Gemma 4 26B A4B 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 Gemma 4 26B A4B and Llama 3.2 11B Vision.
Gemma 4 26B A4B
Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...
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 | Gemma 4 26B A4B | Llama 3.2 11B Vision |
|---|---|---|
| Provider | Meta | |
| Context Window | 262,144 tokens | 131,072 tokens |
| Agent Suitability | N/A | 72/100 |
| Time to First Token (TTFT) | N/A | 150 ms |
| Deployment Model | managed api | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2026-04-03 | 2024-09-25 |
API Pricing Comparison
Input Price per Million Tokens
Gemma 4 26B A4B
$0.06
Llama 3.2 11B Vision
$0.34
Output Price per Million Tokens
Gemma 4 26B A4B
$0.33
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.
Gemma 4 26B A4B 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