Gemma 4 31B vs Llama 4 Maverick
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 4 Maverick.
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 4 Maverick
Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...
Technical Specifications
| Specification | Gemma 4 31B | Llama 4 Maverick |
|---|---|---|
| Provider | Meta | |
| Context Window | 262,144 tokens | 1,048,576 tokens |
| Agent Suitability | N/A | N/A |
| Time to First Token (TTFT) | N/A | N/A |
| Deployment Model | managed api | self hostable |
| Production Stability | stable | beta |
| API Available | Yes | Yes |
| Released Date | 2026-04-02 | 2025-04-05 |
API Pricing Comparison
Input Price per Million Tokens
Gemma 4 31B
$0.12
Llama 4 Maverick
$0.15
Output Price per Million Tokens
Gemma 4 31B
$0.35
Llama 4 Maverick
$0.60
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 31B Quirks & Gotchas
No developer gotchas reported.
Llama 4 Maverick Quirks & Gotchas
No developer gotchas reported.