The AI arena is free today

Open Superagent

Ling 3.0 Flash Fin vs Qwen3.8-Flash-Next

Ling 3.0 Flash Fin and Qwen3.8-Flash-Next are closely matched at 43.0 and 49.1 on the LLM Stats Score.

InclusionAI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Ling 3.0 Flash Fin and Qwen3.8-Flash-Next are closely matched on the overall LLM Stats Score at 43.0 and 49.1.

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

Choose Ling 3.0 Flash Fin

  • you want the most recent training data — it shipped Sep 2026

Choose Qwen3.8-Flash-Next

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

At a glance

The differences that matter most.

Ling 3.0 Flash Fin
InclusionAI
Qwen3.8-Flash-Next
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
43.0
#44
49.1
#20
Reasoning
44.2
#35
48.9
#19
Agents
29.2
#37
35.1
#20
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.06 / M
— / M
Output price
$0.18 / M
— / M
Context window
262,144
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Ling 3.0 Flash Fin
Qwen3.8-Flash-Next
Tool use
20.4#58
31.1#11
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

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

No common benchmarks found

Ling 3.0 Flash Fin and Qwen3.8-Flash-Nextdon'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

1.0B diff

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

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

Context Window

Maximum input and output token capacity

Only Ling 3.0 Flash Fin specifies input context (262,144 tokens). Only Ling 3.0 Flash Fin specifies output context (262,144 tokens).

InclusionAI
Ling 3.0 Flash Fin
Input262,144 tokens
Output262,144 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
Input- tokens
Output- tokens
Sun Sep 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3.8-Flash-Next supports multimodal inputs, whereas Ling 3.0 Flash Fin 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 Fin

Text
Images
Audio
Video

Qwen3.8-Flash-Next

Text
Images
Audio
Video

Release Timeline

When each model was launched

Ling 3.0 Flash Fin was released on 2026-09-03, while Qwen3.8-Flash-Next was released on 2026-08-26.

Ling 3.0 Flash Fin is 0 month newer than Qwen3.8-Flash-Next.

Ling 3.0 Flash Fin

Sep 3, 2026

2 weeks ago

1w newer
Qwen3.8-Flash-Next

Aug 26, 2026

3 weeks ago

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?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Ling 3.0 Flash Fin and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.

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

FAQ

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

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

Ling 3.0 Flash Fin and Qwen3.8-Flash-Next are closely matched on the LLM Stats Score at 43.0 and 49.1. Ling 3.0 Flash Fin 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 Fin compare to Qwen3.8-Flash-Next in benchmarks?

Ling 3.0 Flash Fin scores SpreadSheetBench-v1: 86.5%, Finance Agent v1.1: 69.2%, Finance Agent v2: 59.8%, Tau3 Banking: 41.0%, APEX-Agents: 29.2%. 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 Fin and Qwen3.8-Flash-Next?

Ling 3.0 Flash Fin supports 262K 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 Fin and Qwen3.8-Flash-Next?

Key differences include LLM Stats Score (43.0 vs 49.1), 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 Fin and Qwen3.8-Flash-Next?

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

Related comparisons