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Gemini 1.5 Pro vs Llama 3.2 3B Instruct

Gemini 1.5 Pro leads the LLM Stats Score 12.5 to -5.5. Llama 3.2 3B Instruct is 350.0x cheaper per token.

Google · Meta · Updated for 2026

Which is better?

Gemini 1.5 Pro leads the overall LLM Stats Score 12.5 to -5.5, ranking #232 overall.

In the 6 individual benchmarks reported for both models, Gemini 1.5 Pro wins 6; this is a narrower head-to-head signal than the composite indexes.

On price, Llama 3.2 3B Instruct is roughly 350.0x 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.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Gemini 1.5 Pro

  • overall performance matters — it scores 12.5 and ranks #232 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 6 of 6 exact shared results
  • you process long inputs — it offers a 2,097,152 token context window

Choose Llama 3.2 3B Instruct

  • cost matters — it's about 350.0x 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

At a glance

The differences that matter most.

Gemini 1.5 Pro
Google
Llama 3.2 3B Instruct
Meta
Core performance indexes
LLM Stats Score
12.5
#232
-5.5
#338
Reasoning
12.2
#229
-6.1
#332
Cost, coverage & limits
Benchmark wins
6 of 6
0 of 6
Input price
$2.50 / M
$0.01 / M
Output price
$10.00 / M
$0.02 / M
Context window
2,097,152
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Gemini 1.5 Pro
Llama 3.2 3B Instruct
Math
17.1#186
-3.2#297
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

23 reported for Gemini 1.5 Pro · 15 for Llama 3.2 3B Instruct

6 shared

Gemini 1.5 Pro outperforms in 6 benchmarks (GPQA, GSM8k, HellaSwag, MATH, MGSM, MMLU), while Llama 3.2 3B Instruct is better at 0 benchmarks.

Gemini 1.5 Pro significantly outperforms across most benchmarks.

Sun Aug 30 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Llama 3.2 3B Instruct costs less

For input processing, Gemini 1.5 Pro ($2.50/1M tokens) is 250.0x more expensive than Llama 3.2 3B Instruct ($0.01/1M tokens).

For output processing, Gemini 1.5 Pro ($10.00/1M tokens) is 500.0x more expensive than Llama 3.2 3B Instruct ($0.02/1M tokens).

In conclusion, Gemini 1.5 Pro is more expensive than Llama 3.2 3B Instruct.*

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

Lowest available price from all providers
Sun Aug 30 2026 • llm-stats.com
Google
Gemini 1.5 Pro
Input tokens$2.50
Output tokens$10.00
Best providerGoogle
Meta
Llama 3.2 3B Instruct
Input tokens$0.01
Output tokens$0.02
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Gemini 1.5 Pro accepts 2,097,152 input tokens compared to Llama 3.2 3B Instruct's 128,000 tokens. Llama 3.2 3B Instruct can generate longer responses up to 128,000 tokens, while Gemini 1.5 Pro is limited to 8,192 tokens.

Google
Gemini 1.5 Pro
Input2,097,152 tokens
Output8,192 tokens
Meta
Llama 3.2 3B Instruct
Input128,000 tokens
Output128,000 tokens
Sun Aug 30 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Gemini 1.5 Pro supports multimodal inputs, whereas Llama 3.2 3B Instruct does not.

Gemini 1.5 Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 1.5 Pro

Text
Images
Audio
Video

Llama 3.2 3B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 1.5 Pro is licensed under a proprietary license, while Llama 3.2 3B Instruct uses Llama 3.2 Community License.

License differences may affect how you can use these models in commercial or open-source projects.

Gemini 1.5 Pro

Proprietary

Closed source

Llama 3.2 3B Instruct

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 3B Instruct was released on 2024-09-25.

Llama 3.2 3B Instruct is 5 months newer than Gemini 1.5 Pro.

Gemini 1.5 Pro

May 1, 2024

2.3 years ago

Llama 3.2 3B Instruct

Sep 25, 2024

1.9 years ago

4mo newer

Knowledge Cutoff

When training data ends

Gemini 1.5 Pro has a documented knowledge cutoff of 2023-11-01, while Llama 3.2 3B Instruct's cutoff date is not specified.

We can confirm Gemini 1.5 Pro's training data extends to 2023-11-01, but cannot make a direct comparison without Llama 3.2 3B Instruct's cutoff date.

Gemini 1.5 Pro

Nov 2023

Llama 3.2 3B Instruct

—

Provider Availability

Gemini 1.5 Pro is available from Google. Llama 3.2 3B Instruct is available from DeepInfra.

Gemini 1.5 Pro

google logo
Google
Input Price:Input: $2.50/1MOutput Price:Output: $10.00/1M

Llama 3.2 3B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.01/1MOutput Price:Output: $0.02/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Gemini 1.5 Pro and Llama 3.2 3B Instruct side-by-side, then vote on the output you prefer.

Gemini 1.5 Pro
✓ Preferred
Llama 3.2 3B Instruct
Open in Playground

FAQ

Common questions about Gemini 1.5 Pro vs Llama 3.2 3B Instruct.

Which is better, Gemini 1.5 Pro or Llama 3.2 3B Instruct?

Gemini 1.5 Pro leads the LLM Stats Score 12.5 to -5.5. Gemini 1.5 Pro is made by Google and Llama 3.2 3B Instruct is made by Meta. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Gemini 1.5 Pro compare to Llama 3.2 3B Instruct in benchmarks?

Gemini 1.5 Pro scores XSTest: 98.8%, FLEURS: 93.3%, HellaSwag: 93.3%, GSM8k: 90.8%, BIG-Bench Hard: 89.2%. Llama 3.2 3B Instruct scores NIH/Multi-needle: 84.7%, ARC-C: 78.6%, GSM8k: 77.7%, IFEval: 77.4%, HellaSwag: 69.8%.

Is Gemini 1.5 Pro cheaper than Llama 3.2 3B Instruct?

Llama 3.2 3B Instruct is 250.0x cheaper for input tokens. Gemini 1.5 Pro costs $2.50/M input and $10.00/M output via google. Llama 3.2 3B Instruct costs $0.01/M input and $0.02/M output via deepinfra.

What are the context window sizes for Gemini 1.5 Pro and Llama 3.2 3B Instruct?

Gemini 1.5 Pro supports 2.1M tokens and Llama 3.2 3B Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 1.5 Pro and Llama 3.2 3B Instruct?

Key differences include LLM Stats Score (12.5 vs -5.5), context window (2.1M vs 128K), input pricing ($2.50 vs $0.01/M), multimodal support (yes vs no), licensing (Proprietary vs Llama 3.2 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 1.5 Pro and Llama 3.2 3B Instruct?

Gemini 1.5 Pro is developed by Google and Llama 3.2 3B Instruct is developed by Meta.

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