Model Comparison
GPT-4.1 nano vs Llama 3.1 70B InstructWhich is better in 2026?
Llama 3.1 70B Instruct shows notably better performance in the majority of benchmarks. GPT-4.1 nano is 1.1x cheaper per token.
Verdict: GPT-4.1 nano vs Llama 3.1 70B Instruct — which is better?
GPT-4.1 nano (by OpenAI) and Llama 3.1 70B 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-4.1 nano outperforms in 1 benchmarks (GPQA), while Llama 3.1 70B Instruct is better at 2 benchmarks (IFEval, MMLU). Llama 3.1 70B Instruct shows notably better performance in the majority of benchmarks.
On price, GPT-4.1 nano is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-4.1 nano also accepts a larger context window (1,047,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose GPT-4.1 nano if…
- cost matters — it's about 1.1x cheaper per token
- you process long inputs — it offers a 1,047,576 token context window
- you want the most recent training data — it shipped Apr 2025
Choose Llama 3.1 70B Instruct if…
- you want the strongest raw capability — it leads on 2 of 3 shared benchmarks
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
GPT-4.1 nano outperforms in 1 benchmarks (GPQA), while Llama 3.1 70B Instruct is better at 2 benchmarks (IFEval, MMLU).
Llama 3.1 70B 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-4.1 nano ($0.10/1M tokens) is 2.0x cheaper than Llama 3.1 70B Instruct ($0.20/1M tokens).
For output processing, GPT-4.1 nano ($0.40/1M tokens) is 2.0x more expensive than Llama 3.1 70B Instruct ($0.20/1M tokens).
In conclusion, Llama 3.1 70B Instruct is more expensive than GPT-4.1 nano.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-4.1 nano accepts 1,047,576 input tokens compared to Llama 3.1 70B Instruct's 128,000 tokens. Llama 3.1 70B Instruct can generate longer responses up to 128,000 tokens, while GPT-4.1 nano is limited to 32,768 tokens.
Input Capabilities
Supported data types and modalities
GPT-4.1 nano supports multimodal inputs, whereas Llama 3.1 70B Instruct does not.
GPT-4.1 nano can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-4.1 nano
Llama 3.1 70B Instruct
License
Usage and distribution terms
GPT-4.1 nano is licensed under a proprietary license, while Llama 3.1 70B 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-4.1 nano was released on 2025-04-14, while Llama 3.1 70B Instruct was released on 2024-07-23.
GPT-4.1 nano is 9 months newer than Llama 3.1 70B Instruct.
Apr 14, 2025
1.2 years ago
8mo newerJul 23, 2024
1.9 years ago
Knowledge Cutoff
When training data ends
GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while Llama 3.1 70B 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 3.1 70B Instruct's cutoff date.
May 2024
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Provider Availability
GPT-4.1 nano is available from OpenAI. Llama 3.1 70B Instruct is available from Lambda, DeepInfra, Hyperbolic, Groq, Cerebras, Together, Fireworks, Bedrock, Sambanova.
GPT-4.1 nano
Llama 3.1 70B Instruct
Outputs Comparison
Key Takeaways
GPT-4.1 nano
View detailsOpenAI
Detailed Comparison
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FAQ
Common questions about GPT-4.1 nano vs Llama 3.1 70B Instruct.