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DeepSeek-V4.1-Flash-1017 vs MiniMax M2.5

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 36.6. DeepSeek-V4.1-Flash-1017 and MiniMax M2.5 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 36.6, ranking #15 overall.

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 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 M2.5

  • 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 M2.5
MiniMax
Core performance indexes
LLM Stats Score
51.2
#15
36.6
#91
Reasoning
48.8
#18
36.7
#91
Coding
39.3
#14
26.5
#81
Agents
38.7
#8
17.1
#98
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
$0.30 / M
Output price
$1.20 / M
$1.20 / M
Context window
1,048,576
1,000,000

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 8 for MiniMax M2.5

No common benchmarks found

DeepSeek-V4.1-Flash-1017 and MiniMax M2.5don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

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 M2.5 ($0.30/1M tokens).

For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) costs the same as MiniMax M2.5 ($1.20/1M tokens).

In conclusion, DeepSeek-V4.1-Flash-1017 and MiniMax M2.5 cost the same.*

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

Lowest available price from all providers
Fri Oct 23 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash-1017
Input tokens$0.30
Output tokens$1.20
Best providerDeepSeek
MiniMax
MiniMax M2.5
Input tokens$0.30
Output tokens$1.20
Best providerMiniMax
Notice missing or incorrect data?

Model Size

Parameter count comparison

533.2B diff

DeepSeek-V4.1-Flash-1017 has 533.2B more parameters than MiniMax M2.5, making it 231.8% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
MiniMax
MiniMax M2.5
230.0Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
230.0B
MiniMax M2.5

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to MiniMax M2.5's 1,000,000 tokens. MiniMax M2.5 can generate longer responses up to 1,000,000 tokens, while DeepSeek-V4.1-Flash-1017 is limited to 393,216 tokens.

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
MiniMax
MiniMax M2.5
Input1,000,000 tokens
Output1,000,000 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 M2.5 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 M2.5

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 M2.5

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while MiniMax M2.5 was released on 2026-02-12.

DeepSeek-V4.1-Flash-1017 is 8 months newer than MiniMax M2.5.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

2 days ago

8mo newer
MiniMax M2.5

Feb 12, 2026

8 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 M2.5 is available from MiniMax.

DeepSeek-V4.1-Flash-1017

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

MiniMax M2.5

minimax logo
MiniMax
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
* 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 M2.5 side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
MiniMax M2.5
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs MiniMax M2.5.

Which is better, DeepSeek-V4.1-Flash-1017 or MiniMax M2.5?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 36.6. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and MiniMax M2.5 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 M2.5 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 M2.5 scores SWE-Bench Verified: 80.2%, BFCL_v3_MultiTurn: 76.8%, BrowseComp: 76.3%, MEWC: 74.4%, GDPval-MM: 59.0%.

Is DeepSeek-V4.1-Flash-1017 cheaper than MiniMax M2.5?

Both models cost $0.30 per million input tokens.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and MiniMax M2.5?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and MiniMax M2.5 supports 1.0M 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 M2.5?

Key differences include LLM Stats Score (51.2 vs 36.6), context window (1.0M vs 1.0M), multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and MiniMax M2.5?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and MiniMax M2.5 is developed by MiniMax.

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