Google's Gemini 4 Argon and Moonshot AI's Kimi K3.1 Pro compared on specs, pricing, and capabilities — as configured in AI Crucible ensembles.
| Specification | Gemini 4 Argon | Kimi K3.1 Pro |
|---|---|---|
| Provider | Moonshot AI | |
| API model ID | gemini-4-argon | kimi-k3.1-pro |
| Description | Google's flagship Gemini 4 reasoning model for complex software engineering, deep math and science, and autonomous agents, with 1M context. | Moonshot AI's most capable flagship, a 3T-parameter model for coding, agents, and deep reasoning, with vision and 1M context. |
| Context window | 1.048576M tokens | 1.048576M tokens |
| Max output tokens | 32,768 | 8,192 |
| Input cost ($/1M tokens) | $2.40 | $2.40 |
| Output cost ($/1M tokens) | $12.00 | $12.00 |
| Cache read cost ($/1M tokens) | $0.12 | $0.24 |
| Latency | high | high |
| Reasoning model | Yes | Yes |
| Vision (image input) | Yes | Yes |
| Tool use | Yes | Yes |
See all model comparisons, full model specifications, benchmark results, or model comparison articles.