DeepSeek-R1-0528 vs MAI-Thinking-1
MAI-Thinking-1 leads the LLM Stats Score 33.0 to 24.1.
DeepSeek · Microsoft · Updated for 2026
Which is better?
MAI-Thinking-1 leads the overall LLM Stats Score 33.0 to 24.1, ranking #101 overall.
In the 4 individual benchmarks reported for both models, MAI-Thinking-1 wins 4; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-R1-0528
- you need open weights you can self-host or fine-tune
Choose MAI-Thinking-1
- overall performance matters — it scores 33.0 and ranks #101 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 4 exact shared results
- you want the most recent training data — it shipped Jun 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
16 reported for DeepSeek-R1-0528 · 23 for MAI-Thinking-1
DeepSeek-R1-0528 outperforms in 0 benchmarks, while MAI-Thinking-1 is better at 3 benchmarks (AIME 2025, GPQA, SWE-Bench Verified).
MAI-Thinking-1 shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
MAI-Thinking-1 has 329.0B more parameters than DeepSeek-R1-0528, making it 49.0% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-R1-0528 specifies input context (163,840 tokens). Only DeepSeek-R1-0528 specifies output context (163,840 tokens).
License
Usage and distribution terms
DeepSeek-R1-0528 is licensed under MIT, while MAI-Thinking-1 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-R1-0528 was released on 2025-05-28, while MAI-Thinking-1 was released on 2026-06-02.
MAI-Thinking-1 is 12 months newer than DeepSeek-R1-0528.
May 28, 2025
1.3 years ago
Jun 2, 2026
3 months ago
1.0yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-R1-0528 and MAI-Thinking-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-R1-0528 vs MAI-Thinking-1.