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Gemma 4 31B vs Qwen3.8-Flash-Next

Qwen3.8-Flash-Next leads the LLM Stats Score 50.5 to 33.4.

Google · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3.8-Flash-Next leads the overall LLM Stats Score 50.5 to 33.4, ranking #14 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 Gemma 4 31B

  • you want predictable pricing at $0.13/M input and $0.38/M output

Choose Qwen3.8-Flash-Next

  • overall performance matters — it scores 50.5 and ranks #14 on LLM Stats
  • your work emphasizes reasoning and agents — 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

At a glance

The differences that matter most.

Gemma 4 31B
Google
Qwen3.8-Flash-Next
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
33.4
#87
50.5
#14
Reasoning
34.0
#81
50.6
#12
Agents
14.3
#78
37.2
#12
Cost, coverage & limits
Benchmark wins
0 of 4
4 of 4
Input price
$0.13 / M
— / M
Output price
$0.38 / M
— / M
Context window
262,144
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
Gemma 4 31B
Qwen3.8-Flash-Next
Math
29.3#78
33.3#50
Vision
19.4#67
34.6#11
Multimodal
21.7#55
35.3#8
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

12 reported for Gemma 4 31B · 22 for Qwen3.8-Flash-Next

4 shared

Gemma 4 31B outperforms in 0 benchmarks, while Qwen3.8-Flash-Next is better at 4 benchmarks (GPQA, Humanity's Last Exam, LiveCodeBench v6, MathVision).

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

Fri Aug 28 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

94.3B diff

Qwen3.8-Flash-Next has 94.3B more parameters than Gemma 4 31B, making it 307.2% larger.

Google
Gemma 4 31B
30.7Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
125.0Bparameters
30.7B
Gemma 4 31B
125.0B
Qwen3.8-Flash-Next

Context Window

Maximum input and output token capacity

Only Gemma 4 31B specifies input context (262,144 tokens). Only Gemma 4 31B specifies output context (131,072 tokens).

Google
Gemma 4 31B
Input262,144 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
Input- tokens
Output- tokens
Fri Aug 28 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Gemma 4 31B and Qwen3.8-Flash-Next support multimodal inputs.

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

Gemma 4 31B

Text
Images
Audio
Video

Qwen3.8-Flash-Next

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 4 31B 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.

Gemma 4 31B

Apache 2.0

Open weights

Qwen3.8-Flash-Next

Qwen Community License 1.0

Open weights

Release Timeline

When each model was launched

Gemma 4 31B was released on 2026-04-02, while Qwen3.8-Flash-Next was released on 2026-08-26.

Qwen3.8-Flash-Next is 5 months newer than Gemma 4 31B.

Gemma 4 31B

Apr 2, 2026

4 months ago

Qwen3.8-Flash-Next

Aug 26, 2026

2 days ago

4mo newer

Knowledge Cutoff

When training data ends

Gemma 4 31B has a documented knowledge cutoff of 2025-01-01, while Qwen3.8-Flash-Next's cutoff date is not specified.

We can confirm Gemma 4 31B's training data extends to 2025-01-01, but cannot make a direct comparison without Qwen3.8-Flash-Next's cutoff date.

Gemma 4 31B

Jan 2025

Qwen3.8-Flash-Next

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Gemma 4 31B and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.

Gemma 4 31B
✓ Preferred
Qwen3.8-Flash-Next
Open in Playground

FAQ

Common questions about Gemma 4 31B vs Qwen3.8-Flash-Next.

Which is better, Gemma 4 31B or Qwen3.8-Flash-Next?

Qwen3.8-Flash-Next leads the LLM Stats Score 50.5 to 33.4. Gemma 4 31B is made by Google 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 Gemma 4 31B compare to Qwen3.8-Flash-Next in benchmarks?

Gemma 4 31B scores AIME 2026: 89.2%, MMMLU: 88.4%, t2-bench: 86.4%, MathVision: 85.6%, MMLU-Pro: 85.2%. 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 Gemma 4 31B and Qwen3.8-Flash-Next?

Gemma 4 31B 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 Gemma 4 31B and Qwen3.8-Flash-Next?

Key differences include LLM Stats Score (33.4 vs 50.5), licensing (Apache 2.0 vs Qwen Community License 1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 4 31B and Qwen3.8-Flash-Next?

Gemma 4 31B is developed by Google and Qwen3.8-Flash-Next is developed by Alibaba Cloud / Qwen Team.

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