DeepSeek V4 Pro vs Llama 3.1 8B Instruct
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 3.1 8B Instruct.
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 3.1 8B Instruct
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance compared to...
Technical Specifications
| Specification | DeepSeek V4 Pro | Llama 3.1 8B Instruct |
|---|---|---|
| Provider | DeepSeek | Meta |
| Context Window | 1,048,576 tokens | 131,072 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 | 2024-07-23 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek V4 Pro
$0.43
Llama 3.1 8B Instruct
$0.02
Output Price per Million Tokens
DeepSeek V4 Pro
$0.87
Llama 3.1 8B Instruct
$0.03
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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 3.1 8B Instruct Quirks & Gotchas
No developer gotchas reported.