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DeepSeek R1 Distill Llama 70B vs Qwen3.8-27B

Qwen3.8-27B significantly outperforms across most benchmarks.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek R1 Distill Llama 70B outperforms in 0 benchmarks, while Qwen3.8-27B is better at 1 benchmark (GPQA). Qwen3.8-27B significantly outperforms across most benchmarks.

Based on current benchmark, pricing, and model metadata for 2026.

Choose DeepSeek R1 Distill Llama 70B

  • you want predictable pricing at $0.10/M input and $0.40/M output

Choose Qwen3.8-27B

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Benchmark wins
0 of 1
1 of 1
Input price
$0.10 / M
— / M
Output price
$0.40 / M
— / M
Context window
128,000
Released
Jan 2025
Aug 2026
License
MIT
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek R1 Distill Llama 70B outperforms in 0 benchmarks, while Qwen3.8-27B is better at 1 benchmark (GPQA).

Qwen3.8-27B significantly outperforms across most benchmarks.

Mon Aug 24 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

42.8B diff

DeepSeek R1 Distill Llama 70B has 42.8B more parameters than Qwen3.8-27B, making it 154.1% larger.

DeepSeek
DeepSeek R1 Distill Llama 70B
70.6Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-27B
27.8Bparameters
70.6B
DeepSeek R1 Distill Llama 70B
27.8B
Qwen3.8-27B

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
Qwen3.8-27B
Input- tokens
Output- tokens
Mon Aug 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3.8-27B supports multimodal inputs, whereas DeepSeek R1 Distill Llama 70B does not.

Qwen3.8-27B can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek R1 Distill Llama 70B

Text
Images
Audio
Video

Qwen3.8-27B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Distill Llama 70B is licensed under MIT, while Qwen3.8-27B 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

Qwen3.8-27B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Llama 70B was released on 2025-01-20, while Qwen3.8-27B was released on 2026-08-14.

Qwen3.8-27B is 19 months newer than DeepSeek R1 Distill Llama 70B.

DeepSeek R1 Distill Llama 70B

Jan 20, 2025

1.6 years ago

Qwen3.8-27B

Aug 14, 2026

1 weeks ago

1.6yr 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

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek R1 Distill Llama 70B and Qwen3.8-27B side-by-side, then vote on the output you prefer.

DeepSeek R1 Distill Llama 70B
✓ Preferred
Qwen3.8-27B
Open in Playground

FAQ

Common questions about DeepSeek R1 Distill Llama 70B vs Qwen3.8-27B.

Which is better, DeepSeek R1 Distill Llama 70B or Qwen3.8-27B?

Qwen3.8-27B significantly outperforms across most benchmarks. DeepSeek R1 Distill Llama 70B is made by DeepSeek and Qwen3.8-27B 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 Qwen3.8-27B in benchmarks?

DeepSeek R1 Distill Llama 70B scores MATH-500: 94.5%, AIME 2024: 86.7%, GPQA: 65.2%, LiveCodeBench: 57.5%. Qwen3.8-27B scores MathVision: 94.6%, OmniDocBench 1.5: 91.1%, LiveCodeBench v6: 90.3%, CharXiv-R: 90.2%, GPQA: 89.2%.

What are the context window sizes for DeepSeek R1 Distill Llama 70B and Qwen3.8-27B?

DeepSeek R1 Distill Llama 70B supports 128K tokens and Qwen3.8-27B 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 Qwen3.8-27B?

Key differences include multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Distill Llama 70B and Qwen3.8-27B?

DeepSeek R1 Distill Llama 70B is developed by DeepSeek and Qwen3.8-27B is developed by Alibaba Cloud / Qwen Team.