GPT-4 vs Llama 3.1 8B Instruct
GPT-4 leads the LLM Stats Score 3.0 to -2.6. Llama 3.1 8B Instruct is 1666.7x cheaper per token.
OpenAI · Meta · Updated for 2026
Which is better?
GPT-4 leads the overall LLM Stats Score 3.0 to -2.6, ranking #310 overall.
In the 4 individual benchmarks reported for both models, GPT-4 wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, Llama 3.1 8B Instruct is roughly 1666.7x 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.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-4
- overall performance matters — it scores 3.0 and ranks #310 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 4 exact shared results
Choose Llama 3.1 8B Instruct
- cost matters — it's about 1666.7x 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
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
12 reported for GPT-4 · 18 for Llama 3.1 8B Instruct
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.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-4 ($30.00/1M tokens) is 1500.0x more expensive than Llama 3.1 8B Instruct ($0.02/1M 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
Documented input modalities across available providers
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
3.3 years ago
Jul 23, 2024
2.2 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 DeepInfra, Lambda, Groq, Sambanova, Cerebras, Hyperbolic, Together, Fireworks, Bedrock.
GPT-4
Llama 3.1 8B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4 and Llama 3.1 8B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4 vs Llama 3.1 8B Instruct.