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GPT-4.1 nano vs GPT OSS 20B

GPT OSS 20B significantly outperforms across most benchmarks. GPT OSS 20B is 2.0x cheaper per token.

OpenAI · OpenAI · Updated for 2026

Which is better?

GPT-4.1 nano outperforms in 0 benchmarks, while GPT OSS 20B is better at 3 benchmarks (GPQA, MMLU, TAU-bench Retail). GPT OSS 20B significantly outperforms across most benchmarks.

On price, GPT OSS 20B is roughly 2.0x 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.

Based on current benchmark, pricing, and model metadata for 2026.

Choose GPT-4.1 nano

  • you process long inputs — it offers a 1,047,576 token context window

Choose GPT OSS 20B

  • you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
  • cost matters — it's about 2.0x cheaper per token
  • you want the most recent training data — it shipped Aug 2025
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Benchmark wins
0 of 3
3 of 3
Input price
$0.10 / M
$0.05 / M
Output price
$0.40 / M
$0.20 / M
Context window
1,047,576
131,072
Released
Apr 2025
Aug 2025
License
Proprietary
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

GPT-4.1 nano outperforms in 0 benchmarks, while GPT OSS 20B is better at 3 benchmarks (GPQA, MMLU, TAU-bench Retail).

GPT OSS 20B significantly outperforms across most benchmarks.

Tue Aug 25 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Pricing Analysis

Price comparison per million tokens

GPT OSS 20B costs less

For input processing, GPT-4.1 nano ($0.10/1M tokens) is 2.0x more expensive than GPT OSS 20B ($0.05/1M tokens).

For output processing, GPT-4.1 nano ($0.40/1M tokens) is 2.0x more expensive than GPT OSS 20B ($0.20/1M tokens).

In conclusion, GPT-4.1 nano is more expensive than GPT OSS 20B.*

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

Lowest available price from all providers
Tue Aug 25 2026 • llm-stats.com
OpenAI
GPT-4.1 nano
Input tokens$0.10
Output tokens$0.40
Best providerOpenAI
OpenAI
GPT OSS 20B
Input tokens$0.05
Output tokens$0.20
Best providerNovita
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 GPT OSS 20B's 131,072 tokens. Both models can generate responses up to 32,768 tokens.

OpenAI
GPT-4.1 nano
Input1,047,576 tokens
Output32,768 tokens
OpenAI
GPT OSS 20B
Input131,072 tokens
Output32,768 tokens
Tue Aug 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-4.1 nano supports multimodal inputs, whereas GPT OSS 20B 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

GPT OSS 20B

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-4.1 nano is licensed under a proprietary license, while GPT OSS 20B 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

GPT OSS 20B

Apache 2.0

Open weights

Release Timeline

When each model was launched

GPT-4.1 nano was released on 2025-04-14, while GPT OSS 20B was released on 2025-08-05.

GPT OSS 20B is 4 months newer than GPT-4.1 nano.

GPT-4.1 nano

Apr 14, 2025

1.4 years ago

GPT OSS 20B

Aug 5, 2025

1.1 years ago

3mo newer

Knowledge Cutoff

When training data ends

GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while GPT OSS 20B'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 GPT OSS 20B's cutoff date.

GPT-4.1 nano

May 2024

GPT OSS 20B

Provider Availability

GPT-4.1 nano is available from OpenAI. GPT OSS 20B is available from Novita, Fireworks, Groq, OpenAI.

GPT-4.1 nano

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

GPT OSS 20B

novita logo
Novita
Input Price:Input: $0.05/1MOutput Price:Output: $0.20/1M
fireworks logo
Fireworks
Input Price:Input: $0.10/1MOutput Price:Output: $0.50/1M
groq logo
Groq
Input Price:Input: $0.10/1MOutput Price:Output: $0.50/1M
openai logo
OpenAI
Input Price:Input: $0.10/1MOutput Price:Output: $0.50/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against GPT-4.1 nano and GPT OSS 20B side-by-side, then vote on the output you prefer.

GPT-4.1 nano
✓ Preferred
GPT OSS 20B
Open in Playground

FAQ

Common questions about GPT-4.1 nano vs GPT OSS 20B.

Which is better, GPT-4.1 nano or GPT OSS 20B?

GPT OSS 20B significantly outperforms across most benchmarks. GPT-4.1 nano is made by OpenAI and GPT OSS 20B is made by OpenAI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does GPT-4.1 nano compare to GPT OSS 20B in benchmarks?

GPT-4.1 nano scores MMLU: 80.1%, IFEval: 74.5%, CharXiv-D: 73.9%, MMMLU: 66.9%, Multi-IF: 57.2%. GPT OSS 20B scores MMLU: 85.3%, CodeForces: 74.3%, GPQA: 71.5%, TAU-bench Retail: 54.8%, HealthBench: 42.5%.

Is GPT-4.1 nano cheaper than GPT OSS 20B?

GPT OSS 20B is 2.0x cheaper for input tokens. GPT-4.1 nano costs $0.10/M input and $0.40/M output via openai. GPT OSS 20B costs $0.05/M input and $0.20/M output via novita.

What are the context window sizes for GPT-4.1 nano and GPT OSS 20B?

GPT-4.1 nano supports 1.0M tokens and GPT OSS 20B supports 131K 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 GPT OSS 20B?

Key differences include context window (1.0M vs 131K), input pricing ($0.10 vs $0.05/M), multimodal support (yes vs no), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.