Model Comparison

DeepSeek-R1 vs Llama 3.1 8B Instruct

Comparing DeepSeek-R1 and Llama 3.1 8B Instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1 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

Pricing Analysis

Price comparison per million tokens

Llama 3.1 8B Instruct costs less

For input processing, DeepSeek-R1 ($0.55/1M tokens) is 18.3x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).

For output processing, DeepSeek-R1 ($2.19/1M tokens) is 73.0x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).

In conclusion, DeepSeek-R1 is more expensive than Llama 3.1 8B Instruct.*

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

Lowest available price from all providers

Tue Apr 14 2026 • llm-stats.com

DeepSeek-R1

Input tokens$0.55

Output tokens$2.19

Best providerDeepSeek

Llama 3.1 8B Instruct

Input tokens$0.03

Output tokens$0.03

Best providerLambda

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

663.0B diff

DeepSeek-R1 has 663.0B more parameters than Llama 3.1 8B Instruct, making it 8287.5% larger.

DeepSeek-R1

671.0Bparameters

Llama 3.1 8B Instruct

8.0Bparameters

671.0B

DeepSeek-R1

8.0B

Llama 3.1 8B Instruct

Context Window

Maximum input and output token capacity

Both models have the same input context window of 131,072 tokens. Both models can generate responses up to 131,072 tokens.

DeepSeek-R1

Input131,072 tokens

Output131,072 tokens

Llama 3.1 8B Instruct

Input131,072 tokens

Output131,072 tokens

Tue Apr 14 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1 is licensed under MIT, 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-R1

MIT

Open weights

Llama 3.1 8B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while Llama 3.1 8B Instruct was released on 2024-07-23.

DeepSeek-R1 is 6 months newer than Llama 3.1 8B Instruct.

DeepSeek-R1

Jan 20, 2025

1.2 years ago

6mo newer

Llama 3.1 8B Instruct

Jul 23, 2024

1.7 years ago

Knowledge Cutoff

When training data ends

Llama 3.1 8B Instruct has a documented knowledge cutoff of 2023-12-31, while DeepSeek-R1'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-R1's cutoff date.

DeepSeek-R1

—

Llama 3.1 8B Instruct

Dec 2023

Provider Availability

DeepSeek-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. Llama 3.1 8B Instruct is available from Lambda, DeepInfra, Groq, Sambanova, Cerebras, Hyperbolic, Together, Fireworks, Bedrock.

DeepSeek-R1

DeepSeek

Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M

Deepinfra

Input Price:Input: $0.85/1MOutput Price:Output: $2.50/1M

Together

Input Price:Input: $7.00/1MOutput Price:Output: $7.00/1M

Fireworks

Input Price:Input: $8.00/1MOutput Price:Output: $8.00/1M

Llama 3.1 8B Instruct

Lambda

Input Price:Input: $0.03/1MOutput Price:Output: $0.03/1M

Deepinfra

Input Price:Input: $0.05/1MOutput Price:Output: $0.05/1M

Groq

Input Price:Input: $0.05/1MOutput Price:Output: $0.08/1M

Sambanova

Input Price:Input: $0.10/1MOutput Price:Output: $0.20/1M

Cerebras

Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M

Hyperbolic

Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M

Together

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

Fireworks

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

AWS Bedrock

Input Price:Input: $0.22/1MOutput Price:Output: $0.22/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Detailed Comparison

AI Model Comparison Table
Feature	DeepSeek-R1	Llama 3.1 8B Instruct

FAQ

Common questions about DeepSeek-R1 vs Llama 3.1 8B Instruct

DeepSeek-R1 (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.

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%.

Llama 3.1 8B Instruct is 18.3x cheaper for input tokens. DeepSeek-R1 costs $0.55/M input and $2.19/M output via deepseek. Llama 3.1 8B Instruct costs $0.03/M input and $0.03/M output via lambda.

DeepSeek-R1 supports 131K 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.

Key differences include input pricing ($0.55 vs $0.03/M), licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

DeepSeek-R1 is developed by DeepSeek and Llama 3.1 8B Instruct is developed by Meta.

DeepSeek-R1 vs Llama 3.1 8B Instruct

Performance Benchmarks

Arena Performance

Pricing Analysis

Model Size

Context Window

License

Release Timeline

Knowledge Cutoff

Provider Availability

DeepSeek-R1

Llama 3.1 8B Instruct

Outputs Comparison

Key Takeaways

DeepSeek-R1

Llama 3.1 8B Instruct

Detailed Comparison

FAQ

Which is better, DeepSeek-R1 or Llama 3.1 8B Instruct?

How does DeepSeek-R1 compare to Llama 3.1 8B Instruct in benchmarks?

Is DeepSeek-R1 cheaper than Llama 3.1 8B Instruct?

What are the context window sizes for DeepSeek-R1 and Llama 3.1 8B Instruct?

What are the main differences between DeepSeek-R1 and Llama 3.1 8B Instruct?

Who makes DeepSeek-R1 and Llama 3.1 8B Instruct?