The AI arena is free today

Open Superagent

Ling 3.0 Flash Fin vs Ministral 3 (14B Base 2512)

Ling 3.0 Flash Fin leads the LLM Stats Score 43.0 to 3.6.

InclusionAI · Mistral AI · Updated for 2026

Which is better?

Ling 3.0 Flash Fin leads the overall LLM Stats Score 43.0 to 3.6, ranking #44 overall.

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

Choose Ling 3.0 Flash Fin

  • overall performance matters — it scores 43.0 and ranks #44 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 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.

Ling 3.0 Flash Fin
InclusionAI
Ministral 3 (14B Base 2512)
Mistral AI
Core performance indexes
LLM Stats Score
43.0
#44
3.6
#308
Reasoning
44.2
#35
3.5
#300
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.06 / M
— / M
Output price
$0.18 / M
— / M
Context window
262,144
—

Individual benchmarks

6 reported for Ling 3.0 Flash Fin · 6 for Ministral 3 (14B Base 2512)

No common benchmarks found

Ling 3.0 Flash Fin 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

110.0B diff

Ling 3.0 Flash Fin has 110.0B more parameters than Ministral 3 (14B Base 2512), making it 785.7% larger.

InclusionAI
Ling 3.0 Flash Fin
124.0Bparameters
Mistral AI
Ministral 3 (14B Base 2512)
14.0Bparameters
124.0B
Ling 3.0 Flash Fin
14.0B
Ministral 3 (14B Base 2512)

Context Window

Maximum input and output token capacity

Only Ling 3.0 Flash Fin specifies input context (262,144 tokens). Only Ling 3.0 Flash Fin specifies output context (262,144 tokens).

InclusionAI
Ling 3.0 Flash Fin
Input262,144 tokens
Output262,144 tokens
Mistral AI
Ministral 3 (14B Base 2512)
Input- tokens
Output- tokens
Tue Sep 15 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Ministral 3 (14B Base 2512) supports multimodal inputs, whereas Ling 3.0 Flash Fin does not.

Ministral 3 (14B Base 2512) can handle both text and other forms of data like images, making it suitable for multimodal applications.

Ling 3.0 Flash Fin

Text
Images
Audio
Video

Ministral 3 (14B Base 2512)

Text
Images
Audio
Video

Release Timeline

When each model was launched

Ling 3.0 Flash Fin was released on 2026-09-03, while Ministral 3 (14B Base 2512) was released on 2025-12-04.

Ling 3.0 Flash Fin is 9 months newer than Ministral 3 (14B Base 2512).

Ling 3.0 Flash Fin

Sep 3, 2026

1 weeks ago

9mo newer
Ministral 3 (14B Base 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Ling 3.0 Flash Fin and Ministral 3 (14B Base 2512) side-by-side, then vote on the output you prefer.

Ling 3.0 Flash Fin
✓ Preferred
Ministral 3 (14B Base 2512)
Open in Playground

FAQ

Common questions about Ling 3.0 Flash Fin vs Ministral 3 (14B Base 2512).

Which is better, Ling 3.0 Flash Fin or Ministral 3 (14B Base 2512)?

Ling 3.0 Flash Fin leads the LLM Stats Score 43.0 to 3.6. Ling 3.0 Flash Fin is made by InclusionAI 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 Ling 3.0 Flash Fin compare to Ministral 3 (14B Base 2512) in benchmarks?

Ling 3.0 Flash Fin scores SpreadSheetBench-v1: 86.5%, Finance Agent v1.1: 69.2%, Finance Agent v2: 59.8%, Tau3 Banking: 41.0%, APEX-Agents: 29.2%. 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 Ling 3.0 Flash Fin and Ministral 3 (14B Base 2512)?

Ling 3.0 Flash Fin supports 262K 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 Ling 3.0 Flash Fin and Ministral 3 (14B Base 2512)?

Key differences include LLM Stats Score (43.0 vs 3.6), multimodal support (no vs yes), licensing (Unknown vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Ling 3.0 Flash Fin and Ministral 3 (14B Base 2512)?

Ling 3.0 Flash Fin is developed by InclusionAI and Ministral 3 (14B Base 2512) is developed by Mistral AI.

Related comparisons