Model Comparison

DeepSeek R1 Distill Llama 70B vs Qwen2.5 14B Instruct

DeepSeek R1 Distill Llama 70B significantly outperforms across most benchmarks.

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek R1 Distill Llama 70B outperforms in 1 benchmarks (GPQA), while Qwen2.5 14B Instruct is better at 0 benchmarks.

DeepSeek R1 Distill Llama 70B significantly outperforms across most benchmarks.

Thu Jun 04 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

55.9B diff

DeepSeek R1 Distill Llama 70B has 55.9B more parameters than Qwen2.5 14B Instruct, making it 380.3% larger.

DeepSeek
DeepSeek R1 Distill Llama 70B
70.6Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 14B Instruct
14.7Bparameters
70.6B
DeepSeek R1 Distill Llama 70B
14.7B
Qwen2.5 14B Instruct

Context Window

Maximum input and output token capacity

Only DeepSeek R1 Distill Llama 70B specifies input context (128,000 tokens). Only DeepSeek R1 Distill Llama 70B specifies output context (128,000 tokens).

DeepSeek
DeepSeek R1 Distill Llama 70B
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 14B Instruct
Input- tokens
Output- tokens
Thu Jun 04 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Distill Llama 70B is licensed under MIT, while Qwen2.5 14B Instruct uses Apache 2.0.

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

DeepSeek R1 Distill Llama 70B

MIT

Open weights

Qwen2.5 14B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Llama 70B was released on 2025-01-20, while Qwen2.5 14B Instruct was released on 2024-09-19.

DeepSeek R1 Distill Llama 70B is 4 months newer than Qwen2.5 14B Instruct.

DeepSeek R1 Distill Llama 70B

Jan 20, 2025

1.4 years ago

4mo newer
Qwen2.5 14B Instruct

Sep 19, 2024

1.7 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

Larger context window (128,000 tokens)
Higher GPQA score (65.2% vs 45.5%)
Alibaba Cloud / Qwen Team

Qwen2.5 14B Instruct

View details

Alibaba Cloud / Qwen Team

No standout differentiators in the data we have for this pair.

Detailed Comparison

FAQ

Common questions about DeepSeek R1 Distill Llama 70B vs Qwen2.5 14B Instruct.

Which is better, DeepSeek R1 Distill Llama 70B or Qwen2.5 14B Instruct?

DeepSeek R1 Distill Llama 70B significantly outperforms across most benchmarks. DeepSeek R1 Distill Llama 70B is made by DeepSeek and Qwen2.5 14B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek R1 Distill Llama 70B compare to Qwen2.5 14B Instruct in benchmarks?

DeepSeek R1 Distill Llama 70B scores MATH-500: 94.5%, AIME 2024: 86.7%, GPQA: 65.2%, LiveCodeBench: 57.5%. Qwen2.5 14B Instruct scores GSM8k: 94.8%, HumanEval: 83.5%, MBPP: 82.0%, MATH: 80.0%, MMLU-Redux: 80.0%.

What are the context window sizes for DeepSeek R1 Distill Llama 70B and Qwen2.5 14B Instruct?

DeepSeek R1 Distill Llama 70B supports 128K tokens and Qwen2.5 14B Instruct 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 Distill Llama 70B and Qwen2.5 14B Instruct?

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

Who makes DeepSeek R1 Distill Llama 70B and Qwen2.5 14B Instruct?

DeepSeek R1 Distill Llama 70B is developed by DeepSeek and Qwen2.5 14B Instruct is developed by Alibaba Cloud / Qwen Team.