GPT-3.5 Turbo vs Llama 3.1 8B Instruct
GPT-3.5 Turbo shows notably better performance in the majority of benchmarks. Llama 3.1 8B Instruct is 25.0x cheaper per token.
OpenAI · Meta · Updated for 2026
Which is better?
GPT-3.5 Turbo outperforms in 3 benchmarks (DROP, GPQA, MMLU), while Llama 3.1 8B Instruct is better at 1 benchmark (HumanEval). GPT-3.5 Turbo shows notably better performance in the majority of benchmarks.
On price, Llama 3.1 8B Instruct is roughly 25.0x 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.
Based on current benchmark, pricing, and model metadata for 2026.
Choose GPT-3.5 Turbo
- you want the strongest raw capability — it leads on 3 of 4 shared benchmarks
Choose Llama 3.1 8B Instruct
- cost matters — it's about 25.0x 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
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
GPT-3.5 Turbo outperforms in 3 benchmarks (DROP, GPQA, MMLU), while Llama 3.1 8B Instruct is better at 1 benchmark (HumanEval).
GPT-3.5 Turbo shows notably better performance in the majority of benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-3.5 Turbo ($0.50/1M tokens) is 16.7x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).
For output processing, GPT-3.5 Turbo ($1.50/1M tokens) is 50.0x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).
In conclusion, GPT-3.5 Turbo 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-3.5 Turbo's 16,385 tokens. Llama 3.1 8B Instruct can generate longer responses up to 131,072 tokens, while GPT-3.5 Turbo is limited to 4,096 tokens.
License
Usage and distribution terms
GPT-3.5 Turbo 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-3.5 Turbo was released on 2023-03-21, while Llama 3.1 8B Instruct was released on 2024-07-23.
Llama 3.1 8B Instruct is 16 months newer than GPT-3.5 Turbo.
Mar 21, 2023
3.4 years ago
Jul 23, 2024
2.1 years ago
1.3yr newerKnowledge Cutoff
When training data ends
GPT-3.5 Turbo has a knowledge cutoff of 2021-09-30, 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-3.5 Turbo (2021-09-30).
Sep 2021
Dec 2023
2.3 yr newerProvider Availability
GPT-3.5 Turbo is available from Azure, OpenAI. Llama 3.1 8B Instruct is available from Lambda, DeepInfra, Groq, Sambanova, Cerebras, Hyperbolic, Together, Fireworks, Bedrock.
GPT-3.5 Turbo
Llama 3.1 8B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-3.5 Turbo and Llama 3.1 8B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-3.5 Turbo vs Llama 3.1 8B Instruct.