Mercury 2 vs Llama 4 Scout
| Signal | Mercury 2 | Delta | Llama 4 Scout |
|---|---|---|---|
Capabilities | 67 | -- | |
Benchmarks | 60 | +1 | |
Pricing | 99 | 0 | |
Context window size | 81 | -16 | |
Recency | 100 | +60 | |
Output Capacity | 75 | +8 | |
| Overall Result | 3 wins | of 6 | 2 wins |
Score History
60.9
current score
Mercury 2
right now
60.2
current score
Mercury 2
Inception
Llama 4 Scout
Meta
Llama 4 Scout saves you $37.50/month
That's $450.00/year compared to Mercury 2 at your current usage level of 100K calls/month.
| Metric | Mercury 2 | Llama 4 Scout | Winner |
|---|---|---|---|
| Overall Score | 61 | 60 | Mercury 2 |
| Rank | #210 | #212 | Mercury 2 |
| Quality Rank | #210 | #212 | Mercury 2 |
| Adoption Rank | #210 | #212 | Mercury 2 |
| Parameters | -- | -- | -- |
| Context Window | 128K | 1311K | Llama 4 Scout |
| Pricing | $0.25/$0.75/M | $0.10/$0.30/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 67 | Mercury 2 |
| Benchmarks | 60 | 59 | Mercury 2 |
| Pricing | 99 | 100 | Llama 4 Scout |
| Context window size | 81 | 97 | Llama 4 Scout |
| Recency | 100 | 39 | Mercury 2 |
| Output Capacity | 75 | 67 | Mercury 2 |
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 61/100 (rank #210), placing it in the top 28% of all 290 models tracked.
Scores 60/100 (rank #212), placing it in the top 27% of all 290 models tracked.
With only a 1-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.
Choose Mercury 2 when you need:
- Step-by-step reasoning and chain-of-thought problem solving
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 60% better value per quality point. At 1M tokens/day, you'd spend $6.00/month with Llama 4 Scout vs $15.00/month with Mercury 2 - a $9.00 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 (61/100) 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
Mercury 2 and Llama 4 Scout are extremely close in overall performance (only 0.6999999999999957 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
By Use Case
Best for Quality
Mercury 2
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 4 Scout
60% lower pricing; better value at scale
Best for Reliability
Mercury 2
Higher uptime and faster response speeds
Best for Prototyping
Mercury 2
Stronger community support and better developer experience
Best for Production
Mercury 2
Wider enterprise adoption and proven at scale
by Inception
- 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 | Mercury 2 | Llama 4 Scout |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Mercury 2
Inception
Llama 4 Scout
Meta
Llama 4 Scout saves you $0.8100/month
That's 60% cheaper than Mercury 2 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 | Mercury 2 | Llama 4 Scout |
|---|---|---|
| Context Window | 128K | 1.3M |
| Max Output Tokens | 50,000 | 16,384 |
| Open Source | No | Yes |
| Created | Mar 4, 2026 | Apr 5, 2025 |