Model Comparison
DeepSeek R1 Distill Llama 70B vs Llama 4 ScoutWhich is better in 2026?
DeepSeek R1 Distill Llama 70B significantly outperforms across most benchmarks. Llama 4 Scout is 1.3x cheaper per token.
Verdict: DeepSeek R1 Distill Llama 70B vs Llama 4 Scout — which is better?
DeepSeek R1 Distill Llama 70B (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.
DeepSeek R1 Distill Llama 70B outperforms in 2 benchmarks (GPQA, LiveCodeBench), while Llama 4 Scout is better at 0 benchmarks. DeepSeek R1 Distill Llama 70B significantly outperforms across most benchmarks.
On price, Llama 4 Scout is roughly 1.3x 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.
Choose DeepSeek R1 Distill Llama 70B if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
Choose Llama 4 Scout if…
- cost matters — it's about 1.3x cheaper per token
- you process long inputs — it offers a 10,000,000 token context window
- you want the most recent training data — it shipped Apr 2025
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek R1 Distill Llama 70B outperforms in 2 benchmarks (GPQA, LiveCodeBench), while Llama 4 Scout is better at 0 benchmarks.
DeepSeek R1 Distill Llama 70B significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek R1 Distill Llama 70B ($0.10/1M tokens) is 1.3x more expensive than Llama 4 Scout ($0.08/1M tokens).
For output processing, DeepSeek R1 Distill Llama 70B ($0.40/1M tokens) is 1.3x more expensive than Llama 4 Scout ($0.30/1M tokens).
In conclusion, DeepSeek R1 Distill Llama 70B is more expensive than Llama 4 Scout.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Llama 4 Scout has 38.4B more parameters than DeepSeek R1 Distill Llama 70B, making it 54.4% larger.
Context Window
Maximum input and output token capacity
Llama 4 Scout accepts 10,000,000 input tokens compared to DeepSeek R1 Distill Llama 70B's 128,000 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while DeepSeek R1 Distill Llama 70B is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Llama 4 Scout supports multimodal inputs, whereas DeepSeek R1 Distill Llama 70B does not.
Llama 4 Scout can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek R1 Distill Llama 70B
Llama 4 Scout
License
Usage and distribution terms
DeepSeek R1 Distill Llama 70B 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 R1 Distill Llama 70B was released on 2025-01-20, while Llama 4 Scout was released on 2025-04-05.
Llama 4 Scout is 3 months newer than DeepSeek R1 Distill Llama 70B.
Jan 20, 2025
1.5 years ago
Apr 5, 2025
1.2 years ago
2mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek R1 Distill Llama 70B is available from DeepInfra. Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together.
DeepSeek R1 Distill Llama 70B
Llama 4 Scout
Outputs Comparison
Key Takeaways
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek R1 Distill Llama 70B and Llama 4 Scout side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek R1 Distill Llama 70B vs Llama 4 Scout.