Model Comparison

DeepSeek R1 Distill Qwen 32B vs DeepSeek-V2.5

Comparing DeepSeek R1 Distill Qwen 32B and DeepSeek-V2.5 across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek R1 Distill Qwen 32B and DeepSeek-V2.5 don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

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 1.2x cheaper than DeepSeek-V2.5 ($0.14/1M tokens).

For output processing, DeepSeek R1 Distill Qwen 32B ($0.18/1M tokens) is 1.6x cheaper than DeepSeek-V2.5 ($0.28/1M tokens).

In conclusion, DeepSeek-V2.5 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 Apr 20 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Distill Qwen 32B
Input tokens$0.12
Output tokens$0.18
Best providerDeepinfra
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

203.2B diff

DeepSeek-V2.5 has 203.2B more parameters than DeepSeek R1 Distill Qwen 32B, making it 619.5% larger.

DeepSeek
DeepSeek R1 Distill Qwen 32B
32.8Bparameters
DeepSeek
DeepSeek-V2.5
236.0Bparameters
32.8B
DeepSeek R1 Distill Qwen 32B
236.0B
DeepSeek-V2.5

Context Window

Maximum input and output token capacity

DeepSeek R1 Distill Qwen 32B accepts 128,000 input tokens compared to DeepSeek-V2.5's 8,192 tokens. DeepSeek R1 Distill Qwen 32B can generate longer responses up to 128,000 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.

DeepSeek
DeepSeek R1 Distill Qwen 32B
Input128,000 tokens
Output128,000 tokens
DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Mon Apr 20 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Distill Qwen 32B is licensed under MIT, while DeepSeek-V2.5 uses deepseek.

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

DeepSeek R1 Distill Qwen 32B

MIT

Open weights

DeepSeek-V2.5

deepseek

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 32B was released on 2025-01-20, while DeepSeek-V2.5 was released on 2024-05-08.

DeepSeek R1 Distill Qwen 32B is 9 months newer than DeepSeek-V2.5.

DeepSeek R1 Distill Qwen 32B

Jan 20, 2025

1.2 years ago

8mo newer
DeepSeek-V2.5

May 8, 2024

2.0 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 R1 Distill Qwen 32B is available from DeepInfra. DeepSeek-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic.

DeepSeek R1 Distill Qwen 32B

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

DeepSeek-V2.5

deepseek logo
DeepSeek
Input Price:Input: $0.14/1MOutput Price:Output: $0.28/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.70/1MOutput Price:Output: $1.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $2.00/1MOutput Price:Output: $2.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (128,000 tokens)
Less expensive input tokens
Less expensive output tokens
DeepSeek

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 32B
DeepSeek
DeepSeek-V2.5

FAQ

Common questions about DeepSeek R1 Distill Qwen 32B vs DeepSeek-V2.5

DeepSeek R1 Distill Qwen 32B (DeepSeek) and DeepSeek-V2.5 (DeepSeek) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek R1 Distill Qwen 32B scores MATH-500: 94.3%, AIME 2024: 83.3%, GPQA: 62.1%, LiveCodeBench: 57.2%. DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%.
DeepSeek R1 Distill Qwen 32B is 1.2x cheaper for input tokens. DeepSeek R1 Distill Qwen 32B costs $0.12/M input and $0.18/M output via deepinfra. DeepSeek-V2.5 costs $0.14/M input and $0.28/M output via deepseek.
DeepSeek R1 Distill Qwen 32B supports 128K tokens and DeepSeek-V2.5 supports 8K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (128K vs 8K), input pricing ($0.12 vs $0.14/M), licensing (MIT vs deepseek). See the full comparison above for benchmark-by-benchmark results.