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DeepSeek-V4.1-Flash-1017 vs MiniMax M2.7

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 35.4. DeepSeek-V4.1-Flash-1017 and MiniMax M2.7 cost the same.

DeepSeek · MiniMax · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.2 to 35.4, 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.

DeepSeek-V4.1-Flash-1017 also accepts a larger context window (1,048,576 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 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 process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Oct 2026

Choose MiniMax M2.7

  • you want predictable pricing at $0.30/M input and $1.20/M output

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
MiniMax M2.7
MiniMax
Core performance indexes
LLM Stats Score
51.2
#15
35.4
#105
Reasoning
48.8
#18
34.5
#106
Coding
39.3
#14
27.1
#77
Agents
38.7
#8
15.6
#105
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.30 / M
$0.30 / M
Output price
$1.20 / M
$1.20 / M
Context window
1,048,576
196,608

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash-1017
MiniMax M2.7
Tool use
31.3#6
15.2#108
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 11 for MiniMax M2.7

1 shared

DeepSeek-V4.1-Flash-1017 outperforms in 1 benchmarks (NL2Repo), while MiniMax M2.7 is better at 0 benchmarks.

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

Thu Oct 22 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

For input processing, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) costs the same as MiniMax M2.7 ($0.30/1M tokens).

For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) costs the same as MiniMax M2.7 ($1.20/1M tokens).

In conclusion, DeepSeek-V4.1-Flash-1017 and MiniMax M2.7 cost the same.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Thu Oct 22 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash-1017
Input tokens$0.30
Output tokens$1.20
Best providerDeepSeek
MiniMax
MiniMax M2.7
Input tokens$0.30
Output tokens$1.20
Best providerFireworks
Notice missing or incorrect data?

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to MiniMax M2.7's 196,608 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while MiniMax M2.7 is limited to 196,608 tokens.

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
MiniMax
MiniMax M2.7
Input196,608 tokens
Output196,608 tokens
Thu Oct 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash-1017 supports multimodal inputs, whereas MiniMax M2.7 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 M2.7

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 M2.7

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while MiniMax M2.7 was released on 2026-03-18.

DeepSeek-V4.1-Flash-1017 is 7 months newer than MiniMax M2.7.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

2 days ago

7mo newer
MiniMax M2.7

Mar 18, 2026

7 months 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

Provider Availability

DeepSeek-V4.1-Flash-1017 is available from DeepSeek. MiniMax M2.7 is available from Fireworks, MiniMax, Novita, DeepInfra.

DeepSeek-V4.1-Flash-1017

deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

MiniMax M2.7

fireworks logo
Fireworks
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
minimax logo
MiniMax
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.38/1MOutput Price:Output: $1.70/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and MiniMax M2.7 side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
MiniMax M2.7
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs MiniMax M2.7.

Which is better, DeepSeek-V4.1-Flash-1017 or MiniMax M2.7?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 35.4. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and MiniMax M2.7 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 M2.7 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 M2.7 scores SWE-bench Multilingual: 76.5%, MLE-Bench Lite: 66.6%, MM-ClawBench: 62.7%, Terminal-Bench 2.0: 57.0%, SWE-Bench Pro: 56.2%.

Is DeepSeek-V4.1-Flash-1017 cheaper than MiniMax M2.7?

Both models cost $0.30 per million input tokens.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and MiniMax M2.7?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and MiniMax M2.7 supports 197K 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 M2.7?

Key differences include LLM Stats Score (51.2 vs 35.4), context window (1.0M vs 197K), multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and MiniMax M2.7?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and MiniMax M2.7 is developed by MiniMax.

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