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DeepSeek-V4-Flash-0731 vs Qwen3 VL 32B Instruct

DeepSeek-V4-Flash-0731 leads the LLM Stats Score 44.7 to 20.3.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-V4-Flash-0731 leads the overall LLM Stats Score 44.7 to 20.3, ranking #36 overall.

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

Choose DeepSeek-V4-Flash-0731

  • overall performance matters — it scores 44.7 and ranks #36 on LLM Stats
  • your work emphasizes reasoning and agents — it leads those capability indexes
  • you want the most recent training data — it shipped Jul 2026

Choose Qwen3 VL 32B Instruct

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

At a glance

The differences that matter most.

DeepSeek-V4-Flash-0731
DeepSeek
Qwen3 VL 32B Instruct
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
44.7
#36
20.3
#195
Reasoning
42.3
#46
19.2
#201
Agents
31.1
#31
9.6
#122
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.06 / M
— / M
Output price
$0.18 / M
— / M
Context window
1,048,576
—

Individual benchmarks

9 reported for DeepSeek-V4-Flash-0731 · 45 for Qwen3 VL 32B Instruct

No common benchmarks found

DeepSeek-V4-Flash-0731 and Qwen3 VL 32B Instructdon'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

271.0B diff

DeepSeek-V4-Flash-0731 has 271.0B more parameters than Qwen3 VL 32B Instruct, making it 821.2% larger.

DeepSeek
DeepSeek-V4-Flash-0731
304.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Instruct
33.0Bparameters
304.0B
DeepSeek-V4-Flash-0731
33.0B
Qwen3 VL 32B Instruct

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Flash-0731 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Flash-0731 specifies output context (1,048,576 tokens).

DeepSeek
DeepSeek-V4-Flash-0731
Input1,048,576 tokens
Output1,048,576 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Instruct
Input- tokens
Output- tokens
Sun Sep 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3 VL 32B Instruct supports multimodal inputs, whereas DeepSeek-V4-Flash-0731 does not.

Qwen3 VL 32B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4-Flash-0731

Text
Images
Audio
Video

Qwen3 VL 32B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4-Flash-0731 is licensed under MIT, while Qwen3 VL 32B Instruct uses Apache 2.0.

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

DeepSeek-V4-Flash-0731

MIT

Open weights

Qwen3 VL 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Flash-0731 was released on 2026-07-31, while Qwen3 VL 32B Instruct was released on 2025-09-22.

DeepSeek-V4-Flash-0731 is 10 months newer than Qwen3 VL 32B Instruct.

DeepSeek-V4-Flash-0731

Jul 31, 2026

1 months ago

10mo newer
Qwen3 VL 32B Instruct

Sep 22, 2025

12 months 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 DeepSeek-V4-Flash-0731 and Qwen3 VL 32B Instruct side-by-side, then vote on the output you prefer.

DeepSeek-V4-Flash-0731
✓ Preferred
Qwen3 VL 32B Instruct
Open in Playground

FAQ

Common questions about DeepSeek-V4-Flash-0731 vs Qwen3 VL 32B Instruct.

Which is better, DeepSeek-V4-Flash-0731 or Qwen3 VL 32B Instruct?

DeepSeek-V4-Flash-0731 leads the LLM Stats Score 44.7 to 20.3. DeepSeek-V4-Flash-0731 is made by DeepSeek and Qwen3 VL 32B Instruct 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-V4-Flash-0731 compare to Qwen3 VL 32B Instruct in benchmarks?

DeepSeek-V4-Flash-0731 scores Terminal-Bench 2.1: 82.7%, CyberGym: 76.7%, Toolathlon: 70.3%, DSBench-FullStack: 68.7%, DSBench-Hard: 59.6%. Qwen3 VL 32B Instruct scores DocVQAtest: 96.9%, ScreenSpot: 95.8%, CharXiv-D: 90.5%, MMLU-Redux: 89.8%, AI2D: 89.5%.

What are the context window sizes for DeepSeek-V4-Flash-0731 and Qwen3 VL 32B Instruct?

DeepSeek-V4-Flash-0731 supports 1.0M tokens and Qwen3 VL 32B Instruct 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-V4-Flash-0731 and Qwen3 VL 32B Instruct?

Key differences include LLM Stats Score (44.7 vs 20.3), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Flash-0731 and Qwen3 VL 32B Instruct?

DeepSeek-V4-Flash-0731 is developed by DeepSeek and Qwen3 VL 32B Instruct is developed by Alibaba Cloud / Qwen Team.

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