Model Comparison

GPT-4 Turbo vs o1-mini

o1-mini shows notably better performance in the majority of benchmarks. o1-mini is 2.9x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

GPT-4 Turbo outperforms in 1 benchmarks (MMLU), while o1-mini is better at 2 benchmarks (GPQA, HumanEval).

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

Fri Apr 10 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

o1-mini costs less

For input processing, GPT-4 Turbo ($10.00/1M tokens) is 3.3x more expensive than o1-mini ($3.00/1M tokens).

For output processing, GPT-4 Turbo ($30.00/1M tokens) is 2.5x more expensive than o1-mini ($12.00/1M tokens).

In conclusion, GPT-4 Turbo is more expensive than o1-mini.*

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

Lowest available price from all providers
Fri Apr 10 2026 • llm-stats.com
OpenAI
GPT-4 Turbo
Input tokens$10.00
Output tokens$30.00
Best providerAzure
OpenAI
o1-mini
Input tokens$3.00
Output tokens$12.00
Best providerOpenAI
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Both models have the same input context window of 128,000 tokens. o1-mini can generate longer responses up to 65,536 tokens, while GPT-4 Turbo is limited to 4,096 tokens.

OpenAI
GPT-4 Turbo
Input128,000 tokens
Output4,096 tokens
OpenAI
o1-mini
Input128,000 tokens
Output65,536 tokens
Fri Apr 10 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

GPT-4 Turbo

Proprietary

Closed source

o1-mini

Proprietary

Closed source

Release Timeline

When each model was launched

GPT-4 Turbo was released on 2024-04-09, while o1-mini was released on 2024-09-12.

o1-mini is 5 months newer than GPT-4 Turbo.

GPT-4 Turbo

Apr 9, 2024

2.0 years ago

o1-mini

Sep 12, 2024

1.6 years ago

5mo newer

Knowledge Cutoff

When training data ends

GPT-4 Turbo has a documented knowledge cutoff of 2023-12-31, while o1-mini's cutoff date is not specified.

We can confirm GPT-4 Turbo's training data extends to 2023-12-31, but cannot make a direct comparison without o1-mini's cutoff date.

GPT-4 Turbo

Dec 2023

o1-mini

—

Provider Availability

GPT-4 Turbo is available from Azure, OpenAI. o1-mini is available from OpenAI, Azure.

GPT-4 Turbo

azure logo
Azure
Input Price:Input: $10.00/1MOutput Price:Output: $30.00/1M
openai logo
OpenAI
Input Price:Input: $10.00/1MOutput Price:Output: $30.00/1M

o1-mini

openai logo
OpenAI
Input Price:Input: $3.00/1MOutput Price:Output: $12.00/1M
azure logo
Azure
Input Price:Input: $3.30/1MOutput Price:Output: $13.20/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

OpenAI
Higher MMLU score (86.5% vs 85.2%)
OpenAI
Less expensive input tokens
Less expensive output tokens
Higher GPQA score (60.0% vs 48.0%)
Higher HumanEval score (92.4% vs 87.1%)

Detailed Comparison

AI Model Comparison Table
Feature
OpenAI
GPT-4 Turbo
OpenAI
o1-mini

FAQ

Common questions about GPT-4 Turbo vs o1-mini

o1-mini shows notably better performance in the majority of benchmarks. GPT-4 Turbo is made by OpenAI and o1-mini is made by OpenAI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
GPT-4 Turbo scores MGSM: 88.5%, HumanEval: 87.1%, MMLU: 86.5%, DROP: 86.0%, MATH: 72.6%. o1-mini scores HumanEval: 92.4%, MATH-500: 90.0%, MMLU: 85.2%, SuperGLUE: 75.0%, GPQA: 60.0%.
o1-mini is 3.3x cheaper for input tokens. GPT-4 Turbo costs $10.00/M input and $30.00/M output via azure. o1-mini costs $3.00/M input and $12.00/M output via openai.
GPT-4 Turbo supports 128K tokens and o1-mini supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include input pricing ($10.00 vs $3.00/M). See the full comparison above for benchmark-by-benchmark results.