GPT-5 mini vs MiniMax M1 80K
GPT-5 mini leads the LLM Stats Score 27.3 to 21.4. GPT-5 mini is 1.4x cheaper per token.
OpenAI · MiniMax · Updated for 2026
Which is better?
GPT-5 mini leads the overall LLM Stats Score 27.3 to 21.4, ranking #148 overall.
In the 3 individual benchmarks reported for both models, GPT-5 mini wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, GPT-5 mini is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiniMax M1 80K also accepts a larger context window (1,000,000 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 mini
- overall performance matters — it scores 27.3 and ranks #148 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 3 exact shared results
- cost matters — it's about 1.4x cheaper per token
- you want the most recent training data — it shipped Aug 2025
Choose MiniMax M1 80K
- you process long inputs — it offers a 1,000,000 token context window
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
5 reported for GPT-5 mini · 16 for MiniMax M1 80K
GPT-5 mini outperforms in 3 benchmarks (AIME 2025, GPQA, Humanity's Last Exam), while MiniMax M1 80K is better at 0 benchmarks.
GPT-5 mini significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5 mini ($0.25/1M tokens) is 2.2x cheaper than MiniMax M1 80K ($0.55/1M tokens).
For output processing, GPT-5 mini ($2.00/1M tokens) is 1.1x cheaper than MiniMax M1 80K ($2.20/1M tokens).
In conclusion, MiniMax M1 80K is more expensive than GPT-5 mini.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
MiniMax M1 80K accepts 1,000,000 input tokens compared to GPT-5 mini's 400,000 tokens. GPT-5 mini can generate longer responses up to 128,000 tokens, while MiniMax M1 80K is limited to 40,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-5 mini supports multimodal inputs, whereas MiniMax M1 80K does not.
GPT-5 mini can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-5 mini
MiniMax M1 80K
License
Usage and distribution terms
GPT-5 mini is licensed under a proprietary license, while MiniMax M1 80K uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
GPT-5 mini was released on 2025-08-07, while MiniMax M1 80K was released on 2025-06-16.
GPT-5 mini is 2 months newer than MiniMax M1 80K.
Aug 7, 2025
1.1 years ago
1mo newerJun 16, 2025
1.3 years ago
Knowledge Cutoff
When training data ends
GPT-5 mini has a documented knowledge cutoff of 2024-05-30, while MiniMax M1 80K's cutoff date is not specified.
We can confirm GPT-5 mini's training data extends to 2024-05-30, but cannot make a direct comparison without MiniMax M1 80K's cutoff date.
May 2024
—
Provider Availability
GPT-5 mini is available from OpenAI. MiniMax M1 80K is available from Novita.
GPT-5 mini
MiniMax M1 80K
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5 mini and MiniMax M1 80K side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5 mini vs MiniMax M1 80K.