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DeepSeek-V4-Pro-0813 vs Ling 3.1 Flash

DeepSeek-V4-Pro-0813 and Ling 3.1 Flash are closely matched at 50.6 and 51.0 on the LLM Stats Score.

DeepSeek · InclusionAI · Updated for 2026

Which is better?

DeepSeek-V4-Pro-0813 and Ling 3.1 Flash are closely matched on the overall LLM Stats Score at 50.6 and 51.0.

In the 2 individual benchmarks reported for both models, Ling 3.1 Flash wins 2; this is a narrower head-to-head signal than the composite indexes.

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

Choose DeepSeek-V4-Pro-0813

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

Choose Ling 3.1 Flash

  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

DeepSeek-V4-Pro-0813
DeepSeek
Ling 3.1 Flash
InclusionAI
Core performance indexes
LLM Stats Score
50.6
#18
51.0
#15
Reasoning
48.5
#19
47.5
#26
Coding
38.7
#19
38.8
#18
Agents
35.4
#20
38.0
#12
Cost, coverage & limits
Benchmark wins
0 of 2
2 of 2
Input price
$1.30 / M
— / M
Output price
$2.60 / M
— / M
Context window
1,048,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4-Pro-0813
Ling 3.1 Flash
Tool use
27.3#25
29.0#16
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

12 reported for DeepSeek-V4-Pro-0813 · 11 for Ling 3.1 Flash

2 shared

DeepSeek-V4-Pro-0813 outperforms in 0 benchmarks, while Ling 3.1 Flash is better at 2 benchmarks (AutomationBench, CyberGym).

Ling 3.1 Flash significantly outperforms across most benchmarks.

Sun Oct 11 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

1040.0B diff

DeepSeek-V4-Pro-0813 has 1040.0B more parameters than Ling 3.1 Flash, making it 185.7% larger.

DeepSeek
DeepSeek-V4-Pro-0813
1.6Tparameters
InclusionAI
Ling 3.1 Flash
560.0Bparameters
1600.0B
DeepSeek-V4-Pro-0813
560.0B
Ling 3.1 Flash

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Pro-0813 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Pro-0813 specifies output context (1,048,576 tokens).

DeepSeek
DeepSeek-V4-Pro-0813
Input1,048,576 tokens
Output1,048,576 tokens
InclusionAI
Ling 3.1 Flash
Input- tokens
Output- tokens
Sun Oct 11 2026 • llm-stats.com

Release Timeline

When each model was launched

DeepSeek-V4-Pro-0813 was released on 2026-08-13, while Ling 3.1 Flash was released on 2026-09-30.

Ling 3.1 Flash is 2 months newer than DeepSeek-V4-Pro-0813.

DeepSeek-V4-Pro-0813

Aug 13, 2026

1 months ago

Ling 3.1 Flash

Sep 30, 2026

1 weeks ago

1mo 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

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek-V4-Pro-0813 and Ling 3.1 Flash side-by-side, then vote on the output you prefer.

DeepSeek-V4-Pro-0813
✓ Preferred
Ling 3.1 Flash
Open in Playground

FAQ

Common questions about DeepSeek-V4-Pro-0813 vs Ling 3.1 Flash.

Which is better, DeepSeek-V4-Pro-0813 or Ling 3.1 Flash?

DeepSeek-V4-Pro-0813 and Ling 3.1 Flash are closely matched on the LLM Stats Score at 50.6 and 51.0. DeepSeek-V4-Pro-0813 is made by DeepSeek and Ling 3.1 Flash 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-V4-Pro-0813 compare to Ling 3.1 Flash in benchmarks?

DeepSeek-V4-Pro-0813 scores Terminal-Bench 2.1: 87.9%, CyberGym: 83.3%, Toolathlon: 74.1%, DSBench-FullStack: 71.1%, DSBench-Hard: 67.2%. Ling 3.1 Flash scores CyberGym: 87.9%, DRACO: 85.5%, FrontierSWE: 75.2%, Multi-Challenge: 69.8%, SkillsBench: 68.7%.

What are the context window sizes for DeepSeek-V4-Pro-0813 and Ling 3.1 Flash?

DeepSeek-V4-Pro-0813 supports 1.0M tokens and Ling 3.1 Flash 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 DeepSeek-V4-Pro-0813 and Ling 3.1 Flash?

Key differences include LLM Stats Score (50.6 vs 51.0), licensing (MIT vs Unknown). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Pro-0813 and Ling 3.1 Flash?

DeepSeek-V4-Pro-0813 is developed by DeepSeek and Ling 3.1 Flash is developed by InclusionAI.

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