Model Comparison

Llama 4 Scout vs Qwen2.5-Coder 7B Instruct

Llama 4 Scout significantly outperforms across most benchmarks.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

Llama 4 Scout outperforms in 4 benchmarks (LiveCodeBench, MATH, MMLU, MMLU-Pro), while Qwen2.5-Coder 7B Instruct is better at 1 benchmark (MBPP).

Llama 4 Scout significantly outperforms across most benchmarks.

Mon May 25 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

102.0B diff

Llama 4 Scout has 102.0B more parameters than Qwen2.5-Coder 7B Instruct, making it 1457.1% larger.

Llama 4 Scout

109.0Bparameters

Qwen2.5-Coder 7B Instruct

7.0Bparameters

109.0B

Llama 4 Scout

7.0B

Qwen2.5-Coder 7B Instruct

Context Window

Maximum input and output token capacity

Only Llama 4 Scout specifies input context (10,000,000 tokens). Only Llama 4 Scout specifies output context (10,000,000 tokens).

Llama 4 Scout

Input10,000,000 tokens

Output10,000,000 tokens

Qwen2.5-Coder 7B Instruct

Input- tokens

Output- tokens

Mon May 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Llama 4 Scout supports multimodal inputs, whereas Qwen2.5-Coder 7B Instruct does not.

Llama 4 Scout can handle both text and other forms of data like images, making it suitable for multimodal applications.

Llama 4 Scout

Text

Images

Audio

Video

Qwen2.5-Coder 7B Instruct

Text

Images

Audio

Video

License

Usage and distribution terms

Llama 4 Scout is licensed under Llama 4 Community License Agreement, while Qwen2.5-Coder 7B Instruct uses Apache 2.0.

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

Llama 4 Scout

Llama 4 Community License Agreement

Open weights

Qwen2.5-Coder 7B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Llama 4 Scout was released on 2025-04-05, while Qwen2.5-Coder 7B Instruct was released on 2024-09-19.

Llama 4 Scout is 7 months newer than Qwen2.5-Coder 7B Instruct.

Llama 4 Scout

Apr 5, 2025

1.1 years ago

6mo newer

Qwen2.5-Coder 7B 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

Qwen2.5-Coder 7B Instruct

View details

Alibaba Cloud / Qwen Team

Higher MBPP score (83.5% vs 67.8%)

Detailed Comparison

AI Model Comparison Table
Feature	Llama 4 Scout	Qwen2.5-Coder 7B Instruct

FAQ

Common questions about Llama 4 Scout vs Qwen2.5-Coder 7B Instruct.

Which is better, Llama 4 Scout or Qwen2.5-Coder 7B Instruct?

Llama 4 Scout significantly outperforms across most benchmarks. Llama 4 Scout is made by Meta and Qwen2.5-Coder 7B 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 Llama 4 Scout compare to Qwen2.5-Coder 7B Instruct in benchmarks?

Llama 4 Scout scores DocVQA: 94.4%, MGSM: 90.6%, ChartQA: 88.8%, MMLU: 79.6%, MMLU-Pro: 74.3%. Qwen2.5-Coder 7B Instruct scores HumanEval: 88.4%, GSM8k: 83.9%, MBPP: 83.5%, HellaSwag: 76.8%, Winogrande: 72.9%.

What are the context window sizes for Llama 4 Scout and Qwen2.5-Coder 7B Instruct?

Llama 4 Scout supports 10.0M tokens and Qwen2.5-Coder 7B 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 Llama 4 Scout and Qwen2.5-Coder 7B Instruct?

Key differences include multimodal support (yes vs no), licensing (Llama 4 Community License Agreement vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Llama 4 Scout and Qwen2.5-Coder 7B Instruct?

Llama 4 Scout is developed by Meta and Qwen2.5-Coder 7B Instruct is developed by Alibaba Cloud / Qwen Team.