| Signal | Llama 4 Scout | Delta | Mistral Large 2407 |
|---|---|---|---|
Capabilities | 67 | +17 | |
Benchmarks | 52 | -4 | |
Pricing | 100 | +6 | |
Context window size | 88 | +6 | |
Recency | 63 | +25 | |
Output Capacity | 70 | +50 | |
| Overall Result | 5 wins | of 6 | 1 wins |
Score History
54.2
current score
Mistral Large 2407
right now
56.2
current score
Meta
Mistral AI
Llama 4 Scout saves you $477.00/month
That's $5724.00/year compared to Mistral Large 2407 at your current usage level of 100K calls/month.
| Metric | Llama 4 Scout | Mistral Large 2407 | Winner |
|---|---|---|---|
| Overall Score | 54 | 56 | Mistral Large 2407 |
| Rank | #151 | #149 | Mistral Large 2407 |
| Quality Rank | #151 | #149 | Mistral Large 2407 |
| Adoption Rank | #151 | #149 | Mistral Large 2407 |
| Parameters | -- | -- | -- |
| Context Window | 328K | 131K | Llama 4 Scout |
| Pricing | $0.08/$0.30/M | $2.00/$6.00/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 50 | Llama 4 Scout |
| Benchmarks | 52 | 55 | Mistral Large 2407 |
| Pricing | 100 | 94 | Llama 4 Scout |
| Context window size | 88 | 81 | Llama 4 Scout |
| Recency | 63 | 38 | Llama 4 Scout |
| 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 #151), placing it in the top 48% of all 290 models tracked.
Scores 56/100 (rank #149), placing it in the top 49% of all 290 models tracked.
With only a 2-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 95% better value per quality point. At 1M tokens/day, you'd spend $5.70/month with Llama 4 Scout vs $120.00/month with Mistral Large 2407 - a $114.30 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 (56/100) 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 and Mistral Large 2407 are extremely close in overall performance (only 2 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Llama 4 Scout
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 4 Scout
95% 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 | Mistral Large 2407 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Meta
Mistral AI
Llama 4 Scout saves you $10.30/month
That's 95% cheaper than Mistral Large 2407 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 | Mistral Large 2407 |
|---|---|---|
| Context Window | 328K | 131K |
| Max Output Tokens | 16,384 | -- |
| Open Source | Yes | No |
| Created | Apr 5, 2025 | Nov 19, 2024 |