GPT-6 Astra vs MiniMax M2
GPT-6 Astra leads the LLM Stats Score 59.6 to 26.9. MiniMax M2 is 38.1x cheaper per token.
OpenAI · MiniMax · Updated for 2026
Which is better?
GPT-6 Astra leads the overall LLM Stats Score 59.6 to 26.9, ranking #1 overall.
In the 2 individual benchmarks reported for both models, GPT-6 Astra wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, MiniMax M2 is roughly 38.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6 Astra also accepts a larger context window (1,050,000 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-6 Astra
- overall performance matters — it scores 59.6 and ranks #1 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose MiniMax M2
- cost matters — it's about 38.1x cheaper per token
- 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
22 reported for GPT-6 Astra · 16 for MiniMax M2
GPT-6 Astra outperforms in 2 benchmarks (BrowseComp, GPQA), while MiniMax M2 is better at 0 benchmarks.
GPT-6 Astra 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-6 Astra ($10.00/1M tokens) is 33.3x more expensive than MiniMax M2 ($0.30/1M tokens).
For output processing, GPT-6 Astra ($50.00/1M tokens) is 41.7x more expensive than MiniMax M2 ($1.20/1M tokens).
In conclusion, GPT-6 Astra is more expensive than MiniMax M2.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-6 Astra accepts 1,050,000 input tokens compared to MiniMax M2's 1,000,000 tokens. MiniMax M2 can generate longer responses up to 1,000,000 tokens, while GPT-6 Astra is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-6 Astra supports multimodal inputs, whereas MiniMax M2 does not.
GPT-6 Astra can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-6 Astra
MiniMax M2
License
Usage and distribution terms
GPT-6 Astra is licensed under a proprietary license, while MiniMax M2 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-6 Astra was released on 2026-09-04, while MiniMax M2 was released on 2025-10-27.
GPT-6 Astra is 10 months newer than MiniMax M2.
Sep 4, 2026
2 weeks ago
10mo newerOct 27, 2025
10 months ago
Knowledge Cutoff
When training data ends
GPT-6 Astra has a documented knowledge cutoff of 2026-04-30, while MiniMax M2's cutoff date is not specified.
We can confirm GPT-6 Astra's training data extends to 2026-04-30, but cannot make a direct comparison without MiniMax M2's cutoff date.
Apr 2026
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Provider Availability
GPT-6 Astra is available from OpenAI. MiniMax M2 is available from MiniMax, Novita.
GPT-6 Astra
MiniMax M2
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Astra and MiniMax M2 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Astra vs MiniMax M2.