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GPT-4.1 mini vs o1-preview

GPT-4.1 mini and o1-preview are closely matched at 14.2 and 16.7 on the LLM Stats Score. GPT-4.1 mini is 37.5x cheaper per token.

OpenAI · OpenAI · Updated for 2026

Which is better?

GPT-4.1 mini and o1-preview are closely matched on the overall LLM Stats Score at 14.2 and 16.7.

In the 4 individual benchmarks reported for both models, o1-preview wins 3; this is a narrower head-to-head signal than the composite indexes.

On price, GPT-4.1 mini is roughly 37.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

GPT-4.1 mini 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 LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GPT-4.1 mini

  • cost matters — it's about 37.5x 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 o1-preview

  • you value its reported benchmark strengths — it wins 3 of 4 exact shared results

At a glance

The differences that matter most.

Core performance indexes
14.2
#227
16.7
#208
14.2
#219
17.0
#201
-3.0
#244
-2.9
#243
Cost, coverage & limits
Benchmark wins
1 of 4
3 of 4
Input price
$0.40 / M
$15.00 / M
Output price
$1.60 / M
$60.00 / M
Context window
1,047,576
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
GPT-4.1 mini
o1-preview
13.8#217
20.4#151
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

28 reported for GPT-4.1 mini · 8 for o1-preview

4 shared

GPT-4.1 mini outperforms in 1 benchmarks (AIME 2024), while o1-preview is better at 3 benchmarks (GPQA, MMLU, SWE-Bench Verified).

o1-preview shows notably better performance in the majority of benchmarks.

Sun Sep 06 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

GPT-4.1 mini costs less

For input processing, GPT-4.1 mini ($0.40/1M tokens) is 37.5x cheaper than o1-preview ($15.00/1M tokens).

For output processing, GPT-4.1 mini ($1.60/1M tokens) is 37.5x cheaper than o1-preview ($60.00/1M tokens).

In conclusion, o1-preview is more expensive than GPT-4.1 mini.*

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

Lowest available price from all providers
Sun Sep 06 2026 • llm-stats.com
OpenAI
GPT-4.1 mini
Input tokens$0.40
Output tokens$1.60
Best providerOpenAI
OpenAI
o1-preview
Input tokens$15.00
Output tokens$60.00
Best providerOpenAI
Notice missing or incorrect data?Start an Issue

Context Window

Maximum input and output token capacity

GPT-4.1 mini accepts 1,047,576 input tokens compared to o1-preview's 128,000 tokens. Both models can generate responses up to 32,768 tokens.

OpenAI
GPT-4.1 mini
Input1,047,576 tokens
Output32,768 tokens
OpenAI
o1-preview
Input128,000 tokens
Output32,768 tokens
Sun Sep 06 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GPT-4.1 mini supports multimodal inputs, whereas o1-preview does not.

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

GPT-4.1 mini

Text
Images
Audio
Video

o1-preview

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

GPT-4.1 mini

Proprietary

Closed source

o1-preview

Proprietary

Closed source

Release Timeline

When each model was launched

GPT-4.1 mini was released on 2025-04-14, while o1-preview was released on 2024-09-12.

GPT-4.1 mini is 7 months newer than o1-preview.

GPT-4.1 mini

Apr 14, 2025

1.4 years ago

7mo newer
o1-preview

Sep 12, 2024

2.0 years ago

Knowledge Cutoff

When training data ends

GPT-4.1 mini has a documented knowledge cutoff of 2024-05-31, while o1-preview's cutoff date is not specified.

We can confirm GPT-4.1 mini's training data extends to 2024-05-31, but cannot make a direct comparison without o1-preview's cutoff date.

GPT-4.1 mini

May 2024

o1-preview

Provider Availability

GPT-4.1 mini is available from OpenAI. o1-preview is available from OpenAI, Azure.

GPT-4.1 mini

openai logo
OpenAI
Input Price:Input: $0.40/1MOutput Price:Output: $1.60/1M

o1-preview

openai logo
OpenAI
Input Price:Input: $15.00/1MOutput Price:Output: $60.00/1M
azure logo
Azure
Input Price:Input: $16.50/1MOutput Price:Output: $66.00/1M
* 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 mini and o1-preview side-by-side, then vote on the output you prefer.

GPT-4.1 mini
✓ Preferred
o1-preview
Open in Playground

FAQ

Common questions about GPT-4.1 mini vs o1-preview.

Which is better, GPT-4.1 mini or o1-preview?

GPT-4.1 mini and o1-preview are closely matched on the LLM Stats Score at 14.2 and 16.7. GPT-4.1 mini is made by OpenAI and o1-preview is made by OpenAI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GPT-4.1 mini compare to o1-preview in benchmarks?

GPT-4.1 mini scores CharXiv-D: 88.4%, MMLU: 87.5%, IFEval: 84.1%, MMMLU: 78.5%, MathVista: 73.1%. o1-preview scores MGSM: 90.8%, MMLU: 90.8%, MATH: 85.5%, GPQA: 73.3%, LiveBench: 52.3%.

Is GPT-4.1 mini cheaper than o1-preview?

GPT-4.1 mini is 37.5x cheaper for input tokens. GPT-4.1 mini costs $0.40/M input and $1.60/M output via openai. o1-preview costs $15.00/M input and $60.00/M output via openai.

What are the context window sizes for GPT-4.1 mini and o1-preview?

GPT-4.1 mini supports 1.0M tokens and o1-preview 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 mini and o1-preview?

Key differences include LLM Stats Score (14.2 vs 16.7), context window (1.0M vs 128K), input pricing ($0.40 vs $15.00/M), multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.