Model Comparison

DeepSeek-R1-0528 vs Llama 3.1 8B Instruct

DeepSeek-R1-0528 significantly outperforms across most benchmarks. Llama 3.1 8B Instruct is 30.4x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-R1-0528 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Llama 3.1 8B Instruct is better at 0 benchmarks.

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Mon Apr 20 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Llama 3.1 8B Instruct costs less

For input processing, DeepSeek-R1-0528 ($0.50/1M tokens) is 16.7x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).

For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 71.7x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).

In conclusion, DeepSeek-R1-0528 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
Mon Apr 20 2026 • llm-stats.com
DeepSeek
DeepSeek-R1-0528
Input tokens$0.50
Output tokens$2.15
Best providerDeepinfra
Meta
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-R1-0528 has 663.0B more parameters than Llama 3.1 8B Instruct, making it 8287.5% larger.

DeepSeek
DeepSeek-R1-0528
671.0Bparameters
Meta
Llama 3.1 8B Instruct
8.0Bparameters
671.0B
DeepSeek-R1-0528
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
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Meta
Llama 3.1 8B Instruct
Input131,072 tokens
Output131,072 tokens
Mon Apr 20 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1-0528 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-R1-0528

MIT

Open weights

Llama 3.1 8B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while Llama 3.1 8B Instruct was released on 2024-07-23.

DeepSeek-R1-0528 is 10 months newer than Llama 3.1 8B Instruct.

DeepSeek-R1-0528

May 28, 2025

10 months ago

10mo 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-R1-0528'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-R1-0528's cutoff date.

DeepSeek-R1-0528

—

Llama 3.1 8B Instruct

Dec 2023

Provider Availability

DeepSeek-R1-0528 is available from DeepInfra, DeepSeek, Novita. Llama 3.1 8B Instruct is available from Lambda, DeepInfra, Groq, Sambanova, Cerebras, Hyperbolic, Together, Fireworks, Bedrock.

DeepSeek-R1-0528

deepinfra logo
Deepinfra
Input Price:Input: $0.50/1MOutput Price:Output: $2.15/1M
deepseek logo
DeepSeek
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
novita logo
Novita
Input Price:Input: $0.70/1MOutput Price:Output: $2.50/1M

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

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Key Takeaways

DeepSeek
Higher GPQA score (81.0% vs 30.4%)
Higher MMLU-Pro score (85.0% vs 48.3%)
Meta
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1-0528
Meta
Llama 3.1 8B Instruct

FAQ

Common questions about DeepSeek-R1-0528 vs Llama 3.1 8B Instruct

DeepSeek-R1-0528 significantly outperforms across most benchmarks. DeepSeek-R1-0528 is made by DeepSeek and Llama 3.1 8B Instruct is made by Meta. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%. 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 16.7x cheaper for input tokens. DeepSeek-R1-0528 costs $0.50/M input and $2.15/M output via deepinfra. Llama 3.1 8B Instruct costs $0.03/M input and $0.03/M output via lambda.
DeepSeek-R1-0528 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 ($0.50 vs $0.03/M), licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-R1-0528 is developed by DeepSeek and Llama 3.1 8B Instruct is developed by Meta.