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DeepSeek VL2 vs Ling 3.0 Flash Fin

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

DeepSeek · InclusionAI · Updated for 2026

Which is better?

Ling 3.0 Flash Fin leads the overall LLM Stats Score 43.3 to 3.0, ranking #39 overall.

Ling 3.0 Flash Fin also accepts a larger context window (262,144 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 VL2

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

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 process long inputs — it offers a 262,144 token context window
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

DeepSeek VL2
DeepSeek
Ling 3.0 Flash Fin
InclusionAI
Core performance indexes
LLM Stats Score
3.0
#309
43.3
#39
Reasoning
-1.8
#327
44.7
#32
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.06 / M
Output price
— / M
$0.18 / M
Context window
129,280
262,144

Individual benchmarks

14 reported for DeepSeek VL2 · 6 for Ling 3.0 Flash Fin

No common benchmarks found

DeepSeek VL2 and Ling 3.0 Flash Findon'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

97.0B diff

Ling 3.0 Flash Fin has 97.0B more parameters than DeepSeek VL2, making it 359.3% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
InclusionAI
Ling 3.0 Flash Fin
124.0Bparameters
27.0B
DeepSeek VL2
124.0B
Ling 3.0 Flash Fin

Context Window

Maximum input and output token capacity

Ling 3.0 Flash Fin accepts 262,144 input tokens compared to DeepSeek VL2's 129,280 tokens. Ling 3.0 Flash Fin can generate longer responses up to 262,144 tokens, while DeepSeek VL2 is limited to 129,280 tokens.

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
InclusionAI
Ling 3.0 Flash Fin
Input262,144 tokens
Output262,144 tokens
Thu Sep 10 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek VL2 supports multimodal inputs, whereas Ling 3.0 Flash Fin does not.

DeepSeek VL2 can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek VL2

Text
Images
Audio
Video

Ling 3.0 Flash Fin

Text
Images
Audio
Video

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while Ling 3.0 Flash Fin was released on 2026-09-03.

Ling 3.0 Flash Fin is 21 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.7 years ago

Ling 3.0 Flash Fin

Sep 3, 2026

6 days ago

1.7yr newer

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 VL2 is available from Replicate. Ling 3.0 Flash Fin is available from DeepInfra.

DeepSeek VL2

replicate logo
Replicate

Ling 3.0 Flash Fin

deepinfra logo
Deepinfra
Input Price:Input: $0.06/1MOutput Price:Output: $0.18/1M
* 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 VL2 and Ling 3.0 Flash Fin side-by-side, then vote on the output you prefer.

DeepSeek VL2
✓ Preferred
Ling 3.0 Flash Fin
Open in Playground

FAQ

Common questions about DeepSeek VL2 vs Ling 3.0 Flash Fin.

Which is better, DeepSeek VL2 or Ling 3.0 Flash Fin?

Ling 3.0 Flash Fin leads the LLM Stats Score 43.3 to 3.0. DeepSeek VL2 is made by DeepSeek and Ling 3.0 Flash Fin is made by InclusionAI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek VL2 compare to Ling 3.0 Flash Fin in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. 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%.

What are the context window sizes for DeepSeek VL2 and Ling 3.0 Flash Fin?

DeepSeek VL2 supports 129K tokens and Ling 3.0 Flash Fin 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 VL2 and Ling 3.0 Flash Fin?

Key differences include LLM Stats Score (3.0 vs 43.3), context window (129K vs 262K), multimodal support (yes vs no), licensing (deepseek vs Unknown). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 and Ling 3.0 Flash Fin?

DeepSeek VL2 is developed by DeepSeek and Ling 3.0 Flash Fin is developed by InclusionAI.

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