Gemma 4 31B vs MiniMax M1
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 MiniMax M1.
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...
MiniMax M1
MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it...
Technical Specifications
| Specification | Gemma 4 31B | MiniMax M1 |
|---|---|---|
| Provider | MiniMax | |
| Context Window | 262,144 tokens | 1,000,000 tokens |
| Agent Suitability | N/A | N/A |
| Time to First Token (TTFT) | N/A | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | stable | beta |
| API Available | Yes | Yes |
| Released Date | 2026-04-02 | 2025-06-17 |
API Pricing Comparison
Input Price per Million Tokens
Gemma 4 31B
$0.12
MiniMax M1
$0.40
Output Price per Million Tokens
Gemma 4 31B
$0.35
MiniMax M1
$2.20
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.
Gemma 4 31B Quirks & Gotchas
No developer gotchas reported.
MiniMax M1 Quirks & Gotchas
No developer gotchas reported.