Model Comparison

GPT-4.1 nano vs Llama 3.2 90B Instruct

Llama 3.2 90B Instruct shows notably better performance in the majority of benchmarks. GPT-4.1 nano is 2.1x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

GPT-4.1 nano outperforms in 1 benchmarks (GPQA), while Llama 3.2 90B Instruct is better at 3 benchmarks (MathVista, MMLU, MMMU).

Llama 3.2 90B Instruct shows notably better performance in the majority of benchmarks.

Fri May 01 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

GPT-4.1 nano costs less

For input processing, GPT-4.1 nano ($0.10/1M tokens) is 3.5x cheaper than Llama 3.2 90B Instruct ($0.35/1M tokens).

For output processing, GPT-4.1 nano ($0.40/1M tokens) costs the same as Llama 3.2 90B Instruct ($0.40/1M tokens).

In conclusion, Llama 3.2 90B Instruct is more expensive than GPT-4.1 nano.*

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

Lowest available price from all providers
Fri May 01 2026 • llm-stats.com
OpenAI
GPT-4.1 nano
Input tokens$0.10
Output tokens$0.40
Best providerOpenAI
Meta
Llama 3.2 90B Instruct
Input tokens$0.35
Output tokens$0.40
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

GPT-4.1 nano accepts 1,047,576 input tokens compared to Llama 3.2 90B Instruct's 128,000 tokens. Llama 3.2 90B Instruct can generate longer responses up to 128,000 tokens, while GPT-4.1 nano is limited to 32,768 tokens.

OpenAI
GPT-4.1 nano
Input1,047,576 tokens
Output32,768 tokens
Meta
Llama 3.2 90B Instruct
Input128,000 tokens
Output128,000 tokens
Fri May 01 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both GPT-4.1 nano and Llama 3.2 90B Instruct support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

GPT-4.1 nano

Text
Images
Audio
Video

Llama 3.2 90B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-4.1 nano 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-4.1 nano

Proprietary

Closed source

Llama 3.2 90B Instruct

Llama 3.2

Open weights

Release Timeline

When each model was launched

GPT-4.1 nano was released on 2025-04-14, while Llama 3.2 90B Instruct was released on 2024-09-25.

GPT-4.1 nano is 7 months newer than Llama 3.2 90B Instruct.

GPT-4.1 nano

Apr 14, 2025

1.0 years ago

6mo newer
Llama 3.2 90B Instruct

Sep 25, 2024

1.6 years ago

Knowledge Cutoff

When training data ends

GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while Llama 3.2 90B Instruct's cutoff date is not specified.

We can confirm GPT-4.1 nano's training data extends to 2024-05-31, but cannot make a direct comparison without Llama 3.2 90B Instruct's cutoff date.

GPT-4.1 nano

May 2024

Llama 3.2 90B Instruct

—

Provider Availability

GPT-4.1 nano is available from OpenAI. Llama 3.2 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic.

GPT-4.1 nano

openai logo
OpenAI
Input Price:Input: $0.10/1MOutput Price:Output: $0.40/1M

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

OpenAI
Larger context window (1,047,576 tokens)
Less expensive input tokens
Higher GPQA score (50.3% vs 46.7%)
Meta
Has open weights
Higher MathVista score (57.3% vs 56.2%)
Higher MMLU score (86.0% vs 80.1%)
Higher MMMU score (60.3% vs 55.4%)

Detailed Comparison

AI Model Comparison Table
Feature
OpenAI
GPT-4.1 nano
Meta
Llama 3.2 90B Instruct

FAQ

Common questions about GPT-4.1 nano vs Llama 3.2 90B Instruct

Llama 3.2 90B Instruct shows notably better performance in the majority of benchmarks. GPT-4.1 nano is made by OpenAI and Llama 3.2 90B Instruct is made by Meta. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
GPT-4.1 nano scores MMLU: 80.1%, IFEval: 74.5%, CharXiv-D: 73.9%, MMMLU: 66.9%, Multi-IF: 57.2%. Llama 3.2 90B Instruct scores AI2D: 92.3%, DocVQA: 90.1%, MGSM: 86.9%, MMLU: 86.0%, ChartQA: 85.5%.
GPT-4.1 nano is 3.5x cheaper for input tokens. GPT-4.1 nano costs $0.10/M input and $0.40/M output via openai. Llama 3.2 90B Instruct costs $0.35/M input and $0.40/M output via deepinfra.
GPT-4.1 nano supports 1.0M tokens and Llama 3.2 90B Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (1.0M vs 128K), input pricing ($0.10 vs $0.35/M), licensing (Proprietary vs Llama 3.2). See the full comparison above for benchmark-by-benchmark results.
GPT-4.1 nano is developed by OpenAI and Llama 3.2 90B Instruct is developed by Meta.