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DeepSeek-V3 vs Ling 3.1 Flash

Ling 3.1 Flash leads the LLM Stats Score 51.1 to 15.6.

DeepSeek · InclusionAI · Updated for 2026

Which is better?

Ling 3.1 Flash leads the overall LLM Stats Score 51.1 to 15.6, ranking #14 overall.

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

Choose DeepSeek-V3

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

Choose Ling 3.1 Flash

  • overall performance matters — it scores 51.1 and ranks #14 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

Core performance indexes
15.6
#243
51.1
#14
14.7
#242
47.7
#25
6.1
#205
39.2
#17
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.27 / M
— / M
Output price
$0.89 / M
— / M
Context window
131,072
—

Individual benchmarks

20 reported for DeepSeek-V3 · 11 for Ling 3.1 Flash

No common benchmarks found

DeepSeek-V3 and Ling 3.1 Flashdon'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

111.0B diff

DeepSeek-V3 has 111.0B more parameters than Ling 3.1 Flash, making it 19.8% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
InclusionAI
Ling 3.1 Flash
560.0Bparameters
671.0B
DeepSeek-V3
560.0B
Ling 3.1 Flash

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 specifies input context (131,072 tokens). Only DeepSeek-V3 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
InclusionAI
Ling 3.1 Flash
Input- tokens
Output- tokens
Wed Oct 07 2026 • llm-stats.com

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Ling 3.1 Flash was released on 2026-09-30.

Ling 3.1 Flash is 21 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.8 years ago

Ling 3.1 Flash

Sep 30, 2026

1 weeks ago

1.8yr 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-V3 and Ling 3.1 Flash side-by-side, then vote on the output you prefer.

DeepSeek-V3
✓ Preferred
Ling 3.1 Flash
Open in Playground

FAQ

Common questions about DeepSeek-V3 vs Ling 3.1 Flash.

Which is better, DeepSeek-V3 or Ling 3.1 Flash?

Ling 3.1 Flash leads the LLM Stats Score 51.1 to 15.6. DeepSeek-V3 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-V3 compare to Ling 3.1 Flash in benchmarks?

DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. 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-V3 and Ling 3.1 Flash?

DeepSeek-V3 supports 131K 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-V3 and Ling 3.1 Flash?

Key differences include LLM Stats Score (15.6 vs 51.1), licensing (MIT + Model License (Commercial use allowed) vs Unknown). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3 and Ling 3.1 Flash?

DeepSeek-V3 is developed by DeepSeek and Ling 3.1 Flash is developed by InclusionAI.