Gemma 4 31B vs Kimi K2.7 Code
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 Kimi K2.7 Code.
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...
Kimi K2.7 Code
MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts. It uses a native multimodal mixture-of-experts...
Technical Specifications
| Specification | Gemma 4 31B | Kimi K2.7 Code |
|---|---|---|
| Provider | Moonshot AI | |
| Context Window | 262,144 tokens | 262,144 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 | stable |
| API Available | Yes | Yes |
| Released Date | 2026-04-02 | 2026-06-12 |
API Pricing Comparison
Input Price per Million Tokens
Gemma 4 31B
$0.12
Kimi K2.7 Code
$0.74
Output Price per Million Tokens
Gemma 4 31B
$0.35
Kimi K2.7 Code
$3.50
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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.
Kimi K2.7 Code Quirks & Gotchas
No developer gotchas reported.