Model Comparison

DeepSeek-V4-Flash-Max vs MAI-Thinking-1Which is better in 2026?

DeepSeek-V4-Flash-Max significantly outperforms across most benchmarks.

Verdict: DeepSeek-V4-Flash-Max vs MAI-Thinking-1 — which is better?

DeepSeek-V4-Flash-Max (by DeepSeek) and MAI-Thinking-1 (by Microsoft) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

DeepSeek-V4-Flash-Max outperforms in 5 benchmarks (GPQA, HMMT Feb 26, MMLU-Pro, SWE-Bench Verified, Terminal-Bench 2.0), while MAI-Thinking-1 is better at 1 benchmark (SWE-Bench Pro). DeepSeek-V4-Flash-Max significantly outperforms across most benchmarks.

Choose DeepSeek-V4-Flash-Max if…

  • you want the strongest raw capability — it leads on 5 of 6 shared benchmarks
  • you need open weights you can self-host or fine-tune

Choose MAI-Thinking-1 if…

  • you want the most recent training data — it shipped Jun 2026

Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

DeepSeek-V4-Flash-Max outperforms in 5 benchmarks (GPQA, HMMT Feb 26, MMLU-Pro, SWE-Bench Verified, Terminal-Bench 2.0), while MAI-Thinking-1 is better at 1 benchmark (SWE-Bench Pro).

DeepSeek-V4-Flash-Max significantly outperforms across most benchmarks.

Fri Jul 17 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

716.0B diff

MAI-Thinking-1 has 716.0B more parameters than DeepSeek-V4-Flash-Max, making it 252.1% larger.

DeepSeek
DeepSeek-V4-Flash-Max
284.0Bparameters
Microsoft
MAI-Thinking-1
1.0Tparameters
284.0B
DeepSeek-V4-Flash-Max
1000.0B
MAI-Thinking-1

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Flash-Max specifies input context (1,048,576 tokens). Only DeepSeek-V4-Flash-Max specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V4-Flash-Max
Input1,048,576 tokens
Output65,536 tokens
Microsoft
MAI-Thinking-1
Input- tokens
Output- tokens
Fri Jul 17 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V4-Flash-Max 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.

DeepSeek-V4-Flash-Max

MIT

Open weights

MAI-Thinking-1

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V4-Flash-Max was released on 2026-04-23, while MAI-Thinking-1 was released on 2026-06-02.

MAI-Thinking-1 is 1 month newer than DeepSeek-V4-Flash-Max.

DeepSeek-V4-Flash-Max

Apr 23, 2026

2 months ago

MAI-Thinking-1

Jun 2, 2026

1 months ago

1mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (1,048,576 tokens)
Has open weights
Higher GPQA score (88.1% vs 84.2%)
Higher HMMT Feb 26 score (94.8% vs 84.9%)
Higher MMLU-Pro score (86.2% vs 85.0%)
Higher SWE-Bench Verified score (79.0% vs 73.5%)
Higher Terminal-Bench 2.0 score (56.9% vs 46.0%)
Microsoft
Higher SWE-Bench Pro score (52.8% vs 52.6%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek-V4-Flash-Max and MAI-Thinking-1 side-by-side, then vote on the output you prefer.

DeepSeek-V4-Flash-Max
✓ Preferred
MAI-Thinking-1
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V4-Flash-Max
Microsoft
MAI-Thinking-1

FAQ

Common questions about DeepSeek-V4-Flash-Max vs MAI-Thinking-1.

Which is better, DeepSeek-V4-Flash-Max or MAI-Thinking-1?

DeepSeek-V4-Flash-Max significantly outperforms across most benchmarks. DeepSeek-V4-Flash-Max is made by DeepSeek and MAI-Thinking-1 is made by Microsoft. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V4-Flash-Max compare to MAI-Thinking-1 in benchmarks?

DeepSeek-V4-Flash-Max scores CodeForces: 100.0%, HMMT Feb 26: 94.8%, LiveCodeBench: 91.6%, IMO-AnswerBench: 88.4%, GPQA: 88.1%. MAI-Thinking-1 scores LongFact: 98.0%, AIME 2025: 97.0%, AIME 2026: 94.5%, GraphWalks: 90.0%, AIR-Bench: 88.0%.

What are the context window sizes for DeepSeek-V4-Flash-Max and MAI-Thinking-1?

DeepSeek-V4-Flash-Max supports 1.0M tokens and MAI-Thinking-1 supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V4-Flash-Max and MAI-Thinking-1?

Key differences include licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Flash-Max and MAI-Thinking-1?

DeepSeek-V4-Flash-Max is developed by DeepSeek and MAI-Thinking-1 is developed by Microsoft.

Related comparisons