GPT-5 Mini vs Llama 4 Scout
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for GPT-5 Mini and Llama 4 Scout.
GPT-5 Mini
GPT-5 Mini is a compact version of GPT-5, designed to handle lighter-weight reasoning tasks. It provides the same instruction-following and safety-tuning benefits as GPT-5, but with reduced latency and cost....
Llama 4 Scout
Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...
Technical Specifications
| Specification | GPT-5 Mini | Llama 4 Scout |
|---|---|---|
| Provider | OpenAI | Meta |
| Context Window | 400,000 tokens | 10,000,000 tokens |
| Agent Suitability | 85/100 | 82/100 |
| Time to First Token (TTFT) | 180 ms | 350 ms |
| Deployment Model | managed api | self hostable |
| Production Stability | stable | beta |
| API Available | Yes | Yes |
| Released Date | 2025-08-07 | 2025-04-05 |
API Pricing Comparison
Input Price per Million Tokens
GPT-5 Mini
$0.25
Llama 4 Scout
$0.10
Output Price per Million Tokens
GPT-5 Mini
$2.00
Llama 4 Scout
$0.30
Want to test both models live?
Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.
Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
GPT-5 Mini Quirks & Gotchas
- ▸Excellent for high-frequency classification and routing tasks
- ▸Tool calling reliability drops on complex multi-step chains — use GPT-5 for agentic workflows
Llama 4 Scout Quirks & Gotchas
- ▸10M context causes significant VRAM pressure — recommend 4-bit quantization
- ▸Primarily designed for RAG, not agentic tool calling