Model Comparison
GPT-4 vs Llama 3.1 8B InstructWhich is better in 2026?
GPT-4 shows notably better performance in the majority of benchmarks. Llama 3.1 8B Instruct is 1250.0x cheaper per token.
Verdict: GPT-4 vs Llama 3.1 8B Instruct — which is better?
GPT-4 (by OpenAI) 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.
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.
On price, Llama 3.1 8B Instruct is roughly 1250.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
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 GPT-4 if…
- you want the strongest raw capability — it leads on 3 of 4 shared benchmarks
Choose Llama 3.1 8B Instruct if…
- cost matters — it's about 1250.0x cheaper per token
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped Jul 2024
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
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.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
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
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.
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
Llama 3.1 8B Instruct
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.
Proprietary
Closed source
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.
Jun 13, 2023
3.0 years ago
Jul 23, 2024
1.9 years ago
1.1yr newerKnowledge 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).
Dec 2022
Dec 2023
1 yr newerProvider 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.
GPT-4
Llama 3.1 8B Instruct
Outputs Comparison
Key Takeaways
GPT-4
View detailsOpenAI
Detailed Comparison
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FAQ
Common questions about GPT-4 vs Llama 3.1 8B Instruct.