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GPT-5 nano vs Ministral 3 (14B Reasoning 2512)

GPT-5 nano and Ministral 3 (14B Reasoning 2512) are closely matched at 19.1 and 20.3 on the LLM Stats Score. GPT-5 nano is 1.5x cheaper per token.

OpenAI · Mistral AI · Updated for 2026

Which is better?

GPT-5 nano and Ministral 3 (14B Reasoning 2512) are closely matched on the overall LLM Stats Score at 19.1 and 20.3.

The models split the 2 individual benchmarks reported for both models evenly.

On price, GPT-5 nano is roughly 1.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

GPT-5 nano also accepts a larger context window (400,000 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-5 nano

  • cost matters — it's about 1.5x cheaper per token
  • you process long inputs — it offers a 400,000 token context window

Choose Ministral 3 (14B Reasoning 2512)

  • you want the most recent training data — it shipped Dec 2025
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

GPT-5 nano
OpenAI
Ministral 3 (14B Reasoning 2512)
Mistral AI
Core performance indexes
LLM Stats Score
19.1
#229
20.3
#217
Reasoning
18.4
#229
20.3
#209
Cost, coverage & limits
Benchmark wins
1 of 2
1 of 2
Input price
$0.05 / M
$0.20 / M
Output price
$0.40 / M
$0.20 / M
Context window
400,000
262,100

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
GPT-5 nano
Ministral 3 (14B Reasoning 2512)
Math
18.9#181
21.0#161
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

5 reported for GPT-5 nano · 4 for Ministral 3 (14B Reasoning 2512)

2 shared

GPT-5 nano outperforms in 1 benchmarks (AIME 2025), while Ministral 3 (14B Reasoning 2512) is better at 0 benchmarks.

GPT-5 nano has a slight edge in benchmark performance.

Tue Oct 20 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

GPT-5 nano costs less

For input processing, GPT-5 nano ($0.05/1M tokens) is 4.0x cheaper than Ministral 3 (14B Reasoning 2512) ($0.20/1M tokens).

For output processing, GPT-5 nano ($0.40/1M tokens) is 2.0x more expensive than Ministral 3 (14B Reasoning 2512) ($0.20/1M tokens).

In conclusion, Ministral 3 (14B Reasoning 2512) is more expensive than GPT-5 nano.*

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

Lowest available price from all providers
Tue Oct 20 2026 • llm-stats.com
OpenAI
GPT-5 nano
Input tokens$0.05
Output tokens$0.40
Best providerOpenAI
Mistral AI
Ministral 3 (14B Reasoning 2512)
Input tokens$0.20
Output tokens$0.20
Best providerMistral
Notice missing or incorrect data?

Context Window

Maximum input and output token capacity

GPT-5 nano accepts 400,000 input tokens compared to Ministral 3 (14B Reasoning 2512)'s 262,100 tokens. Ministral 3 (14B Reasoning 2512) can generate longer responses up to 262,100 tokens, while GPT-5 nano is limited to 128,000 tokens.

OpenAI
GPT-5 nano
Input400,000 tokens
Output128,000 tokens
Mistral AI
Ministral 3 (14B Reasoning 2512)
Input262,100 tokens
Output262,100 tokens
Tue Oct 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both GPT-5 nano and Ministral 3 (14B Reasoning 2512) support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

GPT-5 nano

Text
Images
Audio
Video

Ministral 3 (14B Reasoning 2512)

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-5 nano is licensed under a proprietary license, while Ministral 3 (14B Reasoning 2512) uses Apache 2.0.

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

GPT-5 nano

Proprietary

Closed source

Ministral 3 (14B Reasoning 2512)

Apache 2.0

Open weights

Release Timeline

When each model was launched

GPT-5 nano was released on 2025-08-07, while Ministral 3 (14B Reasoning 2512) was released on 2025-12-04.

Ministral 3 (14B Reasoning 2512) is 4 months newer than GPT-5 nano.

GPT-5 nano

Aug 7, 2025

1.2 years ago

Ministral 3 (14B Reasoning 2512)

Dec 4, 2025

10 months ago

3mo newer

Knowledge Cutoff

When training data ends

GPT-5 nano has a documented knowledge cutoff of 2024-05-30, while Ministral 3 (14B Reasoning 2512)'s cutoff date is not specified.

We can confirm GPT-5 nano's training data extends to 2024-05-30, but cannot make a direct comparison without Ministral 3 (14B Reasoning 2512)'s cutoff date.

GPT-5 nano

May 2024

Ministral 3 (14B Reasoning 2512)

—

Provider Availability

GPT-5 nano is available from OpenAI. Ministral 3 (14B Reasoning 2512) is available from Mistral AI.

GPT-5 nano

openai logo
OpenAI
Input Price:Input: $0.05/1MOutput Price:Output: $0.40/1M

Ministral 3 (14B Reasoning 2512)

mistral logo
Mistral
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against GPT-5 nano and Ministral 3 (14B Reasoning 2512) side-by-side, then vote on the output you prefer.

GPT-5 nano
✓ Preferred
Ministral 3 (14B Reasoning 2512)
Open in Playground

FAQ

Common questions about GPT-5 nano vs Ministral 3 (14B Reasoning 2512).

Which is better, GPT-5 nano or Ministral 3 (14B Reasoning 2512)?

GPT-5 nano and Ministral 3 (14B Reasoning 2512) are closely matched on the LLM Stats Score at 19.1 and 20.3. GPT-5 nano is made by OpenAI and Ministral 3 (14B Reasoning 2512) is made by Mistral AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GPT-5 nano compare to Ministral 3 (14B Reasoning 2512) in benchmarks?

GPT-5 nano scores AIME 2025: 85.2%, HMMT 2025: 75.6%, GPQA: 71.2%, FrontierMath: 9.6%, Humanity's Last Exam: 8.7%. Ministral 3 (14B Reasoning 2512) scores AIME 2024: 89.8%, AIME 2025: 85.0%, GPQA: 71.2%, LiveCodeBench: 64.6%.

Is GPT-5 nano cheaper than Ministral 3 (14B Reasoning 2512)?

GPT-5 nano is 4.0x cheaper for input tokens. GPT-5 nano costs $0.05/M input and $0.40/M output via openai. Ministral 3 (14B Reasoning 2512) costs $0.20/M input and $0.20/M output via mistral.

What are the context window sizes for GPT-5 nano and Ministral 3 (14B Reasoning 2512)?

GPT-5 nano supports 400K tokens and Ministral 3 (14B Reasoning 2512) supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-5 nano and Ministral 3 (14B Reasoning 2512)?

Key differences include LLM Stats Score (19.1 vs 20.3), context window (400K vs 262K), input pricing ($0.05 vs $0.20/M), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-5 nano and Ministral 3 (14B Reasoning 2512)?

GPT-5 nano is developed by OpenAI and Ministral 3 (14B Reasoning 2512) is developed by Mistral AI.

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