Model Comparison
GPT-4 vs Llama 3.2 90B InstructWhich is better in 2026?
Llama 3.2 90B Instruct shows notably better performance in the majority of benchmarks. Llama 3.2 90B Instruct is 103.4x cheaper per token.
Verdict: GPT-4 vs Llama 3.2 90B Instruct — which is better?
GPT-4 (by OpenAI) and Llama 3.2 90B 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 1 benchmarks (MMLU), while Llama 3.2 90B Instruct is better at 3 benchmarks (GPQA, MATH, MGSM). Llama 3.2 90B Instruct shows notably better performance in the majority of benchmarks.
On price, Llama 3.2 90B Instruct is roughly 103.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Llama 3.2 90B Instruct also accepts a larger context window (128,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose GPT-4 if…
- you want predictable pricing at $30.00/M input and $60.00/M output
Choose Llama 3.2 90B Instruct if…
- you want the strongest raw capability — it leads on 3 of 4 shared benchmarks
- cost matters — it's about 103.4x cheaper per token
- you process long inputs — it offers a 128,000 token context window
- you want the most recent training data — it shipped Sep 2024
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
GPT-4 outperforms in 1 benchmarks (MMLU), while Llama 3.2 90B Instruct is better at 3 benchmarks (GPQA, MATH, MGSM).
Llama 3.2 90B Instruct 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 85.7x more expensive than Llama 3.2 90B Instruct ($0.35/1M tokens).
For output processing, GPT-4 ($60.00/1M tokens) is 150.0x more expensive than Llama 3.2 90B Instruct ($0.40/1M tokens).
In conclusion, GPT-4 is more expensive than Llama 3.2 90B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Llama 3.2 90B Instruct accepts 128,000 input tokens compared to GPT-4's 32,768 tokens. Llama 3.2 90B Instruct can generate longer responses up to 128,000 tokens, while GPT-4 is limited to 32,768 tokens.
Input Capabilities
Supported data types and modalities
Both GPT-4 and Llama 3.2 90B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-4
Llama 3.2 90B Instruct
License
Usage and distribution terms
GPT-4 is licensed under a proprietary license, while Llama 3.2 90B Instruct uses Llama 3.2.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Llama 3.2
Open weights
Release Timeline
When each model was launched
GPT-4 was released on 2023-06-13, while Llama 3.2 90B Instruct was released on 2024-09-25.
Llama 3.2 90B Instruct is 16 months newer than GPT-4.
Jun 13, 2023
3.1 years ago
Sep 25, 2024
1.8 years ago
1.3yr newerKnowledge Cutoff
When training data ends
GPT-4 has a documented knowledge cutoff of 2022-12-31, while Llama 3.2 90B Instruct's cutoff date is not specified.
We can confirm GPT-4's training data extends to 2022-12-31, but cannot make a direct comparison without Llama 3.2 90B Instruct's cutoff date.
Dec 2022
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Provider Availability
GPT-4 is available from Azure, OpenAI. Llama 3.2 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic.
GPT-4
Llama 3.2 90B Instruct
Outputs Comparison
Key Takeaways
GPT-4
View detailsOpenAI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against GPT-4 and Llama 3.2 90B Instruct side-by-side, then vote on the output you prefer.
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FAQ
Common questions about GPT-4 vs Llama 3.2 90B Instruct.