Model Comparison

DeepSeek R1 Distill Llama 8B vs GPT-4.1 nano

Both models are evenly matched across the benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek R1 Distill Llama 8B outperforms in 1 benchmarks (AIME 2024), while GPT-4.1 nano is better at 1 benchmark (GPQA).

Both models are evenly matched across the benchmarks.

Mon Apr 06 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Mon Apr 06 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Distill Llama 8B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
OpenAI
GPT-4.1 nano
Input tokens$0.10
Output tokens$0.40
Best providerOpenAI
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Only GPT-4.1 nano specifies input context (1,047,576 tokens). Only GPT-4.1 nano specifies output context (32,768 tokens).

DeepSeek
DeepSeek R1 Distill Llama 8B
Input- tokens
Output- tokens
OpenAI
GPT-4.1 nano
Input1,047,576 tokens
Output32,768 tokens
Mon Apr 06 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-4.1 nano supports multimodal inputs, whereas DeepSeek R1 Distill Llama 8B does not.

GPT-4.1 nano can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek R1 Distill Llama 8B

Text
Images
Audio
Video

GPT-4.1 nano

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Distill Llama 8B is licensed under MIT, while GPT-4.1 nano uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek R1 Distill Llama 8B

MIT

Open weights

GPT-4.1 nano

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek R1 Distill Llama 8B was released on 2025-01-20, while GPT-4.1 nano was released on 2025-04-14.

GPT-4.1 nano is 3 months newer than DeepSeek R1 Distill Llama 8B.

DeepSeek R1 Distill Llama 8B

Jan 20, 2025

1.2 years ago

GPT-4.1 nano

Apr 14, 2025

11 months ago

2mo newer

Knowledge Cutoff

When training data ends

GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while DeepSeek R1 Distill Llama 8B'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 DeepSeek R1 Distill Llama 8B's cutoff date.

DeepSeek R1 Distill Llama 8B

—

GPT-4.1 nano

May 2024

Outputs Comparison

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Key Takeaways

DeepSeek
Has open weights
Higher AIME 2024 score (80.0% vs 29.4%)
OpenAI
Larger context window (1,047,576 tokens)
Supports multimodal inputs
Higher GPQA score (50.3% vs 49.0%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Llama 8B
OpenAI
GPT-4.1 nano

FAQ

Common questions about DeepSeek R1 Distill Llama 8B vs GPT-4.1 nano

Both models are evenly matched across the benchmarks. DeepSeek R1 Distill Llama 8B is made by DeepSeek and GPT-4.1 nano is made by OpenAI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek R1 Distill Llama 8B scores MATH-500: 89.1%, AIME 2024: 80.0%, GPQA: 49.0%, LiveCodeBench: 39.6%. GPT-4.1 nano scores MMLU: 80.1%, IFEval: 74.5%, CharXiv-D: 73.9%, MMMLU: 66.9%, Multi-IF: 57.2%.
DeepSeek R1 Distill Llama 8B supports an unknown number of tokens and GPT-4.1 nano supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.
DeepSeek R1 Distill Llama 8B is developed by DeepSeek and GPT-4.1 nano is developed by OpenAI.