DeepSeek R1 Distill Llama 70B vs DeepSeek R1 Distill Qwen 1.5B Comparison

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek R1 Distill Llama 70B outperforms in 4 benchmarks (AIME 2024, GPQA, LiveCodeBench, MATH-500), while DeepSeek R1 Distill Qwen 1.5B is better at 0 benchmarks.

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

Wed Mar 18 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
Wed Mar 18 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Distill Llama 70B
Input tokens$0.10
Output tokens$0.40
Best providerDeepinfra
DeepSeek
DeepSeek R1 Distill Qwen 1.5B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

68.8B diff

DeepSeek R1 Distill Llama 70B has 68.8B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 3866.3% larger.

DeepSeek
DeepSeek R1 Distill Llama 70B
70.6Bparameters
DeepSeek
DeepSeek R1 Distill Qwen 1.5B
1.8Bparameters
70.6B
DeepSeek R1 Distill Llama 70B
1.8B
DeepSeek R1 Distill Qwen 1.5B

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
DeepSeek
DeepSeek R1 Distill Qwen 1.5B
Input- tokens
Output- tokens
Wed Mar 18 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 Llama 70B

MIT

Open weights

DeepSeek R1 Distill Qwen 1.5B

MIT

Open weights

Release Timeline

When each model was launched

Both models were released on 2025-01-20.

They likely represent similar generations of model development.

DeepSeek R1 Distill Llama 70B

Jan 20, 2025

1.2 years ago

DeepSeek R1 Distill Qwen 1.5B

Jan 20, 2025

1.2 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

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Key Takeaways

Larger context window (128,000 tokens)
Higher AIME 2024 score (86.7% vs 52.7%)
Higher GPQA score (65.2% vs 33.8%)
Higher LiveCodeBench score (57.5% vs 16.9%)
Higher MATH-500 score (94.5% vs 83.9%)

Detailed Comparison