Gemini 3.1 Pro vs Llama 3.2 1B Instruct
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 Gemini 3.1 Pro and Llama 3.2 1B Instruct.
Gemini 3.1 Pro
Google's premiere multi-modal model featuring a massive 2 million token context window. Engineered for deep code analysis, video indexing, and long-context reasoning.
Llama 3.2 1B Instruct
Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate...
Technical Specifications
| Specification | Gemini 3.1 Pro | Llama 3.2 1B Instruct |
|---|---|---|
| Provider | Meta | |
| Context Window | 2,000,000 tokens | 131,072 tokens |
| Agent Suitability | 93/100 | N/A |
| Time to First Token (TTFT) | 420 ms | N/A |
| Deployment Model | managed api | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2026-04-20 | 2024-09-25 |
API Pricing Comparison
Input Price per Million Tokens
Gemini 3.1 Pro
$2.00
Llama 3.2 1B Instruct
$0.03
Output Price per Million Tokens
Gemini 3.1 Pro
$12.00
Llama 3.2 1B Instruct
$0.20
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.
Gemini 3.1 Pro Quirks & Gotchas
- ▸Best model for massive context — 2M token window is class-leading
- ▸Tool calling requires explicit schema definition in Google AI Studio
Llama 3.2 1B Instruct Quirks & Gotchas
No developer gotchas reported.