Gemma 4 31B vs Llama 3.1 8B
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 3.1 8B.
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 3.1 8B
Llama 3.1 8B is Meta's lightweight open-weight model from the Llama 3.1 generation, optimized for efficient deployment on consumer hardware and edge devices. Despite its compact 8-billion-parameter size, it delivers strong performance on instruction following, text summarization, and lightweight coding tasks. Lllama 3.1 8B is the most downloaded model in the Llama family and runs efficiently on laptops, single GPUs, and CPU via quantization — making it the default choice for on-device AI applications and local prototyping.
Technical Specifications
| Specification | Gemma 4 31B | Llama 3.1 8B |
|---|---|---|
| Provider | Meta | |
| Context Window | 262,144 tokens | 131,072 tokens |
| Agent Suitability | N/A | 74/100 |
| Time to First Token (TTFT) | N/A | 80 ms |
| Deployment Model | managed api | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2026-04-02 | 2024-07-23 |
API Pricing Comparison
Input Price per Million Tokens
Gemma 4 31B
$0.12
Llama 3.1 8B
$0.04
Output Price per Million Tokens
Gemma 4 31B
$0.35
Llama 3.1 8B
$0.04
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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 3.1 8B Quirks & Gotchas
- ▸Perfect for CPU/edge deployment — runs on Raspberry Pi with quantization
- ▸Limited tool calling vs larger models — best for simple classification and chat