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DeepSeek-V4.1-Flash-1017 vs QwQ-32B-Preview

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 8.5. QwQ-32B-Preview is 3.2x 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 8.5, ranking #15 overall.

On price, QwQ-32B-Preview is roughly 3.2x 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 coding — 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 QwQ-32B-Preview

  • cost matters — it's about 3.2x cheaper per token

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
QwQ-32B-Preview
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
51.2
#15
8.5
#299
Reasoning
48.8
#18
8.8
#289
Coding
39.3
#14
4.3
#229
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
$0.15 / M
Output price
$1.20 / M
$0.20 / M
Context window
1,048,576
32,768

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash-1017
QwQ-32B-Preview
Math
31.8#69
8.8#268
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 4 for QwQ-32B-Preview

No common benchmarks found

DeepSeek-V4.1-Flash-1017 and QwQ-32B-Previewdon'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

QwQ-32B-Preview costs less

For input processing, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) is 2.0x more expensive than QwQ-32B-Preview ($0.15/1M tokens).

For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 6.0x more expensive than QwQ-32B-Preview ($0.20/1M tokens).

In conclusion, DeepSeek-V4.1-Flash-1017 is more expensive than QwQ-32B-Preview.*

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

Lowest available price from all providers
Thu Oct 22 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash-1017
Input tokens$0.30
Output tokens$1.20
Best providerDeepSeek
Alibaba Cloud / Qwen Team
QwQ-32B-Preview
Input tokens$0.15
Output tokens$0.20
Best providerDeepinfra
Notice missing or incorrect data?

Model Size

Parameter count comparison

730.7B diff

DeepSeek-V4.1-Flash-1017 has 730.7B more parameters than QwQ-32B-Preview, making it 2248.3% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
Alibaba Cloud / Qwen Team
QwQ-32B-Preview
32.5Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
32.5B
QwQ-32B-Preview

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to QwQ-32B-Preview's 32,768 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while QwQ-32B-Preview is limited to 32,768 tokens.

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
Alibaba Cloud / Qwen Team
QwQ-32B-Preview
Input32,768 tokens
Output32,768 tokens
Thu Oct 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash-1017 supports multimodal inputs, whereas QwQ-32B-Preview does not.

DeepSeek-V4.1-Flash-1017 can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4.1-Flash-1017

Text
Images
Audio
Video

QwQ-32B-Preview

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 is licensed under MIT, while QwQ-32B-Preview 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

QwQ-32B-Preview

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while QwQ-32B-Preview was released on 2024-11-28.

DeepSeek-V4.1-Flash-1017 is 23 months newer than QwQ-32B-Preview.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

2 days ago

1.9yr newer
QwQ-32B-Preview

Nov 28, 2024

1.9 years ago

Knowledge Cutoff

When training data ends

QwQ-32B-Preview has a documented knowledge cutoff of 2024-11-28, while DeepSeek-V4.1-Flash-1017's cutoff date is not specified.

We can confirm QwQ-32B-Preview's training data extends to 2024-11-28, but cannot make a direct comparison without DeepSeek-V4.1-Flash-1017's cutoff date.

DeepSeek-V4.1-Flash-1017

—

QwQ-32B-Preview

Nov 2024

Provider Availability

DeepSeek-V4.1-Flash-1017 is available from DeepSeek. QwQ-32B-Preview is available from DeepInfra, Hyperbolic, Fireworks, Together.

DeepSeek-V4.1-Flash-1017

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

QwQ-32B-Preview

deepinfra logo
Deepinfra
Input Price:Input: $0.15/1MOutput Price:Output: $0.60/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
together logo
Together
Input Price:Input: $1.20/1MOutput Price:Output: $1.20/1M
* 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 QwQ-32B-Preview side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
QwQ-32B-Preview
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs QwQ-32B-Preview.

Which is better, DeepSeek-V4.1-Flash-1017 or QwQ-32B-Preview?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 8.5. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and QwQ-32B-Preview 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 QwQ-32B-Preview 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%. QwQ-32B-Preview scores MATH-500: 90.6%, GPQA: 65.2%, AIME 2024: 50.0%, LiveCodeBench: 50.0%.

Is DeepSeek-V4.1-Flash-1017 cheaper than QwQ-32B-Preview?

QwQ-32B-Preview is 2.0x cheaper for input tokens. DeepSeek-V4.1-Flash-1017 costs $0.30/M input and $1.20/M output via deepseek. QwQ-32B-Preview costs $0.15/M input and $0.20/M output via deepinfra.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and QwQ-32B-Preview?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and QwQ-32B-Preview supports 33K 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 QwQ-32B-Preview?

Key differences include LLM Stats Score (51.2 vs 8.5), context window (1.0M vs 33K), input pricing ($0.30 vs $0.15/M), multimodal support (yes vs no), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and QwQ-32B-Preview?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and QwQ-32B-Preview is developed by Alibaba Cloud / Qwen Team.

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