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DeepSeek-R1 vs QwQ-32B

Comparing DeepSeek-R1 and QwQ-32B across benchmarks, pricing, and capabilities.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-R1 and QwQ-32B trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current benchmark, pricing, and model metadata for 2026.

Choose DeepSeek-R1

  • you want predictable pricing at $0.55/M input and $2.19/M output

Choose QwQ-32B

  • you want the most recent training data — it shipped Mar 2025

At a glance

The differences that matter most.

Benchmark wins
Input price
$0.55 / M
— / M
Output price
$2.19 / M
— / M
Context window
131,072
Released
Jan 2025
Mar 2025
License
MIT
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1 and QwQ-32Bdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

638.5B diff

DeepSeek-R1 has 638.5B more parameters than QwQ-32B, making it 1964.6% larger.

DeepSeek
DeepSeek-R1
671.0Bparameters
Alibaba Cloud / Qwen Team
QwQ-32B
32.5Bparameters
671.0B
DeepSeek-R1
32.5B
QwQ-32B

Context Window

Maximum input and output token capacity

Only DeepSeek-R1 specifies input context (131,072 tokens). Only DeepSeek-R1 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
QwQ-32B
Input- tokens
Output- tokens
Wed Aug 26 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1 is licensed under MIT, while QwQ-32B uses Apache 2.0.

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

DeepSeek-R1

MIT

Open weights

QwQ-32B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while QwQ-32B was released on 2025-03-05.

QwQ-32B is 1 month newer than DeepSeek-R1.

DeepSeek-R1

Jan 20, 2025

1.6 years ago

QwQ-32B

Mar 5, 2025

1.5 years ago

1mo newer

Knowledge Cutoff

When training data ends

QwQ-32B has a documented knowledge cutoff of 2024-11-28, while DeepSeek-R1's cutoff date is not specified.

We can confirm QwQ-32B's training data extends to 2024-11-28, but cannot make a direct comparison without DeepSeek-R1's cutoff date.

DeepSeek-R1

QwQ-32B

Nov 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek-R1 and QwQ-32B side-by-side, then vote on the output you prefer.

DeepSeek-R1
✓ Preferred
QwQ-32B
Open in Playground

FAQ

Common questions about DeepSeek-R1 vs QwQ-32B.

Which is better, DeepSeek-R1 or QwQ-32B?

DeepSeek-R1 (DeepSeek) and QwQ-32B (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek-R1 compare to QwQ-32B in benchmarks?

QwQ-32B scores MATH-500: 90.6%, IFEval: 83.9%, AIME 2024: 79.5%, LiveBench: 73.1%, BFCL: 66.4%.

What are the context window sizes for DeepSeek-R1 and QwQ-32B?

DeepSeek-R1 supports 131K tokens and QwQ-32B 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-R1 and QwQ-32B?

Key differences include licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-R1 and QwQ-32B?

DeepSeek-R1 is developed by DeepSeek and QwQ-32B is developed by Alibaba Cloud / Qwen Team.