DeepSeek V4 Pro vs Llama 4 Maverick
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 4 Maverick.
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 4 Maverick
Meta's next-generation open weights model. Delivers premium agentic capabilities, reasoning, and tool call compliance for local or self-hosted enterprise stacks.
Technical Specifications
| Specification | DeepSeek V4 Pro | Llama 4 Maverick |
|---|---|---|
| Provider | DeepSeek | Meta |
| Context Window | 1,048,576 tokens | 1,048,576 tokens |
| Agent Suitability | 94/100 | 89/100 |
| Time to First Token (TTFT) | 280 ms | 300 ms |
| Deployment Model | managed api | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2026-04-24 | 2026-05-25 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek V4 Pro
$0.43
Llama 4 Maverick
$0.15
Output Price per Million Tokens
DeepSeek V4 Pro
$0.87
Llama 4 Maverick
$0.60
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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 4 Maverick Quirks & Gotchas
- ▸Self-hostable via Ollama/Docker — ideal for on-premise deployments
- ▸Requires specific system prompt for optimal function calling reliability