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DeepSeek-V4.1-Flash-1017 vs MiniStral 3 (14B Instruct 2512)

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 9.8.

DeepSeek · Mistral AI · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to 9.8, ranking #15 overall.

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 51.0 and ranks #15 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Oct 2026

Choose MiniStral 3 (14B Instruct 2512)

  • you are already invested in the Mistral AI ecosystem

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
MiniStral 3 (14B Instruct 2512)
Mistral AI
Core performance indexes
LLM Stats Score
51.0
#15
9.8
#289
Reasoning
48.6
#18
11.6
#272
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
— / M
Output price
$1.20 / M
— / M
Context window
1,048,576
—

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 4 for MiniStral 3 (14B Instruct 2512)

No common benchmarks found

DeepSeek-V4.1-Flash-1017 and MiniStral 3 (14B Instruct 2512)don'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

Model Size

Parameter count comparison

749.2B diff

DeepSeek-V4.1-Flash-1017 has 749.2B more parameters than MiniStral 3 (14B Instruct 2512), making it 5351.5% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
Mistral AI
MiniStral 3 (14B Instruct 2512)
14.0Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
14.0B
MiniStral 3 (14B Instruct 2512)

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
Mistral AI
MiniStral 3 (14B Instruct 2512)
Input- tokens
Output- tokens
Tue Oct 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash-1017 and MiniStral 3 (14B Instruct 2512) support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek-V4.1-Flash-1017

Text
Images
Audio
Video

MiniStral 3 (14B Instruct 2512)

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 is licensed under MIT, while MiniStral 3 (14B Instruct 2512) uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V4.1-Flash-1017

MIT

Open weights

MiniStral 3 (14B Instruct 2512)

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while MiniStral 3 (14B Instruct 2512) was released on 2025-12-04.

DeepSeek-V4.1-Flash-1017 is 11 months newer than MiniStral 3 (14B Instruct 2512).

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

2 days ago

10mo newer
MiniStral 3 (14B Instruct 2512)

Dec 4, 2025

10 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

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and MiniStral 3 (14B Instruct 2512) side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
MiniStral 3 (14B Instruct 2512)
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs MiniStral 3 (14B Instruct 2512).

Which is better, DeepSeek-V4.1-Flash-1017 or MiniStral 3 (14B Instruct 2512)?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 9.8. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and MiniStral 3 (14B Instruct 2512) is made by Mistral AI. 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 MiniStral 3 (14B Instruct 2512) 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%. MiniStral 3 (14B Instruct 2512) scores MATH: 90.4%, Wild Bench: 68.5%, Arena Hard: 55.1%, MM-MT-Bench: 8.5%.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and MiniStral 3 (14B Instruct 2512)?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and MiniStral 3 (14B Instruct 2512) 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 MiniStral 3 (14B Instruct 2512)?

Key differences include LLM Stats Score (51.0 vs 9.8), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and MiniStral 3 (14B Instruct 2512)?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and MiniStral 3 (14B Instruct 2512) is developed by Mistral AI.

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