Model Comparison
GPT-4o vs Llama 3.2 90B InstructWhich is better in 2026?
GPT-4o significantly outperforms across most benchmarks. Llama 3.2 90B Instruct is 12.1x cheaper per token.
Verdict: GPT-4o vs Llama 3.2 90B Instruct — which is better?
GPT-4o (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-4o outperforms in 7 benchmarks (AI2D, ChartQA, DocVQA, GPQA, MathVista, MMMU, MMMU-Pro), while Llama 3.2 90B Instruct is better at 1 benchmark (MMLU). GPT-4o significantly outperforms across most benchmarks.
On price, Llama 3.2 90B Instruct is roughly 12.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose GPT-4o if…
- you want the strongest raw capability — it leads on 7 of 8 shared benchmarks
Choose Llama 3.2 90B Instruct if…
- cost matters — it's about 12.1x cheaper per token
- 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-4o outperforms in 7 benchmarks (AI2D, ChartQA, DocVQA, GPQA, MathVista, MMMU, MMMU-Pro), while Llama 3.2 90B Instruct is better at 1 benchmark (MMLU).
GPT-4o significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-4o ($2.50/1M tokens) is 7.1x more expensive than Llama 3.2 90B Instruct ($0.35/1M tokens).
For output processing, GPT-4o ($10.00/1M tokens) is 25.0x more expensive than Llama 3.2 90B Instruct ($0.40/1M tokens).
In conclusion, GPT-4o 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
Both models have the same input context window of 128,000 tokens. Llama 3.2 90B Instruct can generate longer responses up to 128,000 tokens, while GPT-4o is limited to 16,384 tokens.
Input Capabilities
Supported data types and modalities
Both GPT-4o and Llama 3.2 90B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-4o
Llama 3.2 90B Instruct
License
Usage and distribution terms
GPT-4o 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-4o was released on 2024-08-06, while Llama 3.2 90B Instruct was released on 2024-09-25.
Llama 3.2 90B Instruct is 2 months newer than GPT-4o.
Aug 6, 2024
1.9 years ago
Sep 25, 2024
1.7 years ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GPT-4o is available from Azure, OpenAI. Llama 3.2 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic.
GPT-4o
Llama 3.2 90B Instruct
Outputs Comparison
Key Takeaways
GPT-4o
View detailsOpenAI
Detailed Comparison
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FAQ
Common questions about GPT-4o vs Llama 3.2 90B Instruct.