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DeepSeek-V3 0324 vs Qwen3.8-Flash-Next

Qwen3.8-Flash-Next leads the LLM Stats Score 50.5 to 13.7.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3.8-Flash-Next leads the overall LLM Stats Score 50.5 to 13.7, ranking #14 overall.

In the 1 individual benchmarks reported for both models, Qwen3.8-Flash-Next 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-V3 0324

  • you want predictable pricing at $0.28/M input and $1.14/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 coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

DeepSeek-V3 0324
DeepSeek
Qwen3.8-Flash-Next
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
13.7
#223
50.5
#14
Reasoning
13.9
#216
50.6
#12
Coding
4.0
#197
38.4
#19
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
Input price
$0.28 / M
— / M
Output price
$1.14 / M
— / M
Context window
163,840
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V3 0324
Qwen3.8-Flash-Next
Math
16.0#198
33.3#50
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

5 reported for DeepSeek-V3 0324 · 22 for Qwen3.8-Flash-Next

1 shared

DeepSeek-V3 0324 outperforms in 0 benchmarks, while Qwen3.8-Flash-Next is better at 1 benchmark (GPQA).

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

Sat Aug 29 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

546.0B diff

DeepSeek-V3 0324 has 546.0B more parameters than Qwen3.8-Flash-Next, making it 436.8% larger.

DeepSeek
DeepSeek-V3 0324
671.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
125.0Bparameters
671.0B
DeepSeek-V3 0324
125.0B
Qwen3.8-Flash-Next

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 0324 specifies input context (163,840 tokens). Only DeepSeek-V3 0324 specifies output context (163,840 tokens).

DeepSeek
DeepSeek-V3 0324
Input163,840 tokens
Output163,840 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
Input- tokens
Output- tokens
Sat Aug 29 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3.8-Flash-Next supports multimodal inputs, whereas DeepSeek-V3 0324 does not.

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

DeepSeek-V3 0324

Text
Images
Audio
Video

Qwen3.8-Flash-Next

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3 0324 is licensed under MIT + Model License (Commercial use allowed), 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.

DeepSeek-V3 0324

MIT + Model License (Commercial use allowed)

Open weights

Qwen3.8-Flash-Next

Qwen Community License 1.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 0324 was released on 2025-03-25, while Qwen3.8-Flash-Next was released on 2026-08-26.

Qwen3.8-Flash-Next is 17 months newer than DeepSeek-V3 0324.

DeepSeek-V3 0324

Mar 25, 2025

1.4 years ago

Qwen3.8-Flash-Next

Aug 26, 2026

2 days ago

1.4yr 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 DeepSeek-V3 0324 and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.

DeepSeek-V3 0324
✓ Preferred
Qwen3.8-Flash-Next
Open in Playground

FAQ

Common questions about DeepSeek-V3 0324 vs Qwen3.8-Flash-Next.

Which is better, DeepSeek-V3 0324 or Qwen3.8-Flash-Next?

Qwen3.8-Flash-Next leads the LLM Stats Score 50.5 to 13.7. DeepSeek-V3 0324 is made by DeepSeek 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 DeepSeek-V3 0324 compare to Qwen3.8-Flash-Next in benchmarks?

DeepSeek-V3 0324 scores MATH-500: 94.0%, MMLU-Pro: 81.2%, GPQA: 68.4%, AIME 2024: 59.4%, LiveCodeBench: 49.2%. 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 DeepSeek-V3 0324 and Qwen3.8-Flash-Next?

DeepSeek-V3 0324 supports 164K 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 DeepSeek-V3 0324 and Qwen3.8-Flash-Next?

Key differences include LLM Stats Score (13.7 vs 50.5), multimodal support (no vs yes), licensing (MIT + Model License (Commercial use allowed) vs Qwen Community License 1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3 0324 and Qwen3.8-Flash-Next?

DeepSeek-V3 0324 is developed by DeepSeek and Qwen3.8-Flash-Next is developed by Alibaba Cloud / Qwen Team.

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