Model Comparison

DeepSeek R1 Distill Qwen 32B vs DeepSeek-V3.2 (Thinking)

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks. DeepSeek R1 Distill Qwen 32B is 2.3x cheaper per token.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek R1 Distill Qwen 32B outperforms in 0 benchmarks, while DeepSeek-V3.2 (Thinking) is better at 2 benchmarks (GPQA, LiveCodeBench).

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks.

Mon May 04 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek R1 Distill Qwen 32B costs less

For input processing, DeepSeek R1 Distill Qwen 32B ($0.12/1M tokens) is 2.3x cheaper than DeepSeek-V3.2 (Thinking) ($0.28/1M tokens).

For output processing, DeepSeek R1 Distill Qwen 32B ($0.18/1M tokens) is 2.3x cheaper than DeepSeek-V3.2 (Thinking) ($0.42/1M tokens).

In conclusion, DeepSeek-V3.2 (Thinking) is more expensive than DeepSeek R1 Distill Qwen 32B.*

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

Lowest available price from all providers
Mon May 04 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Distill Qwen 32B
Input tokens$0.12
Output tokens$0.18
Best providerDeepinfra
DeepSeek
DeepSeek-V3.2 (Thinking)
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

652.2B diff

DeepSeek-V3.2 (Thinking) has 652.2B more parameters than DeepSeek R1 Distill Qwen 32B, making it 1988.4% larger.

DeepSeek
DeepSeek R1 Distill Qwen 32B
32.8Bparameters
DeepSeek
DeepSeek-V3.2 (Thinking)
685.0Bparameters
32.8B
DeepSeek R1 Distill Qwen 32B
685.0B
DeepSeek-V3.2 (Thinking)

Context Window

Maximum input and output token capacity

DeepSeek-V3.2 (Thinking) accepts 131,072 input tokens compared to DeepSeek R1 Distill Qwen 32B's 128,000 tokens. DeepSeek R1 Distill Qwen 32B can generate longer responses up to 128,000 tokens, while DeepSeek-V3.2 (Thinking) is limited to 65,536 tokens.

DeepSeek
DeepSeek R1 Distill Qwen 32B
Input128,000 tokens
Output128,000 tokens
DeepSeek
DeepSeek-V3.2 (Thinking)
Input131,072 tokens
Output65,536 tokens
Mon May 04 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

DeepSeek R1 Distill Qwen 32B

MIT

Open weights

DeepSeek-V3.2 (Thinking)

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 32B was released on 2025-01-20, while DeepSeek-V3.2 (Thinking) was released on 2025-12-01.

DeepSeek-V3.2 (Thinking) is 11 months newer than DeepSeek R1 Distill Qwen 32B.

DeepSeek R1 Distill Qwen 32B

Jan 20, 2025

1.3 years ago

DeepSeek-V3.2 (Thinking)

Dec 1, 2025

5 months ago

10mo newer

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 R1 Distill Qwen 32B is available from DeepInfra. DeepSeek-V3.2 (Thinking) is available from DeepSeek.

DeepSeek R1 Distill Qwen 32B

deepinfra logo
Deepinfra
Input Price:Input: $0.12/1MOutput Price:Output: $0.18/1M

DeepSeek-V3.2 (Thinking)

deepseek logo
DeepSeek
Input Price:Input: $0.28/1MOutput Price:Output: $0.42/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Less expensive input tokens
Less expensive output tokens
DeepSeek
Larger context window (131,072 tokens)
Higher GPQA score (82.4% vs 62.1%)
Higher LiveCodeBench score (83.3% vs 57.2%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 32B
DeepSeek
DeepSeek-V3.2 (Thinking)

FAQ

Common questions about DeepSeek R1 Distill Qwen 32B vs DeepSeek-V3.2 (Thinking).

Which is better, DeepSeek R1 Distill Qwen 32B or DeepSeek-V3.2 (Thinking)?

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks. DeepSeek R1 Distill Qwen 32B is made by DeepSeek and DeepSeek-V3.2 (Thinking) is made by DeepSeek. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek R1 Distill Qwen 32B compare to DeepSeek-V3.2 (Thinking) in benchmarks?

DeepSeek R1 Distill Qwen 32B scores MATH-500: 94.3%, AIME 2024: 83.3%, GPQA: 62.1%, LiveCodeBench: 57.2%. DeepSeek-V3.2 (Thinking) scores AIME 2025: 93.1%, HMMT 2025: 90.2%, MMLU-Pro: 85.0%, LiveCodeBench: 83.3%, GPQA: 82.4%.

Is DeepSeek R1 Distill Qwen 32B cheaper than DeepSeek-V3.2 (Thinking)?

DeepSeek R1 Distill Qwen 32B is 2.3x cheaper for input tokens. DeepSeek R1 Distill Qwen 32B costs $0.12/M input and $0.18/M output via deepinfra. DeepSeek-V3.2 (Thinking) costs $0.28/M input and $0.42/M output via deepseek.

What are the context window sizes for DeepSeek R1 Distill Qwen 32B and DeepSeek-V3.2 (Thinking)?

DeepSeek R1 Distill Qwen 32B supports 128K tokens and DeepSeek-V3.2 (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 R1 Distill Qwen 32B and DeepSeek-V3.2 (Thinking)?

Key differences include context window (128K vs 131K), input pricing ($0.12 vs $0.28/M). See the full comparison above for benchmark-by-benchmark results.