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

3 benchmarks

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.

Sat Jun 27 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 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

Lowest available price from all providers
Sat Jun 27 2026 • llm-stats.com
OpenAI
GPT-4.1 nano
Input tokens$0.10
Output tokens$0.40
Best providerOpenAI
Meta
Llama 3.1 70B Instruct
Input tokens$0.20
Output tokens$0.20
Best providerLambda
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 3.1 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.

OpenAI
GPT-4.1 nano
Input1,047,576 tokens
Output32,768 tokens
Meta
Llama 3.1 70B Instruct
Input128,000 tokens
Output128,000 tokens
Sat Jun 27 2026 • llm-stats.com

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

Text
Images
Audio
Video

Llama 3.1 70B Instruct

Text
Images
Audio
Video

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.

GPT-4.1 nano

Proprietary

Closed source

Llama 3.1 70B Instruct

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.

GPT-4.1 nano

Apr 14, 2025

1.2 years ago

8mo newer
Llama 3.1 70B Instruct

Jul 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.

GPT-4.1 nano

May 2024

Llama 3.1 70B Instruct

—

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

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

Llama 3.1 70B Instruct

lambda logo
Lambda
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.35/1MOutput Price:Output: $0.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.40/1MOutput Price:Output: $0.40/1M
groq logo
Groq
Input Price:Input: $0.59/1MOutput Price:Output: $0.78/1M
cerebras logo
Cerebras
Input Price:Input: $0.60/1MOutput Price:Output: $0.60/1M
together logo
Together
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
bedrock logo
AWS Bedrock
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
sambanova logo
Sambanova
Input Price:Input: $5.00/1MOutput Price:Output: $10.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

OpenAI
Larger context window (1,047,576 tokens)
Supports multimodal inputs
Less expensive input tokens
Higher GPQA score (50.3% vs 41.7%)
Meta
Less expensive output tokens
Has open weights
Higher IFEval score (87.5% vs 74.5%)
Higher MMLU score (83.6% vs 80.1%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against GPT-4.1 nano and Llama 3.1 70B Instruct side-by-side, then vote on the output you prefer.

GPT-4.1 nano
✓ Preferred
Llama 3.1 70B Instruct
Open in Playground
AI Model Comparison Table
Feature
OpenAI
GPT-4.1 nano
Meta
Llama 3.1 70B Instruct

FAQ

Common questions about GPT-4.1 nano vs Llama 3.1 70B Instruct.

Which is better, GPT-4.1 nano or Llama 3.1 70B Instruct?

Llama 3.1 70B Instruct shows notably better performance in the majority of benchmarks. GPT-4.1 nano is made by OpenAI and Llama 3.1 70B Instruct is made by Meta. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does GPT-4.1 nano compare to Llama 3.1 70B Instruct in benchmarks?

GPT-4.1 nano scores MMLU: 80.1%, IFEval: 74.5%, CharXiv-D: 73.9%, MMMLU: 66.9%, Multi-IF: 57.2%. Llama 3.1 70B Instruct scores GSM-8K (CoT): 95.1%, ARC-C: 94.8%, API-Bank: 90.0%, IFEval: 87.5%, Multilingual MGSM (CoT): 86.9%.

Is GPT-4.1 nano cheaper than Llama 3.1 70B Instruct?

GPT-4.1 nano is 2.0x cheaper for input tokens. GPT-4.1 nano costs $0.10/M input and $0.40/M output via openai. Llama 3.1 70B Instruct costs $0.20/M input and $0.20/M output via lambda.

What are the context window sizes for GPT-4.1 nano and Llama 3.1 70B Instruct?

GPT-4.1 nano supports 1.0M tokens and Llama 3.1 70B Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-4.1 nano and Llama 3.1 70B Instruct?

Key differences include context window (1.0M vs 128K), input pricing ($0.10 vs $0.20/M), multimodal support (yes vs no), licensing (Proprietary vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-4.1 nano and Llama 3.1 70B Instruct?

GPT-4.1 nano is developed by OpenAI and Llama 3.1 70B Instruct is developed by Meta.

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