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LongCat-2.5 vs Ministral 3 (14B Base 2512)

LongCat-2.5 leads the LLM Stats Score 49.8 to 3.1.

Meituan · Mistral AI · Updated for 2026

Which is better?

LongCat-2.5 leads the overall LLM Stats Score 49.8 to 3.1, ranking #21 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose LongCat-2.5

  • overall performance matters — it scores 49.8 and ranks #21 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Nov 2026

Choose Ministral 3 (14B Base 2512)

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

LongCat-2.5
Meituan
Ministral 3 (14B Base 2512)
Mistral AI
Core performance indexes
LLM Stats Score
49.8
#21
3.1
#350
Reasoning
48.1
#22
2.9
#342
Cost, coverage & limits
Benchmark wins
—
—
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

1 shared
Index
LongCat-2.5
Ministral 3 (14B Base 2512)
Math
37.1#38
8.7#281
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

23 reported for LongCat-2.5 · 6 for Ministral 3 (14B Base 2512)

No common benchmarks found

LongCat-2.5 and Ministral 3 (14B Base 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

1586.0B diff

LongCat-2.5 has 1586.0B more parameters than Ministral 3 (14B Base 2512), making it 11328.6% larger.

Meituan
LongCat-2.5
1.6Tparameters
Mistral AI
Ministral 3 (14B Base 2512)
14.0Bparameters
1600.0B
LongCat-2.5
14.0B
Ministral 3 (14B Base 2512)

Context Window

Maximum input and output token capacity

Only LongCat-2.5 specifies input context (1,048,576 tokens). Only LongCat-2.5 specifies output context (131,072 tokens).

Meituan
LongCat-2.5
Input1,048,576 tokens
Output131,072 tokens
Mistral AI
Ministral 3 (14B Base 2512)
Input- tokens
Output- tokens
Mon Nov 09 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both LongCat-2.5 and Ministral 3 (14B Base 2512) support multimodal inputs.

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

LongCat-2.5

Text
Images
Audio
Video

Ministral 3 (14B Base 2512)

Text
Images
Audio
Video

Release Timeline

When each model was launched

LongCat-2.5 was released on 2026-11-01, while Ministral 3 (14B Base 2512) was released on 2025-12-04.

LongCat-2.5 is 11 months newer than Ministral 3 (14B Base 2512).

LongCat-2.5

Nov 1, 2026

1 weeks ago

11mo newer
Ministral 3 (14B Base 2512)

Dec 4, 2025

11 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 LongCat-2.5 and Ministral 3 (14B Base 2512) side-by-side, then vote on the output you prefer.

LongCat-2.5
✓ Preferred
Ministral 3 (14B Base 2512)
Open in Playground

FAQ

Common questions about LongCat-2.5 vs Ministral 3 (14B Base 2512).

Which is better, LongCat-2.5 or Ministral 3 (14B Base 2512)?

LongCat-2.5 leads the LLM Stats Score 49.8 to 3.1. LongCat-2.5 is made by Meituan and Ministral 3 (14B Base 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 LongCat-2.5 compare to Ministral 3 (14B Base 2512) in benchmarks?

LongCat-2.5 scores MathVision: 96.5%, BrowseComp: 91.9%, CharXiv-R: 90.2%, Terminal-Bench 2.1: 88.4%, Video-MME: 85.2%. Ministral 3 (14B Base 2512) scores MMLU-Redux: 82.0%, MMLU: 79.4%, TriviaQA: 74.9%, Multilingual MMLU: 74.2%, MATH (CoT): 67.6%.

What are the context window sizes for LongCat-2.5 and Ministral 3 (14B Base 2512)?

LongCat-2.5 supports 1.0M tokens and Ministral 3 (14B Base 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 LongCat-2.5 and Ministral 3 (14B Base 2512)?

Key differences include LLM Stats Score (49.8 vs 3.1), licensing (Unknown vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes LongCat-2.5 and Ministral 3 (14B Base 2512)?

LongCat-2.5 is developed by Meituan and Ministral 3 (14B Base 2512) is developed by Mistral AI.

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