Model Comparison

DeepSeek R1 Distill Qwen 14B vs DeepSeek-V3 0324

Both models are evenly matched across the benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek R1 Distill Qwen 14B outperforms in 2 benchmarks (AIME 2024, LiveCodeBench), while DeepSeek-V3 0324 is better at 2 benchmarks (GPQA, MATH-500).

Both models are evenly matched across the benchmarks.

Sun Apr 26 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
Sun Apr 26 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Distill Qwen 14B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
DeepSeek
DeepSeek-V3 0324
Input tokens$0.28
Output tokens$1.14
Best providerNovita
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

656.2B diff

DeepSeek-V3 0324 has 656.2B more parameters than DeepSeek R1 Distill Qwen 14B, making it 4433.8% larger.

DeepSeek
DeepSeek R1 Distill Qwen 14B
14.8Bparameters
DeepSeek
DeepSeek-V3 0324
671.0Bparameters
14.8B
DeepSeek R1 Distill Qwen 14B
671.0B
DeepSeek-V3 0324

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 0324 specifies input context (163,840 tokens). Only DeepSeek-V3 0324 specifies output context (163,840 tokens).

DeepSeek
DeepSeek R1 Distill Qwen 14B
Input- tokens
Output- tokens
DeepSeek
DeepSeek-V3 0324
Input163,840 tokens
Output163,840 tokens
Sun Apr 26 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Distill Qwen 14B is licensed under MIT, while DeepSeek-V3 0324 uses MIT + Model License (Commercial use allowed).

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

DeepSeek R1 Distill Qwen 14B

MIT

Open weights

DeepSeek-V3 0324

MIT + Model License (Commercial use allowed)

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 14B was released on 2025-01-20, while DeepSeek-V3 0324 was released on 2025-03-25.

DeepSeek-V3 0324 is 2 months newer than DeepSeek R1 Distill Qwen 14B.

DeepSeek R1 Distill Qwen 14B

Jan 20, 2025

1.3 years ago

DeepSeek-V3 0324

Mar 25, 2025

1.1 years ago

2mo 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
Higher AIME 2024 score (80.0% vs 59.4%)
Higher LiveCodeBench score (53.1% vs 49.2%)
DeepSeek
Larger context window (163,840 tokens)
Higher GPQA score (68.4% vs 59.1%)
Higher MATH-500 score (94.0% vs 93.9%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 14B
DeepSeek
DeepSeek-V3 0324

FAQ

Common questions about DeepSeek R1 Distill Qwen 14B vs DeepSeek-V3 0324

Both models are evenly matched across the benchmarks. DeepSeek R1 Distill Qwen 14B is made by DeepSeek and DeepSeek-V3 0324 is made by DeepSeek. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek R1 Distill Qwen 14B scores MATH-500: 93.9%, AIME 2024: 80.0%, GPQA: 59.1%, LiveCodeBench: 53.1%. DeepSeek-V3 0324 scores MATH-500: 94.0%, MMLU-Pro: 81.2%, GPQA: 68.4%, AIME 2024: 59.4%, LiveCodeBench: 49.2%.
DeepSeek R1 Distill Qwen 14B supports an unknown number of tokens and DeepSeek-V3 0324 supports 164K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (MIT vs MIT + Model License (Commercial use allowed)). See the full comparison above for benchmark-by-benchmark results.