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

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 9.0. QwQ-32B-Preview is 2.0x cheaper per token.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 9.0, ranking #12 overall.

In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 1; this is a narrower head-to-head signal than the composite indexes.

On price, QwQ-32B-Preview is roughly 2.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V4.1-Flash also accepts a larger context window (1,040,000 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

  • overall performance matters — it scores 51.8 and ranks #12 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 process long inputs — it offers a 1,040,000 token context window
  • you want the most recent training data — it shipped Sep 2026

Choose QwQ-32B-Preview

  • cost matters — it's about 2.0x cheaper per token

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash
DeepSeek
QwQ-32B-Preview
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
51.8
#12
9.0
#271
Reasoning
48.9
#17
9.3
#261
Coding
44.4
#5
4.4
#206
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.22 / M
$0.15 / M
Output price
$0.66 / M
$0.20 / M
Context window
1,040,000
32,768

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash
QwQ-32B-Preview
Math
35.2#43
8.9#255
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

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

1 shared

DeepSeek-V4.1-Flash outperforms in 1 benchmarks (GPQA), while QwQ-32B-Preview is better at 0 benchmarks.

DeepSeek-V4.1-Flash significantly outperforms across most benchmarks.

Sun Sep 13 2026 • llm-stats.com

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 ($0.22/1M tokens) is 1.5x more expensive than QwQ-32B-Preview ($0.15/1M tokens).

For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 3.3x more expensive than QwQ-32B-Preview ($0.20/1M tokens).

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

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

Lowest available price from all providers
Sun Sep 13 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash
Input tokens$0.22
Output tokens$0.66
Best providerFireworks
Alibaba Cloud / Qwen Team
QwQ-32B-Preview
Input tokens$0.15
Output tokens$0.20
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

730.7B diff

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

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

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash accepts 1,040,000 input tokens compared to QwQ-32B-Preview's 32,768 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while QwQ-32B-Preview is limited to 32,768 tokens.

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
Alibaba Cloud / Qwen Team
QwQ-32B-Preview
Input32,768 tokens
Output32,768 tokens
Sun Sep 13 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

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

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

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

QwQ-32B-Preview

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash 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

MIT

Open weights

QwQ-32B-Preview

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while QwQ-32B-Preview was released on 2024-11-28.

DeepSeek-V4.1-Flash is 22 months newer than QwQ-32B-Preview.

DeepSeek-V4.1-Flash

Sep 10, 2026

3 days ago

1.8yr newer
QwQ-32B-Preview

Nov 28, 2024

1.8 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'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's cutoff date.

DeepSeek-V4.1-Flash

—

QwQ-32B-Preview

Nov 2024

Provider Availability

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

DeepSeek-V4.1-Flash

fireworks logo
Fireworks
Input Price:Input: $0.22/1MOutput Price:Output: $0.66/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
novita logo
Novita
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?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash and QwQ-32B-Preview side-by-side, then vote on the output you prefer.

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

FAQ

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

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

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 9.0. DeepSeek-V4.1-Flash 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 compare to QwQ-32B-Preview in benchmarks?

DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%. QwQ-32B-Preview scores MATH-500: 90.6%, GPQA: 65.2%, AIME 2024: 50.0%, LiveCodeBench: 50.0%.

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

QwQ-32B-Preview is 1.5x cheaper for input tokens. DeepSeek-V4.1-Flash costs $0.22/M input and $0.66/M output via fireworks. 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 and QwQ-32B-Preview?

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

Key differences include LLM Stats Score (51.8 vs 9.0), context window (1.0M vs 33K), input pricing ($0.22 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 and QwQ-32B-Preview?

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

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