Llama 4 Scout vs Qwen3-235B-A22B-Instruct-2507
Qwen3-235B-A22B-Instruct-2507 significantly outperforms across most benchmarks. Llama 4 Scout is 2.3x cheaper per token.
Meta · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Llama 4 Scout outperforms in 0 benchmarks, while Qwen3-235B-A22B-Instruct-2507 is better at 2 benchmarks (GPQA, MMLU-Pro). Qwen3-235B-A22B-Instruct-2507 significantly outperforms across most benchmarks.
On price, Llama 4 Scout is roughly 2.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Llama 4 Scout also accepts a larger context window (10,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose Llama 4 Scout
- cost matters — it's about 2.3x cheaper per token
- you process long inputs — it offers a 10,000,000 token context window
Choose Qwen3-235B-A22B-Instruct-2507
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- you want the most recent training data — it shipped Jul 2025
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
Llama 4 Scout outperforms in 0 benchmarks, while Qwen3-235B-A22B-Instruct-2507 is better at 2 benchmarks (GPQA, MMLU-Pro).
Qwen3-235B-A22B-Instruct-2507 significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Llama 4 Scout ($0.08/1M tokens) is 1.9x cheaper than Qwen3-235B-A22B-Instruct-2507 ($0.15/1M tokens).
For output processing, Llama 4 Scout ($0.30/1M tokens) is 2.7x cheaper than Qwen3-235B-A22B-Instruct-2507 ($0.80/1M tokens).
In conclusion, Qwen3-235B-A22B-Instruct-2507 is more expensive than Llama 4 Scout.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3-235B-A22B-Instruct-2507 has 126.0B more parameters than Llama 4 Scout, making it 115.6% larger.
Context Window
Maximum input and output token capacity
Llama 4 Scout accepts 10,000,000 input tokens compared to Qwen3-235B-A22B-Instruct-2507's 262,144 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while Qwen3-235B-A22B-Instruct-2507 is limited to 131,072 tokens.
Input Capabilities
Supported data types and modalities
Llama 4 Scout supports multimodal inputs, whereas Qwen3-235B-A22B-Instruct-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
Qwen3-235B-A22B-Instruct-2507
License
Usage and distribution terms
Llama 4 Scout is licensed under Llama 4 Community License Agreement, while Qwen3-235B-A22B-Instruct-2507 uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Llama 4 Community License Agreement
Open weights
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-Instruct-2507 was released on 2025-07-22.
Qwen3-235B-A22B-Instruct-2507 is 4 months newer than Llama 4 Scout.
Apr 5, 2025
1.4 years ago
Jul 22, 2025
1.1 years ago
3mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together. Qwen3-235B-A22B-Instruct-2507 is available from Fireworks, Novita.
Llama 4 Scout
Qwen3-235B-A22B-Instruct-2507
Outputs Comparison
Judge for yourself.
Run your own prompts against Llama 4 Scout and Qwen3-235B-A22B-Instruct-2507 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Llama 4 Scout vs Qwen3-235B-A22B-Instruct-2507.