DeepSeek V4 Flash vs Llama 3.1 8B
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 Flash and Llama 3.1 8B.
DeepSeek V4 Flash
DeepSeek V4 Flash is an efficiency-optimized Mixture-of-Experts model from DeepSeek with 284B total parameters and 13B activated parameters, supporting a 1M-token context window. It is designed for fast inference and...
Llama 3.1 8B
Llama 3.1 8B is Meta's lightweight open-weight model from the Llama 3.1 generation, optimized for efficient deployment on consumer hardware and edge devices. Despite its compact 8-billion-parameter size, it delivers strong performance on instruction following, text summarization, and lightweight coding tasks. Lllama 3.1 8B is the most downloaded model in the Llama family and runs efficiently on laptops, single GPUs, and CPU via quantization — making it the default choice for on-device AI applications and local prototyping.
Technical Specifications
| Specification | DeepSeek V4 Flash | Llama 3.1 8B |
|---|---|---|
| Provider | DeepSeek | Meta |
| Context Window | 1,048,576 tokens | 131,072 tokens |
| Agent Suitability | 86/100 | 74/100 |
| Time to First Token (TTFT) | 120 ms | 80 ms |
| 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 Flash
$0.09
Llama 3.1 8B
$0.04
Output Price per Million Tokens
DeepSeek V4 Flash
$0.18
Llama 3.1 8B
$0.04
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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 Flash Quirks & Gotchas
- ▸Best cost-per-token ratio of any hosted API — ideal for high-throughput pipelines
- ▸Lower agentic performance vs V4 Pro — route complex tool calls accordingly
Llama 3.1 8B Quirks & Gotchas
- ▸Perfect for CPU/edge deployment — runs on Raspberry Pi with quantization
- ▸Limited tool calling vs larger models — best for simple classification and chat