Model Comparison
DeepSeek-V4-Flash-0731 vs Llama 4 ScoutWhich is better in 2026?
Comparing DeepSeek-V4-Flash-0731 and Llama 4 Scout across benchmarks, pricing, and capabilities.
Verdict: DeepSeek-V4-Flash-0731 vs Llama 4 Scout — which is better?
DeepSeek-V4-Flash-0731 (by DeepSeek) and Llama 4 Scout (by Meta) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
On price, DeepSeek-V4-Flash-0731 is roughly 1.2x 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.
Choose DeepSeek-V4-Flash-0731 if…
- cost matters — it's about 1.2x cheaper per token
- you want the most recent training data — it shipped Jul 2026
Choose Llama 4 Scout if…
- you process long inputs — it offers a 10,000,000 token context window
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-0731 and Llama 4 Scoutdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0731 ($0.09/1M tokens) is 1.1x more expensive than Llama 4 Scout ($0.08/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 1.7x cheaper than Llama 4 Scout ($0.30/1M tokens).
In conclusion, Llama 4 Scout is more expensive than DeepSeek-V4-Flash-0731.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Flash-0731 has 195.0B more parameters than Llama 4 Scout, making it 178.9% larger.
Context Window
Maximum input and output token capacity
Llama 4 Scout accepts 10,000,000 input tokens compared to DeepSeek-V4-Flash-0731's 1,048,576 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while DeepSeek-V4-Flash-0731 is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Llama 4 Scout supports multimodal inputs, whereas DeepSeek-V4-Flash-0731 does not.
Llama 4 Scout can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Flash-0731
Llama 4 Scout
License
Usage and distribution terms
DeepSeek-V4-Flash-0731 is licensed under MIT, while Llama 4 Scout uses Llama 4 Community License Agreement.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Llama 4 Community License Agreement
Open weights
Release Timeline
When each model was launched
DeepSeek-V4-Flash-0731 was released on 2026-07-31, while Llama 4 Scout was released on 2025-04-05.
DeepSeek-V4-Flash-0731 is 16 months newer than Llama 4 Scout.
Jul 31, 2026
3 days ago
1.3yr newerApr 5, 2025
1.3 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V4-Flash-0731 is available from DeepInfra, Fireworks, Novita. Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together.
DeepSeek-V4-Flash-0731
Llama 4 Scout
Outputs Comparison
Key Takeaways
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and Llama 4 Scout side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-V4-Flash-0731 vs Llama 4 Scout.