Model Comparison

GPT-4.1 nano vs Qwen2.5-Coder 32B Instruct

GPT-4.1 nano significantly outperforms across most benchmarks. Qwen2.5-Coder 32B Instruct is 1.9x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

GPT-4.1 nano outperforms in 1 benchmarks (MMLU), while Qwen2.5-Coder 32B Instruct is better at 0 benchmarks.

GPT-4.1 nano significantly outperforms across most benchmarks.

Wed Apr 22 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen2.5-Coder 32B Instruct costs less

For input processing, GPT-4.1 nano ($0.10/1M tokens) is 1.1x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).

For output processing, GPT-4.1 nano ($0.40/1M tokens) is 4.4x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).

In conclusion, GPT-4.1 nano is more expensive than Qwen2.5-Coder 32B Instruct.*

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

Lowest available price from all providers
Wed Apr 22 2026 • llm-stats.com
OpenAI
GPT-4.1 nano
Input tokens$0.10
Output tokens$0.40
Best providerOpenAI
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct
Input tokens$0.09
Output tokens$0.09
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 Qwen2.5-Coder 32B Instruct's 128,000 tokens. Qwen2.5-Coder 32B 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
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct
Input128,000 tokens
Output128,000 tokens
Wed Apr 22 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-4.1 nano supports multimodal inputs, whereas Qwen2.5-Coder 32B 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

Qwen2.5-Coder 32B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-4.1 nano is licensed under a proprietary license, while Qwen2.5-Coder 32B Instruct uses Apache 2.0.

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

GPT-4.1 nano

Proprietary

Closed source

Qwen2.5-Coder 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

GPT-4.1 nano was released on 2025-04-14, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.

GPT-4.1 nano is 7 months newer than Qwen2.5-Coder 32B Instruct.

GPT-4.1 nano

Apr 14, 2025

1.0 years ago

6mo newer
Qwen2.5-Coder 32B Instruct

Sep 19, 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 Qwen2.5-Coder 32B 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 Qwen2.5-Coder 32B Instruct's cutoff date.

GPT-4.1 nano

May 2024

Qwen2.5-Coder 32B Instruct

—

Provider Availability

GPT-4.1 nano is available from OpenAI. Qwen2.5-Coder 32B Instruct is available from Lambda, DeepInfra, Hyperbolic, Fireworks.

GPT-4.1 nano

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

Qwen2.5-Coder 32B Instruct

lambda logo
Lambda
Input Price:Input: $0.09/1MOutput Price:Output: $0.09/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.18/1MOutput Price:Output: $0.18/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

OpenAI
Larger context window (1,047,576 tokens)
Supports multimodal inputs
Higher MMLU score (80.1% vs 75.1%)
Alibaba Cloud / Qwen Team
Less expensive input tokens
Less expensive output tokens
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
OpenAI
GPT-4.1 nano
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct

FAQ

Common questions about GPT-4.1 nano vs Qwen2.5-Coder 32B Instruct

GPT-4.1 nano significantly outperforms across most benchmarks. GPT-4.1 nano is made by OpenAI and Qwen2.5-Coder 32B Instruct is made by Alibaba Cloud / Qwen Team. 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%. Qwen2.5-Coder 32B Instruct scores HumanEval: 92.7%, GSM8k: 91.1%, MBPP: 90.2%, HellaSwag: 83.0%, Winogrande: 80.8%.
Qwen2.5-Coder 32B Instruct is 1.1x cheaper for input tokens. GPT-4.1 nano costs $0.10/M input and $0.40/M output via openai. Qwen2.5-Coder 32B Instruct costs $0.09/M input and $0.09/M output via lambda.
GPT-4.1 nano supports 1.0M tokens and Qwen2.5-Coder 32B 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 $0.09/M), multimodal support (yes vs no), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
GPT-4.1 nano is developed by OpenAI and Qwen2.5-Coder 32B Instruct is developed by Alibaba Cloud / Qwen Team.