| Signal | Llama 4 Scout | Delta | Devstral 2 2512 |
|---|---|---|---|
Capabilities | 67 | +17 | |
Benchmarks | 52 | +9 | |
Pricing | 100 | +2 | |
Context window size | 88 | +2 | |
Recency | 60 | -40 | |
Output Capacity | 70 | +50 | |
| Overall Result | 5 wins | of 6 | 1 wins |
Score History
54.2
current score
Llama 4 Scout
right now
45.5
current score
Meta
Mistral AI
Llama 4 Scout saves you $117.00/month
That's $1404.00/year compared to Devstral 2 2512 at your current usage level of 100K calls/month.
| Metric | Llama 4 Scout | Devstral 2 2512 | Winner |
|---|---|---|---|
| Overall Score | 54 | 46 | Llama 4 Scout |
| Rank | #162 | #177 | Llama 4 Scout |
| Quality Rank | #162 | #177 | Llama 4 Scout |
| Adoption Rank | #162 | #177 | Llama 4 Scout |
| Parameters | -- | -- | -- |
| Context Window | 328K | 262K | Llama 4 Scout |
| Pricing | $0.08/$0.30/M | $0.40/$2.00/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 50 | Llama 4 Scout |
| Benchmarks | 52 | 43 | Llama 4 Scout |
| Pricing | 100 | 98 | Llama 4 Scout |
| Context window size | 88 | 86 | Llama 4 Scout |
| Recency | 60 | 100 | Devstral 2 2512 |
| Output Capacity | 70 | 20 | 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 54/100 (rank #162), placing it in the top 44% of all 290 models tracked.
Scores 46/100 (rank #177), placing it in the top 39% of all 290 models tracked.
Llama 4 Scout has a 9-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Llama 4 Scout offers 84% better value per quality point. At 1M tokens/day, you'd spend $5.70/month with Llama 4 Scout vs $36.00/month with Devstral 2 2512 - a $30.30 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 8.700000000000003-point lead in composite score. It wins on more signal dimensions, but Devstral 2 2512 has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Llama 4 Scout
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 4 Scout
84% lower pricing; better value at scale
Best for Reliability
Llama 4 Scout
Higher uptime and faster response speeds
Best for Prototyping
Llama 4 Scout
Stronger community support and better developer experience
Best for Production
Llama 4 Scout
Wider enterprise adoption and proven at scale
by Meta
| Capability | Llama 4 Scout | Devstral 2 2512 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Meta
Mistral AI
Llama 4 Scout saves you $2.62/month
That's 84% cheaper than Devstral 2 2512 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 | Llama 4 Scout | Devstral 2 2512 |
|---|---|---|
| Context Window | 328K | 262K |
| Max Output Tokens | 16,384 | -- |
| Open Source | Yes | Yes |
| Created | Apr 5, 2025 | Dec 9, 2025 |