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Ling 3.0 Flash vs Qwen3.8-Flash-Next

Qwen3.8-Flash-Next leads the LLM Stats Score 48.3 to 36.0.

InclusionAI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3.8-Flash-Next leads the overall LLM Stats Score 48.3 to 36.0, ranking #27 overall.

In the 4 individual benchmarks reported for both models, Qwen3.8-Flash-Next wins 4; 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 Ling 3.0 Flash

  • you want predictable pricing at $0.06/M input and $0.18/M output

Choose Qwen3.8-Flash-Next

  • overall performance matters — it scores 48.3 and ranks #27 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 4 of 4 exact shared results
  • you want the most recent training data — it shipped Aug 2026
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Ling 3.0 Flash
InclusionAI
Qwen3.8-Flash-Next
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
36.0
#92
48.3
#27
Reasoning
35.3
#94
48.4
#20
Coding
24.5
#84
34.1
#36
Agents
18.9
#79
33.2
#29
Cost, coverage & limits
Benchmark wins
0 of 4
4 of 4
Input price
$0.06 / M
— / M
Output price
$0.18 / M
— / M
Context window
131,072
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Ling 3.0 Flash
Qwen3.8-Flash-Next
Math
29.8#85
32.7#60
Tool use
15.9#93
29.1#13
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

19 reported for Ling 3.0 Flash · 22 for Qwen3.8-Flash-Next

4 shared

Ling 3.0 Flash outperforms in 0 benchmarks, while Qwen3.8-Flash-Next is better at 4 benchmarks (IFBench, LiveCodeBench v6, SWE-bench Multilingual, SWE-Bench Pro).

Qwen3.8-Flash-Next significantly outperforms across most benchmarks.

Fri Oct 09 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

1.0B diff

Qwen3.8-Flash-Next has 1.0B more parameters than Ling 3.0 Flash, making it 0.8% larger.

InclusionAI
Ling 3.0 Flash
124.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
125.0Bparameters
124.0B
Ling 3.0 Flash
125.0B
Qwen3.8-Flash-Next

Context Window

Maximum input and output token capacity

Only Ling 3.0 Flash specifies input context (131,072 tokens). Only Ling 3.0 Flash specifies output context (131,072 tokens).

InclusionAI
Ling 3.0 Flash
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
Input- tokens
Output- tokens
Fri Oct 09 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3.8-Flash-Next supports multimodal inputs, whereas Ling 3.0 Flash does not.

Qwen3.8-Flash-Next can handle both text and other forms of data like images, making it suitable for multimodal applications.

Ling 3.0 Flash

Text
Images
Audio
Video

Qwen3.8-Flash-Next

Text
Images
Audio
Video

Release Timeline

When each model was launched

Ling 3.0 Flash was released on 2026-08-04, while Qwen3.8-Flash-Next was released on 2026-08-26.

Qwen3.8-Flash-Next is 1 month newer than Ling 3.0 Flash.

Ling 3.0 Flash

Aug 4, 2026

2 months ago

Qwen3.8-Flash-Next

Aug 26, 2026

1 months ago

3w 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 Ling 3.0 Flash and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.

Ling 3.0 Flash
✓ Preferred
Qwen3.8-Flash-Next
Open in Playground

FAQ

Common questions about Ling 3.0 Flash vs Qwen3.8-Flash-Next.

Which is better, Ling 3.0 Flash or Qwen3.8-Flash-Next?

Qwen3.8-Flash-Next leads the LLM Stats Score 48.3 to 36.0. Ling 3.0 Flash is made by InclusionAI and Qwen3.8-Flash-Next is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Ling 3.0 Flash compare to Qwen3.8-Flash-Next in benchmarks?

Ling 3.0 Flash scores AIME 2026: 93.2%, Multi-IF: 87.7%, HMMT Feb 26: 87.0%, IMO-AnswerBench: 83.7%, LiveCodeBench v6: 82.8%. Qwen3.8-Flash-Next scores MathVision: 95.7%, LiveCodeBench v6: 91.9%, GPQA: 91.7%, CharXiv-R: 90.6%, RealWorldQA: 88.5%.

What are the context window sizes for Ling 3.0 Flash and Qwen3.8-Flash-Next?

Ling 3.0 Flash supports 131K tokens and Qwen3.8-Flash-Next 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 Ling 3.0 Flash and Qwen3.8-Flash-Next?

Key differences include LLM Stats Score (36.0 vs 48.3), multimodal support (no vs yes), licensing (Unknown vs Qwen Community License 1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Ling 3.0 Flash and Qwen3.8-Flash-Next?

Ling 3.0 Flash is developed by InclusionAI and Qwen3.8-Flash-Next is developed by Alibaba Cloud / Qwen Team.

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