GPT-3.5 Turbo vs Llama 3.2 90B Instruct Comparison

Comparing GPT-3.5 Turbo and Llama 3.2 90B Instruct across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

GPT-3.5 Turbo outperforms in 0 benchmarks, while Llama 3.2 90B Instruct is better at 6 benchmarks (GPQA, MATH, MathVista, MGSM, MMLU, MMMU).

Llama 3.2 90B Instruct significantly outperforms across most benchmarks.

Thu Mar 19 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Llama 3.2 90B Instruct costs less

For input processing, GPT-3.5 Turbo ($0.50/1M tokens) is 1.4x more expensive than Llama 3.2 90B Instruct ($0.35/1M tokens).

For output processing, GPT-3.5 Turbo ($1.50/1M tokens) is 3.8x more expensive than Llama 3.2 90B Instruct ($0.40/1M tokens).

In conclusion, GPT-3.5 Turbo is more expensive than Llama 3.2 90B Instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Thu Mar 19 2026 • llm-stats.com
OpenAI
GPT-3.5 Turbo
Input tokens$0.50
Output tokens$1.50
Best providerAzure
Meta
Llama 3.2 90B Instruct
Input tokens$0.35
Output tokens$0.40
Best providerDeepinfra
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Context Window

Maximum input and output token capacity

Llama 3.2 90B Instruct accepts 128,000 input tokens compared to GPT-3.5 Turbo's 16,385 tokens. Llama 3.2 90B Instruct can generate longer responses up to 128,000 tokens, while GPT-3.5 Turbo is limited to 4,096 tokens.

OpenAI
GPT-3.5 Turbo
Input16,385 tokens
Output4,096 tokens
Meta
Llama 3.2 90B Instruct
Input128,000 tokens
Output128,000 tokens
Thu Mar 19 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Llama 3.2 90B Instruct supports multimodal inputs, whereas GPT-3.5 Turbo does not.

Llama 3.2 90B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT-3.5 Turbo

Text
Images
Audio
Video

Llama 3.2 90B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-3.5 Turbo 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.

GPT-3.5 Turbo

Proprietary

Closed source

Llama 3.2 90B Instruct

Llama 3.2

Open weights

Release Timeline

When each model was launched

GPT-3.5 Turbo was released on 2023-03-21, while Llama 3.2 90B Instruct was released on 2024-09-25.

Llama 3.2 90B Instruct is 18 months newer than GPT-3.5 Turbo.

GPT-3.5 Turbo

Mar 21, 2023

3.0 years ago

Llama 3.2 90B Instruct

Sep 25, 2024

1.5 years ago

1.5yr newer

Knowledge Cutoff

When training data ends

GPT-3.5 Turbo has a documented knowledge cutoff of 2021-09-30, while Llama 3.2 90B Instruct's cutoff date is not specified.

We can confirm GPT-3.5 Turbo's training data extends to 2021-09-30, but cannot make a direct comparison without Llama 3.2 90B Instruct's cutoff date.

GPT-3.5 Turbo

Sep 2021

Llama 3.2 90B Instruct

Provider Availability

GPT-3.5 Turbo is available from Azure, OpenAI. Llama 3.2 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic. The availability of providers can affect quality of the model and reliability.

GPT-3.5 Turbo

azure logo
Azure
Input Price:Input: $0.50/1MOutput Price:Output: $1.50/1M
openai logo
OpenAI
Input Price:Input: $0.50/1MOutput Price:Output: $1.50/1M

Llama 3.2 90B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.35/1MOutput Price:Output: $0.40/1M
bedrock logo
AWS Bedrock
Input Price:Input: $0.72/1MOutput Price:Output: $0.72/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
together logo
Together
Input Price:Input: $1.20/1MOutput Price:Output: $1.20/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $2.00/1MOutput Price:Output: $2.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Larger context window (128,000 tokens)
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens
Has open weights
Higher GPQA score (46.7% vs 30.8%)
Higher MATH score (68.0% vs 43.1%)
Higher MathVista score (57.3% vs 0.0%)
Higher MGSM score (86.9% vs 56.3%)
Higher MMLU score (86.0% vs 69.8%)
Higher MMMU score (60.3% vs 0.0%)

Detailed Comparison

AI Model Comparison Table
Feature
OpenAI
GPT-3.5 Turbo
Meta
Llama 3.2 90B Instruct