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DeepSeek-V4.1-Flash-1017 vs Qwen3 VL 30B A3B Thinking

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 17.8. Qwen3 VL 30B A3B Thinking is 1.3x cheaper per token.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.2 to 17.8, ranking #15 overall.

On price, Qwen3 VL 30B A3B Thinking is roughly 1.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V4.1-Flash-1017 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

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

Choose DeepSeek-V4.1-Flash-1017

  • overall performance matters — it scores 51.2 and ranks #15 on LLM Stats
  • your work emphasizes reasoning and agents — it leads those capability indexes
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Oct 2026

Choose Qwen3 VL 30B A3B Thinking

  • cost matters — it's about 1.3x cheaper per token

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
Qwen3 VL 30B A3B Thinking
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
51.2
#15
17.8
#239
Reasoning
48.8
#18
19.1
#225
Agents
38.7
#8
7.0
#160
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
$0.20 / M
Output price
$1.20 / M
$0.99 / M
Context window
1,048,576
131,072

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
DeepSeek-V4.1-Flash-1017
Qwen3 VL 30B A3B Thinking
Math
31.8#69
22.3#149
Vision
32.3#25
12.1#123
Multimodal
35.0#14
14.8#109
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 50 for Qwen3 VL 30B A3B Thinking

No common benchmarks found

DeepSeek-V4.1-Flash-1017 and Qwen3 VL 30B A3B Thinkingdon'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

Pricing Analysis

Price comparison per million tokens

Qwen3 VL 30B A3B Thinking costs less

For input processing, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) is 1.5x more expensive than Qwen3 VL 30B A3B Thinking ($0.20/1M tokens).

For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 1.2x more expensive than Qwen3 VL 30B A3B Thinking ($0.99/1M tokens).

In conclusion, DeepSeek-V4.1-Flash-1017 is more expensive than Qwen3 VL 30B A3B Thinking.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Fri Oct 23 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash-1017
Input tokens$0.30
Output tokens$1.20
Best providerDeepSeek
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
Input tokens$0.20
Output tokens$0.99
Best providerNovita
Notice missing or incorrect data?

Model Size

Parameter count comparison

732.2B diff

DeepSeek-V4.1-Flash-1017 has 732.2B more parameters than Qwen3 VL 30B A3B Thinking, making it 2362.0% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
31.0Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
31.0B
Qwen3 VL 30B A3B Thinking

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to Qwen3 VL 30B A3B Thinking's 131,072 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while Qwen3 VL 30B A3B Thinking is limited to 32,768 tokens.

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
Input131,072 tokens
Output32,768 tokens
Fri Oct 23 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash-1017 and Qwen3 VL 30B A3B Thinking support multimodal inputs.

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

DeepSeek-V4.1-Flash-1017

Text
Images
Audio
Video

Qwen3 VL 30B A3B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 is licensed under MIT, while Qwen3 VL 30B A3B Thinking uses Apache 2.0.

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

DeepSeek-V4.1-Flash-1017

MIT

Open weights

Qwen3 VL 30B A3B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.

DeepSeek-V4.1-Flash-1017 is 13 months newer than Qwen3 VL 30B A3B Thinking.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

3 days ago

1.1yr newer
Qwen3 VL 30B A3B Thinking

Sep 22, 2025

1.1 years 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

Provider Availability

DeepSeek-V4.1-Flash-1017 is available from DeepSeek. Qwen3 VL 30B A3B Thinking is available from Novita, DeepInfra.

DeepSeek-V4.1-Flash-1017

deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

Qwen3 VL 30B A3B Thinking

novita logo
Novita
Input Price:Input: $0.20/1MOutput Price:Output: $1.00/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.29/1MOutput Price:Output: $0.99/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
Qwen3 VL 30B A3B Thinking
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs Qwen3 VL 30B A3B Thinking.

Which is better, DeepSeek-V4.1-Flash-1017 or Qwen3 VL 30B A3B Thinking?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 17.8. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and Qwen3 VL 30B A3B Thinking 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-V4.1-Flash-1017 compare to Qwen3 VL 30B A3B Thinking in benchmarks?

DeepSeek-V4.1-Flash-1017 scores BabyVision: 92.5%, Chartography: 83.0%, DeepSWE 1.1: 77.0%, NL2Repo: 68.2%, AutomationBench: 60.5%. Qwen3 VL 30B A3B Thinking scores DocVQAtest: 95.0%, ScreenSpot: 94.7%, MMLU-Redux: 90.9%, MMBench-V1.1: 88.9%, MMLU: 87.6%.

Is DeepSeek-V4.1-Flash-1017 cheaper than Qwen3 VL 30B A3B Thinking?

Qwen3 VL 30B A3B Thinking is 1.5x cheaper for input tokens. DeepSeek-V4.1-Flash-1017 costs $0.30/M input and $1.20/M output via deepseek. Qwen3 VL 30B A3B Thinking costs $0.20/M input and $0.99/M output via novita.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and Qwen3 VL 30B A3B Thinking?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and Qwen3 VL 30B A3B Thinking supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V4.1-Flash-1017 and Qwen3 VL 30B A3B Thinking?

Key differences include LLM Stats Score (51.2 vs 17.8), context window (1.0M vs 131K), input pricing ($0.30 vs $0.20/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and Qwen3 VL 30B A3B Thinking?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and Qwen3 VL 30B A3B Thinking is developed by Alibaba Cloud / Qwen Team.

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