GPT-4 vs Llama 3.1 8B Instruct Comparison

Comparing GPT-4 and Llama 3.1 8B Instruct across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

GPT-4 outperforms in 3 benchmarks (DROP, GPQA, MMLU), while Llama 3.1 8B Instruct is better at 1 benchmark (HumanEval).

GPT-4 shows notably better performance in the majority of benchmarks.

Mon Mar 23 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, GPT-4 ($30.00/1M tokens) is 1000.0x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).

For output processing, GPT-4 ($60.00/1M tokens) is 2000.0x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).

In conclusion, GPT-4 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 Mar 23 2026 • llm-stats.com
OpenAI
GPT-4
Input tokens$30.00
Output tokens$60.00
Best providerAzure
Meta
Llama 3.1 8B Instruct
Input tokens$0.03
Output tokens$0.03
Best providerLambda
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Context Window

Maximum input and output token capacity

Llama 3.1 8B Instruct accepts 131,072 input tokens compared to GPT-4's 32,768 tokens. Llama 3.1 8B Instruct can generate longer responses up to 131,072 tokens, while GPT-4 is limited to 32,768 tokens.

OpenAI
GPT-4
Input32,768 tokens
Output32,768 tokens
Meta
Llama 3.1 8B Instruct
Input131,072 tokens
Output131,072 tokens
Mon Mar 23 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-4 supports multimodal inputs, whereas Llama 3.1 8B Instruct does not.

GPT-4 can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT-4

Text
Images
Audio
Video

Llama 3.1 8B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-4 is licensed under a proprietary license, 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.

GPT-4

Proprietary

Closed source

Llama 3.1 8B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

GPT-4 was released on 2023-06-13, while Llama 3.1 8B Instruct was released on 2024-07-23.

Llama 3.1 8B Instruct is 14 months newer than GPT-4.

GPT-4

Jun 13, 2023

2.8 years ago

Llama 3.1 8B Instruct

Jul 23, 2024

1.7 years ago

1.1yr newer

Knowledge Cutoff

When training data ends

GPT-4 has a knowledge cutoff of 2022-12-31, while Llama 3.1 8B Instruct has a cutoff of 2023-12-31.

Llama 3.1 8B Instruct has more recent training data (up to 2023-12-31), making it potentially better informed about events through that date compared to GPT-4 (2022-12-31).

GPT-4

Dec 2022

Llama 3.1 8B Instruct

Dec 2023

1 yr newer

Provider Availability

GPT-4 is available from Azure, OpenAI. Llama 3.1 8B Instruct is available from Lambda, DeepInfra, Groq, Sambanova, Cerebras, Hyperbolic, Together, Fireworks, Bedrock. The availability of providers can affect quality of the model and reliability.

GPT-4

azure logo
Azure
Input Price:Input: $30.00/1MOutput Price:Output: $60.00/1M
openai logo
OpenAI
Input Price:Input: $30.00/1MOutput Price:Output: $60.00/1M

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

Supports multimodal inputs
Higher DROP score (80.9% vs 59.5%)
Higher GPQA score (35.7% vs 30.4%)
Higher MMLU score (86.4% vs 69.4%)
Larger context window (131,072 tokens)
Less expensive input tokens
Less expensive output tokens
Has open weights
Higher HumanEval score (72.6% vs 67.0%)

Detailed Comparison

AI Model Comparison Table
Feature
OpenAI
GPT-4
Meta
Llama 3.1 8B Instruct