DeepSeek V3.1 vs Llama 3.2 11B Vision
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 V3.1 and Llama 3.2 11B Vision.
DeepSeek V3.1
DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...
Llama 3.2 11B Vision
Meta's lightweight open weights vision model, optimized for mobile devices and local deployments. Capable of visual understanding, chart reading, and fast text generation.
Technical Specifications
| Specification | DeepSeek V3.1 | Llama 3.2 11B Vision |
|---|---|---|
| Provider | DeepSeek | Meta |
| Context Window | 163,840 tokens | 131,072 tokens |
| Agent Suitability | N/A | 72/100 |
| Time to First Token (TTFT) | N/A | 150 ms |
| Deployment Model | self hostable | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-08-21 | 2024-09-25 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek V3.1
$0.21
Llama 3.2 11B Vision
$0.34
Output Price per Million Tokens
DeepSeek V3.1
$0.79
Llama 3.2 11B Vision
$0.34
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 V3.1 Quirks & Gotchas
No developer gotchas reported.
Llama 3.2 11B Vision Quirks & Gotchas
- ▸Lightweight vision model for edge/on-device deployments
- ▸Limited tool calling — use Llama 4 for production agentic tasks