DeepSeek-V2.5 vs Llama 3.2 11B Instruct Comparison

Comparing DeepSeek-V2.5 and Llama 3.2 11B Instruct across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V2.5 outperforms in 2 benchmarks (MATH, MMLU), while Llama 3.2 11B Instruct is better at 0 benchmarks.

DeepSeek-V2.5 significantly outperforms across most benchmarks.

Mon Mar 16 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, DeepSeek-V2.5 ($0.14/1M tokens) is 2.8x more expensive than Llama 3.2 11B Instruct ($0.05/1M tokens).

For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 5.6x more expensive than Llama 3.2 11B Instruct ($0.05/1M tokens).

In conclusion, DeepSeek-V2.5 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
Mon Mar 16 2026 • llm-stats.com
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
Meta
Llama 3.2 11B Instruct
Input tokens$0.05
Output tokens$0.05
Best providerDeepinfra
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Model Size

Parameter count comparison

225.4B diff

DeepSeek-V2.5 has 225.4B more parameters than Llama 3.2 11B Instruct, making it 2126.4% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
Meta
Llama 3.2 11B Instruct
10.6Bparameters
236.0B
DeepSeek-V2.5
10.6B
Llama 3.2 11B Instruct

Context Window

Maximum input and output token capacity

Llama 3.2 11B Instruct accepts 128,000 input tokens compared to DeepSeek-V2.5's 8,192 tokens. Llama 3.2 11B Instruct can generate longer responses up to 128,000 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Meta
Llama 3.2 11B Instruct
Input128,000 tokens
Output128,000 tokens
Mon Mar 16 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Llama 3.2 11B Instruct supports multimodal inputs, whereas DeepSeek-V2.5 does not.

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

DeepSeek-V2.5

Text
Images
Audio
Video

Llama 3.2 11B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, 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.

DeepSeek-V2.5

deepseek

Open weights

Llama 3.2 11B Instruct

Llama 3.2 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while Llama 3.2 11B Instruct was released on 2024-09-25.

Llama 3.2 11B Instruct is 5 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

1.9 years ago

Llama 3.2 11B Instruct

Sep 25, 2024

1.5 years ago

4mo newer

Knowledge Cutoff

When training data ends

Llama 3.2 11B Instruct has a documented knowledge cutoff of 2023-12-31, while DeepSeek-V2.5's cutoff date is not specified.

We can confirm Llama 3.2 11B Instruct's training data extends to 2023-12-31, but cannot make a direct comparison without DeepSeek-V2.5's cutoff date.

DeepSeek-V2.5

Llama 3.2 11B Instruct

Dec 2023

Provider Availability

DeepSeek-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic. Llama 3.2 11B Instruct is available from DeepInfra, Sambanova, Bedrock, Groq, Together, Fireworks. The availability of providers can affect quality of the model and reliability.

DeepSeek-V2.5

deepseek logo
DeepSeek
Input Price:Input: $0.14/1MOutput Price:Output: $0.28/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.70/1MOutput Price:Output: $1.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $2.00/1MOutput Price:Output: $2.00/1M

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

Higher MATH score (74.7% vs 51.9%)
Higher MMLU score (80.4% vs 73.0%)
Larger context window (128,000 tokens)
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V2.5
Meta
Llama 3.2 11B Instruct