| Signal | GPT-4.1 Mini | Delta | Llama 4 Scout |
|---|---|---|---|
Capabilities | 83 | +17 | |
Benchmarks | 75 | +75 | |
Pricing | 2 | +1 | |
Context window size | 96 | +8 | |
Recency | 69 | +2 | |
Output Capacity | 75 | +5 | |
| Overall Result | 6 wins | of 6 | 0 wins |
6
days higher
5
days
19
days higher
OpenAI
Meta
Llama 4 Scout saves you $97.00/month
That's $1164.00/year compared to GPT-4.1 Mini at your current usage level of 100K calls/month.
| Metric | GPT-4.1 Mini | Llama 4 Scout | Winner |
|---|---|---|---|
| Overall Score | 72 | 72 | Llama 4 Scout |
| Rank | #150 | #149 | Llama 4 Scout |
| Quality Rank | #150 | #149 | Llama 4 Scout |
| Adoption Rank | #150 | #149 | Llama 4 Scout |
| Parameters | -- | -- | -- |
| Context Window | 1048K | 328K | GPT-4.1 Mini |
| Pricing | $0.40/$1.60/M | $0.08/$0.30/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 67 | GPT-4.1 Mini |
| Benchmarks | 75 | -- | GPT-4.1 Mini |
| Pricing | 2 | 0 | GPT-4.1 Mini |
| Context window size | 96 | 88 | GPT-4.1 Mini |
| Recency | 69 | 68 | GPT-4.1 Mini |
| Output Capacity | 75 | 70 | GPT-4.1 Mini |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 72/100 (rank #150), placing it in the top 49% of all 290 models tracked.
Scores 72/100 (rank #149), placing it in the top 49% of all 290 models tracked.
With only a 0-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 81% better value per quality point. At 1M tokens/day, you'd spend $5.70/month with Llama 4 Scout vs $30.00/month with GPT-4.1 Mini - a $24.30 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
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Llama 4 Scout also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1048K 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 (72/100) 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
GPT-4.1 Mini and Llama 4 Scout are extremely close in overall performance (only 0.09999999999999432 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-4.1 Mini
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 4 Scout
81% lower pricing; better value at scale
Best for Reliability
GPT-4.1 Mini
Higher uptime and faster response speeds
Best for Prototyping
GPT-4.1 Mini
Stronger community support and better developer experience
Best for Production
GPT-4.1 Mini
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-4.1 Mini | Llama 4 Scout |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Meta
Llama 4 Scout saves you $2.14/month
That's 81% cheaper than GPT-4.1 Mini 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 | GPT-4.1 Mini | Llama 4 Scout |
|---|---|---|
| Context Window | 1.0M | 328K |
| Max Output Tokens | 32,768 | 16,384 |
| Open Source | No | Yes |
| Created | Apr 14, 2025 | Apr 5, 2025 |
Llama 4 Scout scores 72/100 (rank #149) compared to GPT-4.1 Mini's 72/100 (rank #150), giving it a 0-point advantage. Llama 4 Scout is the stronger overall choice, though GPT-4.1 Mini may excel in specific areas like certain benchmarks.
GPT-4.1 Mini is ranked #150 and Llama 4 Scout is ranked #149 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Llama 4 Scout is cheaper at $0.30/M output tokens vs GPT-4.1 Mini's $1.60/M output tokens - 5.3x more expensive. Input token pricing: GPT-4.1 Mini at $0.40/M vs Llama 4 Scout at $0.08/M.
GPT-4.1 Mini has a larger context window of 1,047,576 tokens compared to Llama 4 Scout's 327,680 tokens. A larger context window means the model can process longer documents and conversations.