Model Comparison

DeepSeek-V3 vs DeepSeek R1 Distill Qwen 14B

DeepSeek R1 Distill Qwen 14B shows notably better performance in the majority of benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek-V3 outperforms in 0 benchmarks, while DeepSeek R1 Distill Qwen 14B is better at 3 benchmarks (AIME 2024, LiveCodeBench, MATH-500).

DeepSeek R1 Distill Qwen 14B shows notably better performance in the majority of benchmarks.

Thu Apr 30 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Thu Apr 30 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
DeepSeek
DeepSeek R1 Distill Qwen 14B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

656.2B diff

DeepSeek-V3 has 656.2B more parameters than DeepSeek R1 Distill Qwen 14B, making it 4433.8% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
DeepSeek
DeepSeek R1 Distill Qwen 14B
14.8Bparameters
671.0B
DeepSeek-V3
14.8B
DeepSeek R1 Distill Qwen 14B

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 specifies input context (131,072 tokens). Only DeepSeek-V3 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
DeepSeek
DeepSeek R1 Distill Qwen 14B
Input- tokens
Output- tokens
Thu Apr 30 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while DeepSeek R1 Distill Qwen 14B uses MIT.

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

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

DeepSeek R1 Distill Qwen 14B

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while DeepSeek R1 Distill Qwen 14B was released on 2025-01-20.

DeepSeek R1 Distill Qwen 14B is 1 month newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.3 years ago

DeepSeek R1 Distill Qwen 14B

Jan 20, 2025

1.3 years ago

3w 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

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
DeepSeek
Higher AIME 2024 score (80.0% vs 39.2%)
Higher LiveCodeBench score (53.1% vs 37.6%)
Higher MATH-500 score (93.9% vs 90.2%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
DeepSeek
DeepSeek R1 Distill Qwen 14B

FAQ

Common questions about DeepSeek-V3 vs DeepSeek R1 Distill Qwen 14B

DeepSeek R1 Distill Qwen 14B shows notably better performance in the majority of benchmarks. DeepSeek-V3 is made by DeepSeek and DeepSeek R1 Distill Qwen 14B is made by DeepSeek. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. DeepSeek R1 Distill Qwen 14B scores MATH-500: 93.9%, AIME 2024: 80.0%, GPQA: 59.1%, LiveCodeBench: 53.1%.
DeepSeek-V3 supports 131K tokens and DeepSeek R1 Distill Qwen 14B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (MIT + Model License (Commercial use allowed) vs MIT). See the full comparison above for benchmark-by-benchmark results.