| Signal | Command A | Delta | Llama 4 Scout |
|---|---|---|---|
Capabilities | 33 | -33 | |
Benchmarks | 51 | 0 | |
Pricing | 90 | -10 | |
Context window size | 86 | -2 | |
Recency | 56 | -4 | |
Output Capacity | 65 | -5 | |
| Overall Result | 0 wins | of 6 | 6 wins |
Score History
50.8
current score
Llama 4 Scout
right now
54.2
current score
Cohere
Meta
Llama 4 Scout saves you $727.00/month
That's $8724.00/year compared to Command A at your current usage level of 100K calls/month.
| Metric | Command A | Llama 4 Scout | Winner |
|---|---|---|---|
| Overall Score | 51 | 54 | Llama 4 Scout |
| Rank | #170 | #162 | Llama 4 Scout |
| Quality Rank | #170 | #162 | Llama 4 Scout |
| Adoption Rank | #170 | #162 | Llama 4 Scout |
| Parameters | -- | -- | -- |
| Context Window | 256K | 328K | Llama 4 Scout |
| Pricing | $2.50/$10.00/M | $0.08/$0.30/M | -- |
| Signal Scores | |||
| Capabilities | 33 | 67 | Llama 4 Scout |
| Benchmarks | 51 | 52 | Llama 4 Scout |
| Pricing | 90 | 100 | Llama 4 Scout |
| Context window size | 86 | 88 | Llama 4 Scout |
| Recency | 56 | 60 | Llama 4 Scout |
| Output Capacity | 65 | 70 | 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 51/100 (rank #170), placing it in the top 42% of all 290 models tracked.
Scores 54/100 (rank #162), placing it in the top 44% of all 290 models tracked.
With only a 3-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Llama 4 Scout offers 97% better value per quality point. At 1M tokens/day, you'd spend $5.70/month with Llama 4 Scout vs $187.50/month with Command A - a $181.80 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 (328K 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 (54/100) 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 has a moderate advantage with a 3.4000000000000057-point lead in composite score. It wins on more signal dimensions, but Command A has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Command A
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 4 Scout
97% lower pricing; better value at scale
Best for Reliability
Command A
Higher uptime and faster response speeds
Best for Prototyping
Command A
Stronger community support and better developer experience
Best for Production
Command A
Wider enterprise adoption and proven at scale
by Cohere
| Capability | Command A | Llama 4 Scout |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Cohere
Meta
Llama 4 Scout saves you $16.00/month
That's 97% cheaper than Command A 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 A | Llama 4 Scout |
|---|---|---|
| Context Window | 256K | 328K |
| Max Output Tokens | 8,192 | 16,384 |
| Open Source | Yes | Yes |
| Created | Mar 13, 2025 | Apr 5, 2025 |