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Llama 3.3 70B Instruct vs Qwen3.8-27B

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

Meta · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Llama 3.3 70B Instruct 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 Llama 3.3 70B Instruct

  • you want predictable pricing at $0.20/M input and $0.20/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
$0.20 / M
— / M
Output price
$0.20 / M
— / M
Context window
128,000
Released
Dec 2024
Aug 2026
License
Llama 3.3 Community License Agreement
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Llama 3.3 70B Instruct 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

42.2B diff

Llama 3.3 70B Instruct has 42.2B more parameters than Qwen3.8-27B, making it 152.0% larger.

Meta
Llama 3.3 70B Instruct
70.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-27B
27.8Bparameters
70.0B
Llama 3.3 70B Instruct
27.8B
Qwen3.8-27B

Context Window

Maximum input and output token capacity

Only Llama 3.3 70B Instruct specifies input context (128,000 tokens). Only Llama 3.3 70B Instruct specifies output context (128,000 tokens).

Meta
Llama 3.3 70B Instruct
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 Llama 3.3 70B Instruct does not.

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

Llama 3.3 70B Instruct

Text
Images
Audio
Video

Qwen3.8-27B

Text
Images
Audio
Video

License

Usage and distribution terms

Llama 3.3 70B Instruct is licensed under Llama 3.3 Community License Agreement, while Qwen3.8-27B uses Apache 2.0.

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

Llama 3.3 70B Instruct

Llama 3.3 Community License Agreement

Open weights

Qwen3.8-27B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Llama 3.3 70B Instruct was released on 2024-12-06, while Qwen3.8-27B was released on 2026-08-14.

Qwen3.8-27B is 21 months newer than Llama 3.3 70B Instruct.

Llama 3.3 70B Instruct

Dec 6, 2024

1.7 years ago

Qwen3.8-27B

Aug 14, 2026

1 weeks ago

1.7yr 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 Llama 3.3 70B Instruct and Qwen3.8-27B side-by-side, then vote on the output you prefer.

Llama 3.3 70B Instruct
✓ Preferred
Qwen3.8-27B
Open in Playground

FAQ

Common questions about Llama 3.3 70B Instruct vs Qwen3.8-27B.

Which is better, Llama 3.3 70B Instruct or Qwen3.8-27B?

Qwen3.8-27B significantly outperforms across most benchmarks. Llama 3.3 70B Instruct is made by Meta 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 Llama 3.3 70B Instruct compare to Qwen3.8-27B in benchmarks?

Llama 3.3 70B Instruct scores IFEval: 92.1%, MGSM: 91.1%, HumanEval: 88.4%, MBPP EvalPlus: 87.6%, MMLU: 86.0%. 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 Llama 3.3 70B Instruct and Qwen3.8-27B?

Llama 3.3 70B Instruct 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 Llama 3.3 70B Instruct and Qwen3.8-27B?

Key differences include multimodal support (no vs yes), licensing (Llama 3.3 Community License Agreement vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Llama 3.3 70B Instruct and Qwen3.8-27B?

Llama 3.3 70B Instruct is developed by Meta and Qwen3.8-27B is developed by Alibaba Cloud / Qwen Team.