Battle of the Models
Compare specific LLM models, context windows, and capabilities.
DeepSeek-R1
S-TIERNVIDIA NIM
Intelligence Score
97/100
Model Popularity
0 votes
Context Window
128K
Pricing Model
Commercial / Paid
Llama 4 Scout
A-TIERGitHub Models
Intelligence Score
87/100
Context Window
128K
Pricing Model
Free / Open
Model Popularity
0 votes
FINAL VERDICT
DeepSeek-R1 Wins
With an intelligence score of 97/100 vs 87/100, DeepSeek-R1 outperforms Llama 4 Scout by 10 points.
HEAD-TO-HEAD
Detailed Comparison
| Feature |
DeepSeek-R1
|
Llama 4 Scout
|
|---|---|---|
|
Context Window
|
128K | 128K |
|
Architecture
|
Dense Transformer | Transformer (Open Weight) |
|
Est. MMLU Score
|
~92-95% | ~80-84% |
|
Release Date
|
Jan 2025 | 2026 (Latest) |
|
Pricing Model
|
Paid / Commercial | Free Tier |
|
Rate Limit (RPM)
|
40 requests/minute | 10 RPM (high-tier) / higher for mini-tier |
|
Daily Limit
|
- | 50 RPD (high-tier models) / 150 RPD (mini-tier models) |
|
Capabilities
|
No specific data
|
No specific data
|
|
Performance Tier
|
S-Tier (Elite) | A-Tier (Excellent) |
|
Speed Estimate
|
🐢 Slower (Reasoning) | ⚡ Very Fast |
|
Primary Use Case
|
🧠 Complex Reasoning | General Purpose |
|
Model Size
|
Undisclosed | Undisclosed |
|
Limitations
|
|
|
|
Key Strengths
|
|
|
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