B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 1.0 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.

Gemini 1.0 Pro

Proprietary

Closed source

Llama 3.2 11B Instruct

Llama 3.2 Community License

Open weights

Release Timeline

When each model was launched

Gemini 1.0 Pro was released on 2024-02-15, while Llama 3.2 11B Instruct was released on 2024-09-25.

Llama 3.2 11B Instruct is 7 months newer than Gemini 1.0 Pro.

Gemini 1.0 Pro

Feb 15, 2024

2.1 years ago

Llama 3.2 11B Instruct

Sep 25, 2024

1.5 years ago

7mo newer

Knowledge Cutoff

When training data ends

Gemini 1.0 Pro has a knowledge cutoff of 2024-02-01, while Llama 3.2 11B Instruct has a cutoff of 2023-12-31.

Gemini 1.0 Pro has more recent training data (up to 2024-02-01), making it potentially better informed about events through that date compared to Llama 3.2 11B Instruct (2023-12-31).

Gemini 1.0 Pro

Feb 2024

2 mo newer
Llama 3.2 11B Instruct

Dec 2023

Provider Availability

Gemini 1.0 Pro is available from Google. Llama 3.2 11B Instruct is available from DeepInfra, Sambanova, Bedrock, Groq, Together, Fireworks.

Gemini 1.0 Pro

google logo
Google
Input Price:Input: $0.50/1MOutput Price:Output: $1.50/1M

Llama 3.2 11B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.05/1MOutput Price:Output: $0.05/1M
sambanova logo
Sambanova
Input Price:Input: $0.15/1MOutput Price:Output: $0.30/1M
bedrock logo
AWS Bedrock
Input Price:Input: $0.16/1MOutput Price:Output: $0.16/1M
groq logo
Groq
Input Price:Input: $0.18/1MOutput Price:Output: $0.18/1M
together logo
Together
Input Price:Input: $0.18/1MOutput Price:Output: $0.18/1M
fireworks logo
Fireworks
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Google
Meta
Larger context window (128,000 tokens)
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens
Has open weights
Higher GPQA score (32.8% vs 27.9%)
Higher MATH score (51.9% vs 32.6%)
Higher MathVista score (51.5% vs 46.6%)
Higher MMLU score (73.0% vs 71.8%)
Higher MMMU score (50.7% vs 47.9%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 1.0 Pro
Meta
Llama 3.2 11B Instruct

FAQ

Common questions about Gemini 1.0 Pro vs Llama 3.2 11B Instruct

Llama 3.2 11B Instruct significantly outperforms across most benchmarks. Gemini 1.0 Pro is made by Google and Llama 3.2 11B Instruct is made by Meta. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Gemini 1.0 Pro scores BIG-Bench: 75.0%, MMLU: 71.8%, WMT23: 71.7%, EgoSchema: 55.7%, MMMU: 47.9%. Llama 3.2 11B Instruct scores AI2D: 91.1%, DocVQA: 88.4%, ChartQA: 83.4%, VQAv2 (test): 75.2%, MMLU: 73.0%.
Llama 3.2 11B Instruct is 10.0x cheaper for input tokens. Gemini 1.0 Pro costs $0.50/M input and $1.50/M output via google. Llama 3.2 11B Instruct costs $0.05/M input and $0.05/M output via deepinfra.
Gemini 1.0 Pro supports 33K tokens and Llama 3.2 11B Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (33K vs 128K), input pricing ($0.50 vs $0.05/M), multimodal support (no vs yes), licensing (Proprietary vs Llama 3.2 Community License). See the full comparison above for benchmark-by-benchmark results.
Gemini 1.0 Pro is developed by Google and Llama 3.2 11B Instruct is developed by Meta.