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Ling 3.0 Flash Fin vs Qwen2-VL-72B-Instruct

Ling 3.0 Flash Fin leads the LLM Stats Score 43.3 to 14.4.

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 14.4, 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 Qwen2-VL-72B-Instruct

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

At a glance

The differences that matter most.

Core performance indexes
43.3
#39
14.4
#235
44.7
#32
11.7
#250
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 · 15 for Qwen2-VL-72B-Instruct

No common benchmarks found

Ling 3.0 Flash Fin and Qwen2-VL-72B-Instructdon'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 Qwen2-VL-72B-Instruct, making it 68.9% larger.

InclusionAI
Ling 3.0 Flash Fin
124.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2-VL-72B-Instruct
73.4Bparameters
124.0B
Ling 3.0 Flash Fin
73.4B
Qwen2-VL-72B-Instruct

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
Qwen2-VL-72B-Instruct
Input- tokens
Output- tokens
Wed Sep 09 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen2-VL-72B-Instruct supports multimodal inputs, whereas Ling 3.0 Flash Fin does not.

Qwen2-VL-72B-Instruct 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

Qwen2-VL-72B-Instruct

Text
Images
Audio
Video

Release Timeline

When each model was launched

Ling 3.0 Flash Fin was released on 2026-09-03, while Qwen2-VL-72B-Instruct was released on 2024-08-29.

Ling 3.0 Flash Fin is 25 months newer than Qwen2-VL-72B-Instruct.

Ling 3.0 Flash Fin

Sep 3, 2026

6 days ago

2.0yr newer
Qwen2-VL-72B-Instruct

Aug 29, 2024

2.0 years ago

Knowledge Cutoff

When training data ends

Qwen2-VL-72B-Instruct has a documented knowledge cutoff of 2023-06-30, while Ling 3.0 Flash Fin's cutoff date is not specified.

We can confirm Qwen2-VL-72B-Instruct's training data extends to 2023-06-30, but cannot make a direct comparison without Ling 3.0 Flash Fin's cutoff date.

Ling 3.0 Flash Fin

Qwen2-VL-72B-Instruct

Jun 2023

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 Qwen2-VL-72B-Instruct side-by-side, then vote on the output you prefer.

Ling 3.0 Flash Fin
✓ Preferred
Qwen2-VL-72B-Instruct
Open in Playground

FAQ

Common questions about Ling 3.0 Flash Fin vs Qwen2-VL-72B-Instruct.

Which is better, Ling 3.0 Flash Fin or Qwen2-VL-72B-Instruct?

Ling 3.0 Flash Fin leads the LLM Stats Score 43.3 to 14.4. Ling 3.0 Flash Fin is made by InclusionAI and Qwen2-VL-72B-Instruct 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 Qwen2-VL-72B-Instruct 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%. Qwen2-VL-72B-Instruct scores DocVQAtest: 96.5%, VCR_en_easy: 91.9%, ChartQA: 88.3%, OCRBench: 87.7%, MMBench: 86.5%.

What are the context window sizes for Ling 3.0 Flash Fin and Qwen2-VL-72B-Instruct?

Ling 3.0 Flash Fin supports 262K tokens and Qwen2-VL-72B-Instruct 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 Qwen2-VL-72B-Instruct?

Key differences include LLM Stats Score (43.3 vs 14.4), multimodal support (no vs yes), licensing (Unknown vs tongyi-qianwen). See the full comparison above for benchmark-by-benchmark results.

Who makes Ling 3.0 Flash Fin and Qwen2-VL-72B-Instruct?

Ling 3.0 Flash Fin is developed by InclusionAI and Qwen2-VL-72B-Instruct is developed by Alibaba Cloud / Qwen Team.