Command R (08-2024) vs Llama 4 Scout
| Signal | Command R (08-2024) | Delta | Llama 4 Scout |
|---|---|---|---|
Capabilities | 50 | -17 | |
Benchmarks | 47 | -11 | |
Pricing | 99 | 0 | |
Context window size | 81 | -16 | |
Recency | 0 | -35 | |
Output Capacity | 58 | -10 | |
| Overall Result | 0 wins | of 6 | 6 wins |
Score History
48.7
current score
Llama 4 Scout
right now
60.2
current score
Command R (08-2024)
Cohere
Llama 4 Scout
Meta
Llama 4 Scout saves you $20.00/month
That's $240.00/year compared to Command R (08-2024) at your current usage level of 100K calls/month.
| Metric | Command R (08-2024) | Llama 4 Scout | Winner |
|---|---|---|---|
| Overall Score | 49 | 60 | Llama 4 Scout |
| Rank | #228 | #215 | Llama 4 Scout |
| Quality Rank | #228 | #215 | Llama 4 Scout |
| Adoption Rank | #228 | #215 | Llama 4 Scout |
| Parameters | -- | -- | -- |
| Context Window | 128K | 1311K | Llama 4 Scout |
| Pricing | $0.15/$0.60/M | $0.10/$0.30/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 67 | Llama 4 Scout |
| Benchmarks | 47 | 59 | Llama 4 Scout |
| Pricing | 99 | 100 | Llama 4 Scout |
| Context window size | 81 | 97 | Llama 4 Scout |
| Recency | 0 | 36 | Llama 4 Scout |
| Output Capacity | 58 | 67 | Llama 4 Scout |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 49/100 (rank #228), placing it in the top 22% of all 290 models tracked.
Scores 60/100 (rank #215), placing it in the top 26% of all 290 models tracked.
Llama 4 Scout has a 12-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Choose Command R (08-2024) when you need:
- Budget-friendly applications with moderate quality requirements
Choose Llama 4 Scout when you need:
- High-volume production workloads where API costs must be minimized
- Processing long documents or large codebases (1311K token context)
- Multimodal workflows that require image understanding
- Self-hosted deployments where you need full control over the model
Llama 4 Scout offers 47% better value per quality point. At 1M tokens/day, you'd spend $6.00/month with Llama 4 Scout vs $11.25/month with Command R (08-2024) - a $5.25 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. Llama 4 Scout also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1311K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.30/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (60/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
Llama 4 Scout clearly outperforms Command R (08-2024) with a significant 11.5-point lead. For most general use cases, Llama 4 Scout is the stronger choice. However, Command R (08-2024) may still excel in niche scenarios.
By Use Case
Best for Quality
Command R (08-2024)
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 4 Scout
47% lower pricing; better value at scale
Best for Reliability
Command R (08-2024)
Higher uptime and faster response speeds
Best for Prototyping
Command R (08-2024)
Stronger community support and better developer experience
Best for Production
Command R (08-2024)
Wider enterprise adoption and proven at scale
by Cohere
- Choose for Quality - Marginally better benchmark scores; both are excellent
- Choose for Reliability - Higher uptime and faster response speeds
- Choose for Prototyping - Stronger community support and better developer experience
- Choose for Production - Wider enterprise adoption and proven at scale
| Capability | Command R (08-2024) | Llama 4 Scout |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Command R (08-2024)
Cohere
Llama 4 Scout
Meta
Llama 4 Scout saves you $0.4500/month
That's 45% cheaper than Command R (08-2024) at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Command R (08-2024) | Llama 4 Scout |
|---|---|---|
| Context Window | 128K | 1.3M |
| Max Output Tokens | 4,000 | 16,384 |
| Open Source | No | Yes |
| Created | Aug 30, 2024 | Apr 5, 2025 |