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DeepSeek-V4.1-Flash vs Ministral 3 (14B Reasoning 2512)

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 20.6. Ministral 3 (14B Reasoning 2512) is 1.6x cheaper per token.

DeepSeek · Mistral AI · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 20.6, ranking #12 overall.

In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 1; this is a narrower head-to-head signal than the composite indexes.

On price, Ministral 3 (14B Reasoning 2512) is roughly 1.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V4.1-Flash also accepts a larger context window (1,040,000 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

  • overall performance matters — it scores 51.8 and ranks #12 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 1,040,000 token context window
  • you want the most recent training data — it shipped Sep 2026

Choose Ministral 3 (14B Reasoning 2512)

  • cost matters — it's about 1.6x cheaper per token

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash
DeepSeek
Ministral 3 (14B Reasoning 2512)
Mistral AI
Core performance indexes
LLM Stats Score
51.8
#12
20.6
#192
Reasoning
48.9
#17
20.6
#183
Coding
44.4
#5
11.1
#159
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.22 / M
$0.20 / M
Output price
$0.66 / M
$0.20 / M
Context window
1,040,000
262,100

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash
Ministral 3 (14B Reasoning 2512)
Math
35.2#43
21.1#151
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 4 for Ministral 3 (14B Reasoning 2512)

1 shared

DeepSeek-V4.1-Flash outperforms in 1 benchmarks (GPQA), while Ministral 3 (14B Reasoning 2512) is better at 0 benchmarks.

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

Fri Sep 11 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Ministral 3 (14B Reasoning 2512) costs less

For input processing, DeepSeek-V4.1-Flash ($0.22/1M tokens) is 1.1x more expensive than Ministral 3 (14B Reasoning 2512) ($0.20/1M tokens).

For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 3.3x more expensive than Ministral 3 (14B Reasoning 2512) ($0.20/1M tokens).

In conclusion, DeepSeek-V4.1-Flash is more expensive than Ministral 3 (14B Reasoning 2512).*

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

Lowest available price from all providers
Fri Sep 11 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash
Input tokens$0.22
Output tokens$0.66
Best providerFireworks
Mistral AI
Ministral 3 (14B Reasoning 2512)
Input tokens$0.20
Output tokens$0.20
Best providerMistral
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

749.2B diff

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

DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
Mistral AI
Ministral 3 (14B Reasoning 2512)
14.0Bparameters
763.2B
DeepSeek-V4.1-Flash
14.0B
Ministral 3 (14B Reasoning 2512)

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash accepts 1,040,000 input tokens compared to Ministral 3 (14B Reasoning 2512)'s 262,100 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while Ministral 3 (14B Reasoning 2512) is limited to 262,100 tokens.

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
Mistral AI
Ministral 3 (14B Reasoning 2512)
Input262,100 tokens
Output262,100 tokens
Fri Sep 11 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash and Ministral 3 (14B Reasoning 2512) support multimodal inputs.

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

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

Ministral 3 (14B Reasoning 2512)

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash is licensed under MIT, while Ministral 3 (14B Reasoning 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

MIT

Open weights

Ministral 3 (14B Reasoning 2512)

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while Ministral 3 (14B Reasoning 2512) was released on 2025-12-04.

DeepSeek-V4.1-Flash is 9 months newer than Ministral 3 (14B Reasoning 2512).

DeepSeek-V4.1-Flash

Sep 10, 2026

-1 days ago

9mo newer
Ministral 3 (14B Reasoning 2512)

Dec 4, 2025

9 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 is available from Fireworks, DeepInfra, DeepSeek, Novita. Ministral 3 (14B Reasoning 2512) is available from Mistral AI.

DeepSeek-V4.1-Flash

fireworks logo
Fireworks
Input Price:Input: $0.22/1MOutput Price:Output: $0.66/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
deepseek logo
DeepSeek
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

Ministral 3 (14B Reasoning 2512)

mistral logo
Mistral
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

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

DeepSeek-V4.1-Flash
✓ Preferred
Ministral 3 (14B Reasoning 2512)
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash vs Ministral 3 (14B Reasoning 2512).

Which is better, DeepSeek-V4.1-Flash or Ministral 3 (14B Reasoning 2512)?

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 20.6. DeepSeek-V4.1-Flash is made by DeepSeek and Ministral 3 (14B Reasoning 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 compare to Ministral 3 (14B Reasoning 2512) in benchmarks?

DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%. Ministral 3 (14B Reasoning 2512) scores AIME 2024: 89.8%, AIME 2025: 85.0%, GPQA: 71.2%, LiveCodeBench: 64.6%.

Is DeepSeek-V4.1-Flash cheaper than Ministral 3 (14B Reasoning 2512)?

Ministral 3 (14B Reasoning 2512) is 1.1x cheaper for input tokens. DeepSeek-V4.1-Flash costs $0.22/M input and $0.66/M output via fireworks. Ministral 3 (14B Reasoning 2512) costs $0.20/M input and $0.20/M output via mistral.

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

DeepSeek-V4.1-Flash supports 1.0M tokens and Ministral 3 (14B Reasoning 2512) supports 262K 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 and Ministral 3 (14B Reasoning 2512)?

Key differences include LLM Stats Score (51.8 vs 20.6), context window (1.0M vs 262K), input pricing ($0.22 vs $0.20/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash and Ministral 3 (14B Reasoning 2512)?

DeepSeek-V4.1-Flash is developed by DeepSeek and Ministral 3 (14B Reasoning 2512) is developed by Mistral AI.

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