Gemma 4 31B 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 31B and Llama 3.2 11B Vision.
Gemma 4 31B
Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...
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 31B | 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 | 2026-04-02 | 2024-09-25 |
API Pricing Comparison
Input Price per Million Tokens
Gemma 4 31B
$0.12
Llama 3.2 11B Vision
$0.34
Output Price per Million Tokens
Gemma 4 31B
$0.35
Llama 3.2 11B Vision
$0.34
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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 31B 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