Gemini 3.1 Pro 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 Gemini 3.1 Pro and Kimi K2.7 Code.
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.
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 | Gemini 3.1 Pro | Kimi K2.7 Code |
|---|---|---|
| Provider | Moonshot AI | |
| Context Window | 2,000,000 tokens | 262,144 tokens |
| Agent Suitability | 93/100 | N/A |
| Time to First Token (TTFT) | 420 ms | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2026-04-20 | 2026-06-12 |
API Pricing Comparison
Input Price per Million Tokens
Gemini 3.1 Pro
$2.00
Kimi K2.7 Code
$0.74
Output Price per Million Tokens
Gemini 3.1 Pro
$12.00
Kimi K2.7 Code
$3.50
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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
Kimi K2.7 Code Quirks & Gotchas
No developer gotchas reported.