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DeepSeek-V4.1-Flash-1017 vs MiniMax M1 40K

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 20.0.

DeepSeek · MiniMax · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.2 to 20.0, ranking #15 overall.

In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash-1017 wins 1; 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-V4.1-Flash-1017

  • overall performance matters — it scores 51.2 and ranks #15 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

Choose MiniMax M1 40K

  • you are already invested in the MiniMax ecosystem

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
MiniMax M1 40K
MiniMax
Core performance indexes
LLM Stats Score
51.2
#15
20.0
#220
Reasoning
48.8
#18
20.2
#210
Coding
39.3
#14
7.7
#205
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.30 / M
— / M
Output price
$1.20 / M
— / M
Context window
1,048,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V4.1-Flash-1017
MiniMax M1 40K
Math
31.8#69
17.9#200
Tool use
31.3#6
12.7#120
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 16 for MiniMax M1 40K

1 shared

DeepSeek-V4.1-Flash-1017 outperforms in 1 benchmarks (Humanity's Last Exam), while MiniMax M1 40K is better at 0 benchmarks.

DeepSeek-V4.1-Flash-1017 significantly outperforms across most benchmarks.

Fri Oct 23 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

307.2B diff

DeepSeek-V4.1-Flash-1017 has 307.2B more parameters than MiniMax M1 40K, making it 67.4% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
MiniMax
MiniMax M1 40K
456.0Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
456.0B
MiniMax M1 40K

Context Window

Maximum input and output token capacity

Only DeepSeek-V4.1-Flash-1017 specifies input context (1,048,576 tokens). Only DeepSeek-V4.1-Flash-1017 specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
MiniMax
MiniMax M1 40K
Input- tokens
Output- tokens
Fri Oct 23 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash-1017 supports multimodal inputs, whereas MiniMax M1 40K does not.

DeepSeek-V4.1-Flash-1017 can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4.1-Flash-1017

Text
Images
Audio
Video

MiniMax M1 40K

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

DeepSeek-V4.1-Flash-1017

MIT

Open weights

MiniMax M1 40K

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while MiniMax M1 40K was released on 2025-06-16.

DeepSeek-V4.1-Flash-1017 is 16 months newer than MiniMax M1 40K.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

2 days ago

1.3yr newer
MiniMax M1 40K

Jun 16, 2025

1.3 years ago

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?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and MiniMax M1 40K side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
MiniMax M1 40K
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs MiniMax M1 40K.

Which is better, DeepSeek-V4.1-Flash-1017 or MiniMax M1 40K?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 20.0. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and MiniMax M1 40K is made by MiniMax. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V4.1-Flash-1017 compare to MiniMax M1 40K in benchmarks?

DeepSeek-V4.1-Flash-1017 scores BabyVision: 92.5%, Chartography: 83.0%, DeepSWE 1.1: 77.0%, NL2Repo: 68.2%, AutomationBench: 60.5%. MiniMax M1 40K scores MATH-500: 96.0%, AIME 2024: 83.3%, MMLU-Pro: 80.6%, ZebraLogic: 80.1%, OpenAI-MRCR: 2 needle 128k: 76.1%.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and MiniMax M1 40K?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and MiniMax M1 40K 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-V4.1-Flash-1017 and MiniMax M1 40K?

Key differences include LLM Stats Score (51.2 vs 20.0), multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and MiniMax M1 40K?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and MiniMax M1 40K is developed by MiniMax.

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