Llama 3.2 11B Vision vs Qwen3 30B A3B Instruct 2507
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 Llama 3.2 11B Vision and Qwen3 30B A3B Instruct 2507.
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.
Qwen3 30B A3B Instruct 2507
Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is designed for high-quality instruction following, multilingual understanding, and...
Technical Specifications
| Specification | Llama 3.2 11B Vision | Qwen3 30B A3B Instruct 2507 |
|---|---|---|
| Provider | Meta | Alibaba |
| Context Window | 131,072 tokens | 131,072 tokens |
| Agent Suitability | 72/100 | N/A |
| Time to First Token (TTFT) | 150 ms | N/A |
| Deployment Model | self hostable | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2024-09-25 | 2025-07-29 |
API Pricing Comparison
Input Price per Million Tokens
Llama 3.2 11B Vision
$0.34
Qwen3 30B A3B Instruct 2507
$0.05
Output Price per Million Tokens
Llama 3.2 11B Vision
$0.34
Qwen3 30B A3B Instruct 2507
$0.19
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.
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
Qwen3 30B A3B Instruct 2507 Quirks & Gotchas
No developer gotchas reported.