Model Comparison

DeepSeek VL2 vs Llama 3.1 8B InstructWhich is better in 2026?

Comparing DeepSeek VL2 and Llama 3.1 8B Instruct across benchmarks, pricing, and capabilities.

Verdict: DeepSeek VL2 vs Llama 3.1 8B Instruct — which is better?

DeepSeek VL2 (by DeepSeek) and Llama 3.1 8B 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.

Llama 3.1 8B Instruct also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.

Choose DeepSeek VL2 if…

  • you want the most recent training data — it shipped Dec 2024

Choose Llama 3.1 8B Instruct if…

  • you process long inputs — it offers a 131,072 token context window
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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 and Llama 3.1 8B Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

19.0B diff

DeepSeek VL2 has 19.0B more parameters than Llama 3.1 8B Instruct, making it 237.5% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
Meta
Llama 3.1 8B Instruct
8.0Bparameters
27.0B
DeepSeek VL2
8.0B
Llama 3.1 8B Instruct

Context Window

Maximum input and output token capacity

Llama 3.1 8B Instruct accepts 131,072 input tokens compared to DeepSeek VL2's 129,280 tokens. Llama 3.1 8B Instruct can generate longer responses up to 131,072 tokens, while DeepSeek VL2 is limited to 129,280 tokens.

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Meta
Llama 3.1 8B Instruct
Input131,072 tokens
Output131,072 tokens
Sat Jun 06 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 supports multimodal inputs, whereas Llama 3.1 8B Instruct does not.

DeepSeek VL2 can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek VL2

Text
Images
Audio
Video

Llama 3.1 8B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while Llama 3.1 8B Instruct uses Llama 3.1 Community License.

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

DeepSeek VL2

deepseek

Open weights

Llama 3.1 8B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while Llama 3.1 8B Instruct was released on 2024-07-23.

DeepSeek VL2 is 5 months newer than Llama 3.1 8B Instruct.

DeepSeek VL2

Dec 13, 2024

1.5 years ago

4mo newer
Llama 3.1 8B Instruct

Jul 23, 2024

1.9 years ago

Knowledge Cutoff

When training data ends

Llama 3.1 8B Instruct has a documented knowledge cutoff of 2023-12-31, while DeepSeek VL2's cutoff date is not specified.

We can confirm Llama 3.1 8B Instruct's training data extends to 2023-12-31, but cannot make a direct comparison without DeepSeek VL2's cutoff date.

DeepSeek VL2

—

Llama 3.1 8B Instruct

Dec 2023

Provider Availability

DeepSeek VL2 is available from Replicate. Llama 3.1 8B Instruct is available from Lambda, DeepInfra, Groq, Sambanova, Cerebras, Hyperbolic, Together, Fireworks, Bedrock.

DeepSeek VL2

replicate logo
Replicate

Llama 3.1 8B Instruct

lambda logo
Lambda
Input Price:Input: $0.03/1MOutput Price:Output: $0.03/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.05/1MOutput Price:Output: $0.05/1M
groq logo
Groq
Input Price:Input: $0.05/1MOutput Price:Output: $0.08/1M
sambanova logo
Sambanova
Input Price:Input: $0.10/1MOutput Price:Output: $0.20/1M
cerebras logo
Cerebras
Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M
together logo
Together
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
fireworks logo
Fireworks
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
bedrock logo
AWS Bedrock
Input Price:Input: $0.22/1MOutput Price:Output: $0.22/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Supports multimodal inputs
Meta
Larger context window (131,072 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2
Meta
Llama 3.1 8B Instruct

FAQ

Common questions about DeepSeek VL2 vs Llama 3.1 8B Instruct.

Which is better, DeepSeek VL2 or Llama 3.1 8B Instruct?

DeepSeek VL2 (DeepSeek) and Llama 3.1 8B Instruct (Meta) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek VL2 compare to Llama 3.1 8B Instruct in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. Llama 3.1 8B Instruct scores GSM-8K (CoT): 84.5%, ARC-C: 83.4%, API-Bank: 82.6%, IFEval: 80.4%, BFCL: 76.1%.

What are the context window sizes for DeepSeek VL2 and Llama 3.1 8B Instruct?

DeepSeek VL2 supports 129K tokens and Llama 3.1 8B Instruct supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek VL2 and Llama 3.1 8B Instruct?

Key differences include context window (129K vs 131K), multimodal support (yes vs no), licensing (deepseek vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 and Llama 3.1 8B Instruct?

DeepSeek VL2 is developed by DeepSeek and Llama 3.1 8B Instruct is developed by Meta.

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