GPT-5.5 Pro 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-5.5 Pro and Llama 4 Scout.
GPT-5.5 Pro
GPT-5.5 Pro is OpenAI’s high-capability model optimized for deep reasoning and accuracy on complex, high-stakes workloads. It features a 1M+ token context window (922K input, 128K output) with support for...
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-5.5 Pro | Llama 4 Scout |
|---|---|---|
| Provider | OpenAI | Meta |
| Context Window | 1,050,000 tokens | 10,000,000 tokens |
| Agent Suitability | 98/100 | 82/100 |
| Time to First Token (TTFT) | 450 ms | 350 ms |
| Deployment Model | managed api | self hostable |
| Production Stability | beta | beta |
| API Available | Yes | Yes |
| Released Date | 2026-04-24 | 2025-04-05 |
API Pricing Comparison
Input Price per Million Tokens
GPT-5.5 Pro
$30.00
Llama 4 Scout
$0.10
Output Price per Million Tokens
GPT-5.5 Pro
$180.00
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-5.5 Pro Quirks & Gotchas
- ▸Best-in-class instruction following for complex agentic chains
- ▸Premium pricing — use GPT-5 for cost-sensitive workloads
Llama 4 Scout Quirks & Gotchas
- ▸10M context causes significant VRAM pressure — recommend 4-bit quantization
- ▸Primarily designed for RAG, not agentic tool calling