Model Comparison

DeepSeek VL2 vs Llama 3.1 70B Instruct

Comparing DeepSeek VL2 and Llama 3.1 70B Instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 and Llama 3.1 70B Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers

Wed Apr 22 2026 • llm-stats.com

DeepSeek VL2

Input tokens$0.00

Output tokens$0.00

Best providerUnknown Organization

Llama 3.1 70B Instruct

Input tokens$0.20

Output tokens$0.20

Best providerLambda

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

43.0B diff

Llama 3.1 70B Instruct has 43.0B more parameters than DeepSeek VL2, making it 159.3% larger.

DeepSeek VL2

27.0Bparameters

Llama 3.1 70B Instruct

70.0Bparameters

27.0B

DeepSeek VL2

70.0B

Llama 3.1 70B Instruct

Context Window

Maximum input and output token capacity

DeepSeek VL2 accepts 129,280 input tokens compared to Llama 3.1 70B Instruct's 128,000 tokens. DeepSeek VL2 can generate longer responses up to 129,280 tokens, while Llama 3.1 70B Instruct is limited to 128,000 tokens.

DeepSeek VL2

Input129,280 tokens

Output129,280 tokens

Llama 3.1 70B Instruct

Input128,000 tokens

Output128,000 tokens

Wed Apr 22 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 supports multimodal inputs, whereas Llama 3.1 70B 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 70B Instruct

Text

Images

Audio

Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while Llama 3.1 70B 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 70B 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 70B Instruct was released on 2024-07-23.

DeepSeek VL2 is 5 months newer than Llama 3.1 70B Instruct.

DeepSeek VL2

Dec 13, 2024

1.4 years ago

4mo newer

Llama 3.1 70B Instruct

Jul 23, 2024

1.7 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

DeepSeek VL2 is available from Replicate. Llama 3.1 70B Instruct is available from Lambda, DeepInfra, Hyperbolic, Groq, Cerebras, Together, Fireworks, Bedrock, Sambanova.

DeepSeek VL2

Replicate

Llama 3.1 70B Instruct

Lambda

Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M

Deepinfra

Input Price:Input: $0.35/1MOutput Price:Output: $0.40/1M

Hyperbolic

Input Price:Input: $0.40/1MOutput Price:Output: $0.40/1M

Groq

Input Price:Input: $0.59/1MOutput Price:Output: $0.78/1M

Cerebras

Input Price:Input: $0.60/1MOutput Price:Output: $0.60/1M

Together

Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M

Fireworks

Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M

AWS Bedrock

Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M

Sambanova

Input Price:Input: $5.00/1MOutput Price:Output: $10.00/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek VL2

View details

DeepSeek

Larger context window (129,280 tokens)

Supports multimodal inputs

Llama 3.1 70B Instruct

View details

Detailed Comparison

AI Model Comparison Table
Feature	DeepSeek VL2	Llama 3.1 70B Instruct

FAQ

Common questions about DeepSeek VL2 vs Llama 3.1 70B Instruct

DeepSeek VL2 (DeepSeek) and Llama 3.1 70B Instruct (Meta) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. Llama 3.1 70B Instruct scores GSM-8K (CoT): 95.1%, ARC-C: 94.8%, API-Bank: 90.0%, IFEval: 87.5%, Multilingual MGSM (CoT): 86.9%.

DeepSeek VL2 supports 129K tokens and Llama 3.1 70B 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 (129K vs 128K), multimodal support (yes vs no), licensing (deepseek vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

DeepSeek VL2 is developed by DeepSeek and Llama 3.1 70B Instruct is developed by Meta.

DeepSeek VL2 vs Llama 3.1 70B Instruct

Performance Benchmarks

Arena Performance

Pricing Analysis

Model Size

Context Window

Input Capabilities

DeepSeek VL2

Llama 3.1 70B Instruct

License

Release Timeline

Knowledge Cutoff

Provider Availability

DeepSeek VL2

Llama 3.1 70B Instruct

Outputs Comparison

Key Takeaways

DeepSeek VL2

Llama 3.1 70B Instruct

Detailed Comparison

FAQ

Which is better, DeepSeek VL2 or Llama 3.1 70B Instruct?

How does DeepSeek VL2 compare to Llama 3.1 70B Instruct in benchmarks?

What are the context window sizes for DeepSeek VL2 and Llama 3.1 70B Instruct?

What are the main differences between DeepSeek VL2 and Llama 3.1 70B Instruct?

Who makes DeepSeek VL2 and Llama 3.1 70B Instruct?