GPT-4.1 nano vs MiniMax M3.1 Flash
MiniMax M3.1 Flash leads the LLM Stats Score 48.5 to 1.3. GPT-4.1 nano is 1.5x cheaper per token.
OpenAI · MiniMax · Updated for 2026
Which is better?
MiniMax M3.1 Flash leads the overall LLM Stats Score 48.5 to 1.3, ranking #29 overall.
In the 1 individual benchmarks reported for both models, MiniMax M3.1 Flash wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, GPT-4.1 nano is roughly 1.5x 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 LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-4.1 nano
- cost matters — it's about 1.5x cheaper per token
- you process long inputs — it offers a 1,047,576 token context window
Choose MiniMax M3.1 Flash
- overall performance matters — it scores 48.5 and ranks #29 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
24 reported for GPT-4.1 nano · 14 for MiniMax M3.1 Flash
GPT-4.1 nano outperforms in 0 benchmarks, while MiniMax M3.1 Flash is better at 1 benchmark (CharXiv-R).
MiniMax M3.1 Flash 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-4.1 nano ($0.10/1M tokens) is 1.5x cheaper than MiniMax M3.1 Flash ($0.15/1M tokens).
For output processing, GPT-4.1 nano ($0.40/1M tokens) is 1.5x cheaper than MiniMax M3.1 Flash ($0.60/1M tokens).
In conclusion, MiniMax M3.1 Flash is more expensive than GPT-4.1 nano.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-4.1 nano accepts 1,047,576 input tokens compared to MiniMax M3.1 Flash's 1,000,000 tokens. MiniMax M3.1 Flash can generate longer responses up to 524,288 tokens, while GPT-4.1 nano is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-4.1 nano and MiniMax M3.1 Flash support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-4.1 nano
MiniMax M3.1 Flash
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
GPT-4.1 nano was released on 2025-04-14, while MiniMax M3.1 Flash was released on 2026-10-19.
MiniMax M3.1 Flash is 18 months newer than GPT-4.1 nano.
Apr 14, 2025
1.5 years ago
Oct 19, 2026
0 days ago
1.5yr newerKnowledge Cutoff
When training data ends
GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while MiniMax M3.1 Flash'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 MiniMax M3.1 Flash's cutoff date.
May 2024
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Provider Availability
GPT-4.1 nano is available from OpenAI. MiniMax M3.1 Flash is available from MiniMax.
GPT-4.1 nano
MiniMax M3.1 Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4.1 nano and MiniMax M3.1 Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4.1 nano vs MiniMax M3.1 Flash.