DeepSeek V4 Pro vs Llama Guard 4 12B
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 DeepSeek V4 Pro and Llama Guard 4 12B.
DeepSeek V4 Pro
DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...
Llama Guard 4 12B
Llama Guard 4 is a Llama 4 Scout-derived multimodal pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM...
Technical Specifications
| Specification | DeepSeek V4 Pro | Llama Guard 4 12B |
|---|---|---|
| Provider | DeepSeek | Meta |
| Context Window | 1,048,576 tokens | 163,840 tokens |
| Agent Suitability | 94/100 | N/A |
| Time to First Token (TTFT) | 280 ms | N/A |
| Deployment Model | managed api | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2026-04-24 | 2025-04-30 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek V4 Pro
$0.43
Llama Guard 4 12B
$0.18
Output Price per Million Tokens
DeepSeek V4 Pro
$0.87
Llama Guard 4 12B
$0.18
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.
DeepSeek V4 Pro Quirks & Gotchas
- ▸MoE architecture — cold-start latency on first request, use keep-alive
- ▸Best cost-performance ratio of any frontier model — strong tool calling for agentic use
Llama Guard 4 12B Quirks & Gotchas
No developer gotchas reported.