The AI arena is free today

Open Superagent

Qwen3.8-27B vs Qwen3.8-Flash-Next

Qwen3.8-27B and Qwen3.8-Flash-Next are closely matched at 45.2 and 49.2 on the LLM Stats Score.

Alibaba Cloud / Qwen Team · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3.8-27B and Qwen3.8-Flash-Next are closely matched on the overall LLM Stats Score at 45.2 and 49.2.

In the 18 individual benchmarks reported for both models, Qwen3.8-Flash-Next wins 18; 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 Qwen3.8-27B

  • you are already invested in the Alibaba Cloud / Qwen Team ecosystem

Choose Qwen3.8-Flash-Next

  • you value its reported benchmark strengths — it wins 18 of 18 exact shared results
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Qwen3.8-27B
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
45.2
#30
49.2
#19
Reasoning
44.8
#30
48.9
#18
Coding
31.6
#39
36.1
#21
Agents
30.4
#31
34.7
#18
Cost, coverage & limits
Benchmark wins
0 of 18
18 of 18
Input price
— / M
— / M
Output price
— / M
— / M
Context window
262,144
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

5 shared
Index
Qwen3.8-27B
Qwen3.8-Flash-Next
Math
31.0#68
32.6#55
Vision
33.1#18
33.9#13
Tool use
22.7#42
30.7#13
Multimodal
36.9#6
35.6#8
Productivity
5.5#10
15.3#2
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

26 reported for Qwen3.8-27B · 22 for Qwen3.8-Flash-Next

18 shared

Qwen3.8-27B outperforms in 0 benchmarks, while Qwen3.8-Flash-Next is better at 18 benchmarks (Agents' Last Exam, AndroidWorld, CharXiv-R, ClawEval-MM, CoWorkBench, DeepSWE 1.1, ERQA, GPQA, Humanity's Last Exam, IFBench, Job Bench, LiveCodeBench v6, MathVision, NL2Repo, RealWorldQA, RecreationBench, SWE-Bench Pro, Vision2Web).

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

Sun Sep 06 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

97.2B diff

Qwen3.8-Flash-Next has 97.2B more parameters than Qwen3.8-27B, making it 349.9% larger.

Alibaba Cloud / Qwen Team
Qwen3.8-27B
27.8Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
125.0Bparameters
27.8B
Qwen3.8-27B
125.0B
Qwen3.8-Flash-Next

Context Window

Maximum input and output token capacity

Only Qwen3.8-27B specifies input context (262,144 tokens). Only Qwen3.8-27B specifies output context (131,072 tokens).

Alibaba Cloud / Qwen Team
Qwen3.8-27B
Input262,144 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
Input- tokens
Output- tokens
Sun Sep 06 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Qwen3.8-27B and Qwen3.8-Flash-Next support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Qwen3.8-27B

Text
Images
Audio
Video

Qwen3.8-Flash-Next

Text
Images
Audio
Video

License

Usage and distribution terms

Qwen3.8-27B is licensed under Apache 2.0, while Qwen3.8-Flash-Next uses Qwen Community License 1.0.

License differences may affect how you can use these models in commercial or open-source projects.

Qwen3.8-27B

Apache 2.0

Open weights

Qwen3.8-Flash-Next

Qwen Community License 1.0

Open weights

Release Timeline

When each model was launched

Qwen3.8-27B was released on 2026-08-14, while Qwen3.8-Flash-Next was released on 2026-08-26.

Qwen3.8-Flash-Next is 0 month newer than Qwen3.8-27B.

Qwen3.8-27B

Aug 14, 2026

3 weeks ago

Qwen3.8-Flash-Next

Aug 26, 2026

1 weeks ago

1w 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?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Qwen3.8-27B and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.

Qwen3.8-27B
✓ Preferred
Qwen3.8-Flash-Next
Open in Playground

FAQ

Common questions about Qwen3.8-27B vs Qwen3.8-Flash-Next.

Which is better, Qwen3.8-27B or Qwen3.8-Flash-Next?

Qwen3.8-27B and Qwen3.8-Flash-Next are closely matched on the LLM Stats Score at 45.2 and 49.2. Qwen3.8-27B is made by Alibaba Cloud / Qwen Team 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 Qwen3.8-27B compare to Qwen3.8-Flash-Next in benchmarks?

Qwen3.8-27B scores MathVision: 94.6%, OmniDocBench 1.5: 91.1%, LiveCodeBench v6: 90.3%, CharXiv-R: 90.2%, GPQA: 89.2%. 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 Qwen3.8-27B and Qwen3.8-Flash-Next?

Qwen3.8-27B 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 Qwen3.8-27B and Qwen3.8-Flash-Next?

Key differences include LLM Stats Score (45.2 vs 49.2), licensing (Apache 2.0 vs Qwen Community License 1.0). See the full comparison above for benchmark-by-benchmark results.

Related comparisons