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DeepSeek-V4-Flash-Vision-Exp vs Ling 3.1 Flash

DeepSeek-V4-Flash-Vision-Exp and Ling 3.1 Flash are closely matched at 44.7 and 51.1 on the LLM Stats Score.

DeepSeek · InclusionAI · Updated for 2026

Which is better?

DeepSeek-V4-Flash-Vision-Exp and Ling 3.1 Flash are closely matched on the overall LLM Stats Score at 44.7 and 51.1.

In the 1 individual benchmarks reported for both models, Ling 3.1 Flash wins 1; 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-Flash-Vision-Exp

  • you want predictable pricing at $0.22/M input and $0.66/M output

Choose Ling 3.1 Flash

  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

DeepSeek-V4-Flash-Vision-Exp
DeepSeek
Ling 3.1 Flash
InclusionAI
Core performance indexes
LLM Stats Score
44.7
#39
51.1
#14
Reasoning
41.1
#58
47.7
#25
Coding
33.8
#39
39.2
#17
Agents
31.0
#37
38.3
#11
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
Input price
$0.22 / M
— / M
Output price
$0.66 / M
— / M
Context window
1,048,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4-Flash-Vision-Exp
Ling 3.1 Flash
Tool use
21.3#54
29.0#13
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

7 reported for DeepSeek-V4-Flash-Vision-Exp · 11 for Ling 3.1 Flash

1 shared

DeepSeek-V4-Flash-Vision-Exp outperforms in 0 benchmarks, while Ling 3.1 Flash is better at 1 benchmark (AutomationBench).

Ling 3.1 Flash significantly outperforms across most benchmarks.

Wed Oct 07 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Flash-Vision-Exp specifies input context (1,048,576 tokens). Only DeepSeek-V4-Flash-Vision-Exp specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4-Flash-Vision-Exp
Input1,048,576 tokens
Output393,216 tokens
InclusionAI
Ling 3.1 Flash
Input- tokens
Output- tokens
Wed Oct 07 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4-Flash-Vision-Exp supports multimodal inputs, whereas Ling 3.1 Flash does not.

DeepSeek-V4-Flash-Vision-Exp can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4-Flash-Vision-Exp

Text
Images
Audio
Video

Ling 3.1 Flash

Text
Images
Audio
Video

Release Timeline

When each model was launched

DeepSeek-V4-Flash-Vision-Exp was released on 2026-08-21, while Ling 3.1 Flash was released on 2026-09-30.

Ling 3.1 Flash is 1 month newer than DeepSeek-V4-Flash-Vision-Exp.

DeepSeek-V4-Flash-Vision-Exp

Aug 21, 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-Flash-Vision-Exp and Ling 3.1 Flash side-by-side, then vote on the output you prefer.

DeepSeek-V4-Flash-Vision-Exp
✓ Preferred
Ling 3.1 Flash
Open in Playground

FAQ

Common questions about DeepSeek-V4-Flash-Vision-Exp vs Ling 3.1 Flash.

Which is better, DeepSeek-V4-Flash-Vision-Exp or Ling 3.1 Flash?

DeepSeek-V4-Flash-Vision-Exp and Ling 3.1 Flash are closely matched on the LLM Stats Score at 44.7 and 51.1. DeepSeek-V4-Flash-Vision-Exp 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-Flash-Vision-Exp compare to Ling 3.1 Flash in benchmarks?

DeepSeek-V4-Flash-Vision-Exp scores Terminal-Bench 2.1: 83.9%, DSBench-Hard: 63.6%, DeepSWE: 59.3%, NL2Repo: 57.7%, ZEROBench: 35.0%. 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-Flash-Vision-Exp and Ling 3.1 Flash?

DeepSeek-V4-Flash-Vision-Exp 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-Flash-Vision-Exp and Ling 3.1 Flash?

Key differences include LLM Stats Score (44.7 vs 51.1), multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Flash-Vision-Exp and Ling 3.1 Flash?

DeepSeek-V4-Flash-Vision-Exp is developed by DeepSeek and Ling 3.1 Flash is developed by InclusionAI.

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