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DeepSeek-V2.5 vs Ling 3.1 Flash

Ling 3.1 Flash leads the LLM Stats Score 51.0 to 8.1.

DeepSeek · InclusionAI · Updated for 2026

Which is better?

Ling 3.1 Flash leads the overall LLM Stats Score 51.0 to 8.1, ranking #15 overall.

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

Choose DeepSeek-V2.5

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

Choose Ling 3.1 Flash

  • overall performance matters — it scores 51.0 and ranks #15 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.

DeepSeek-V2.5
DeepSeek
Ling 3.1 Flash
InclusionAI
Core performance indexes
LLM Stats Score
8.1
#297
51.0
#15
Reasoning
8.2
#293
47.5
#26
Coding
6.3
#205
38.8
#18
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.14 / M
— / M
Output price
$0.28 / M
— / M
Context window
8,192
—

Individual benchmarks

15 reported for DeepSeek-V2.5 · 11 for Ling 3.1 Flash

No common benchmarks found

DeepSeek-V2.5 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

324.0B diff

Ling 3.1 Flash has 324.0B more parameters than DeepSeek-V2.5, making it 137.3% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
InclusionAI
Ling 3.1 Flash
560.0Bparameters
236.0B
DeepSeek-V2.5
560.0B
Ling 3.1 Flash

Context Window

Maximum input and output token capacity

Only DeepSeek-V2.5 specifies input context (8,192 tokens). Only DeepSeek-V2.5 specifies output context (8,192 tokens).

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
InclusionAI
Ling 3.1 Flash
Input- tokens
Output- tokens
Fri Oct 09 2026 • llm-stats.com

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while Ling 3.1 Flash was released on 2026-09-30.

Ling 3.1 Flash is 29 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

2.4 years ago

Ling 3.1 Flash

Sep 30, 2026

1 weeks ago

2.4yr 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-V2.5 and Ling 3.1 Flash side-by-side, then vote on the output you prefer.

DeepSeek-V2.5
✓ Preferred
Ling 3.1 Flash
Open in Playground

FAQ

Common questions about DeepSeek-V2.5 vs Ling 3.1 Flash.

Which is better, DeepSeek-V2.5 or Ling 3.1 Flash?

Ling 3.1 Flash leads the LLM Stats Score 51.0 to 8.1. DeepSeek-V2.5 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-V2.5 compare to Ling 3.1 Flash in benchmarks?

DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%. 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-V2.5 and Ling 3.1 Flash?

DeepSeek-V2.5 supports 8K 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-V2.5 and Ling 3.1 Flash?

Key differences include LLM Stats Score (8.1 vs 51.0), licensing (deepseek vs Unknown). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V2.5 and Ling 3.1 Flash?

DeepSeek-V2.5 is developed by DeepSeek and Ling 3.1 Flash is developed by InclusionAI.

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