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Ling 3.0 Flash Fin vs QvQ-72B-Preview

Ling 3.0 Flash Fin leads the LLM Stats Score 43.3 to 7.9.

InclusionAI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Ling 3.0 Flash Fin leads the overall LLM Stats Score 43.3 to 7.9, ranking #39 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 43.3 and ranks #39 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

Choose QvQ-72B-Preview

  • 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
QvQ-72B-Preview
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
43.3
#39
7.9
#280
Reasoning
44.7
#32
8.3
#274
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 · 4 for QvQ-72B-Preview

No common benchmarks found

Ling 3.0 Flash Fin and QvQ-72B-Previewdon'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

50.6B diff

Ling 3.0 Flash Fin has 50.6B more parameters than QvQ-72B-Preview, making it 68.9% larger.

InclusionAI
Ling 3.0 Flash Fin
124.0Bparameters
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
73.4Bparameters
124.0B
Ling 3.0 Flash Fin
73.4B
QvQ-72B-Preview

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
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
Input- tokens
Output- tokens
Thu Sep 10 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

QvQ-72B-Preview supports multimodal inputs, whereas Ling 3.0 Flash Fin does not.

QvQ-72B-Preview 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

QvQ-72B-Preview

Text
Images
Audio
Video

Release Timeline

When each model was launched

Ling 3.0 Flash Fin was released on 2026-09-03, while QvQ-72B-Preview was released on 2024-12-25.

Ling 3.0 Flash Fin is 21 months newer than QvQ-72B-Preview.

Ling 3.0 Flash Fin

Sep 3, 2026

6 days ago

1.7yr newer
QvQ-72B-Preview

Dec 25, 2024

1.7 years 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 QvQ-72B-Preview side-by-side, then vote on the output you prefer.

Ling 3.0 Flash Fin
✓ Preferred
QvQ-72B-Preview
Open in Playground

FAQ

Common questions about Ling 3.0 Flash Fin vs QvQ-72B-Preview.

Which is better, Ling 3.0 Flash Fin or QvQ-72B-Preview?

Ling 3.0 Flash Fin leads the LLM Stats Score 43.3 to 7.9. Ling 3.0 Flash Fin is made by InclusionAI and QvQ-72B-Preview is made by Alibaba Cloud / Qwen Team. 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 QvQ-72B-Preview 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%. QvQ-72B-Preview scores MathVista: 71.4%, MMMU: 70.3%, MathVision: 35.9%, OlympiadBench: 20.4%.

What are the context window sizes for Ling 3.0 Flash Fin and QvQ-72B-Preview?

Ling 3.0 Flash Fin supports 262K tokens and QvQ-72B-Preview 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 QvQ-72B-Preview?

Key differences include LLM Stats Score (43.3 vs 7.9), multimodal support (no vs yes), licensing (Unknown vs Qwen). See the full comparison above for benchmark-by-benchmark results.

Who makes Ling 3.0 Flash Fin and QvQ-72B-Preview?

Ling 3.0 Flash Fin is developed by InclusionAI and QvQ-72B-Preview is developed by Alibaba Cloud / Qwen Team.

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