Model Comparison

Llama 4 Scout vs Qwen3-235B-A22B-Thinking-2507

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks. Llama 4 Scout is 7.2x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Llama 4 Scout outperforms in 0 benchmarks, while Qwen3-235B-A22B-Thinking-2507 is better at 2 benchmarks (GPQA, MMLU-Pro).

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.

Thu Apr 30 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Llama 4 Scout costs less

For input processing, Llama 4 Scout ($0.08/1M tokens) is 3.8x cheaper than Qwen3-235B-A22B-Thinking-2507 ($0.30/1M tokens).

For output processing, Llama 4 Scout ($0.30/1M tokens) is 10.0x cheaper than Qwen3-235B-A22B-Thinking-2507 ($3.00/1M tokens).

In conclusion, Qwen3-235B-A22B-Thinking-2507 is more expensive than Llama 4 Scout.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers

Thu Apr 30 2026 • llm-stats.com

Llama 4 Scout

Input tokens$0.08

Output tokens$0.30

Best providerDeepinfra

Qwen3-235B-A22B-Thinking-2507

Input tokens$0.30

Output tokens$3.00

Best providerFireworks

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Model Size

Parameter count comparison

126.0B diff

Qwen3-235B-A22B-Thinking-2507 has 126.0B more parameters than Llama 4 Scout, making it 115.6% larger.

Llama 4 Scout

109.0Bparameters

Qwen3-235B-A22B-Thinking-2507

235.0Bparameters

109.0B

Llama 4 Scout

235.0B

Qwen3-235B-A22B-Thinking-2507

Context Window

Maximum input and output token capacity

Llama 4 Scout accepts 10,000,000 input tokens compared to Qwen3-235B-A22B-Thinking-2507's 262,144 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while Qwen3-235B-A22B-Thinking-2507 is limited to 131,072 tokens.

Llama 4 Scout

Input10,000,000 tokens

Output10,000,000 tokens

Qwen3-235B-A22B-Thinking-2507

Input262,144 tokens

Output131,072 tokens

Thu Apr 30 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Llama 4 Scout supports multimodal inputs, whereas Qwen3-235B-A22B-Thinking-2507 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

Qwen3-235B-A22B-Thinking-2507

Text

Images

Audio

Video

License

Usage and distribution terms

Llama 4 Scout is licensed under Llama 4 Community License Agreement, while Qwen3-235B-A22B-Thinking-2507 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

Qwen3-235B-A22B-Thinking-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

Llama 4 Scout was released on 2025-04-05, while Qwen3-235B-A22B-Thinking-2507 was released on 2025-07-25.

Qwen3-235B-A22B-Thinking-2507 is 4 months newer than Llama 4 Scout.

Llama 4 Scout

Apr 5, 2025

1.1 years ago

Qwen3-235B-A22B-Thinking-2507

Jul 25, 2025

9 months ago

3mo 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

Provider Availability

Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together. Qwen3-235B-A22B-Thinking-2507 is available from Fireworks, Novita.

Llama 4 Scout

Deepinfra

Input Price:Input: $0.08/1MOutput Price:Output: $0.30/1M

Lambda

Input Price:Input: $0.08/1MOutput Price:Output: $0.30/1M

Novita

Input Price:Input: $0.10/1MOutput Price:Output: $0.50/1M

Groq

Input Price:Input: $0.11/1MOutput Price:Output: $0.34/1M

Fireworks

Input Price:Input: $0.15/1MOutput Price:Output: $0.60/1M

Together

Input Price:Input: $0.18/1MOutput Price:Output: $0.59/1M

Qwen3-235B-A22B-Thinking-2507

Fireworks

Input Price:Input: $0.30/1MOutput Price:Output: $3.00/1M

Novita

Input Price:Input: $0.30/1MOutput Price:Output: $3.00/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Llama 4 Scout

View details

Qwen3-235B-A22B-Thinking-2507

View details

Alibaba Cloud / Qwen Team

Higher GPQA score (81.1% vs 57.2%)

Higher MMLU-Pro score (84.4% vs 74.3%)

Detailed Comparison

AI Model Comparison Table
Feature	Llama 4 Scout	Qwen3-235B-A22B-Thinking-2507

FAQ

Common questions about Llama 4 Scout vs Qwen3-235B-A22B-Thinking-2507

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks. Llama 4 Scout is made by Meta and Qwen3-235B-A22B-Thinking-2507 is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

Llama 4 Scout scores DocVQA: 94.4%, MGSM: 90.6%, ChartQA: 88.8%, MMLU: 79.6%, MMLU-Pro: 74.3%. Qwen3-235B-A22B-Thinking-2507 scores MMLU-Redux: 93.8%, AIME 2025: 92.3%, WritingBench: 88.3%, IFEval: 87.8%, Creative Writing v3: 86.1%.

Llama 4 Scout is 3.8x cheaper for input tokens. Llama 4 Scout costs $0.08/M input and $0.30/M output via deepinfra. Qwen3-235B-A22B-Thinking-2507 costs $0.30/M input and $3.00/M output via fireworks.

Llama 4 Scout supports 10.0M tokens and Qwen3-235B-A22B-Thinking-2507 supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

Key differences include context window (10.0M vs 262K), input pricing ($0.08 vs $0.30/M), 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.

Llama 4 Scout is developed by Meta and Qwen3-235B-A22B-Thinking-2507 is developed by Alibaba Cloud / Qwen Team.

Llama 4 Scout vs Qwen3-235B-A22B-Thinking-2507

Performance Benchmarks

Arena Performance

Pricing Analysis

Model Size

Context Window

Input Capabilities

Llama 4 Scout

Qwen3-235B-A22B-Thinking-2507

License

Release Timeline

Knowledge Cutoff

Provider Availability

Llama 4 Scout

Qwen3-235B-A22B-Thinking-2507

Outputs Comparison

Key Takeaways

Llama 4 Scout

Qwen3-235B-A22B-Thinking-2507

Detailed Comparison

FAQ

Which is better, Llama 4 Scout or Qwen3-235B-A22B-Thinking-2507?

How does Llama 4 Scout compare to Qwen3-235B-A22B-Thinking-2507 in benchmarks?

Is Llama 4 Scout cheaper than Qwen3-235B-A22B-Thinking-2507?

What are the context window sizes for Llama 4 Scout and Qwen3-235B-A22B-Thinking-2507?

What are the main differences between Llama 4 Scout and Qwen3-235B-A22B-Thinking-2507?

Who makes Llama 4 Scout and Qwen3-235B-A22B-Thinking-2507?