MoonshotAI: Kimi K2.6 vs Meta: Llama 4 Maverick
Side-by-side comparison — pricing, context window, capabilities, and live leaderboard data.
Key differences
- Meta: Llama 4 Maverick has a 1049K-token context window — 4.0× larger than MoonshotAI: Kimi K2.6's 262K.
- Meta: Llama 4 Maverick is 79% cheaper per 1K input tokens than MoonshotAI: Kimi K2.6 ($0.0001 vs $0.0007).
- MoonshotAI: Kimi K2.6 is built by OpenRouter; Meta: Llama 4 Maverick is built by Meta.
Specifications
| MoonshotAI: Kimi K2.6 | Meta: Llama 4 Maverick | |
|---|---|---|
| Provider | OpenRouter | Meta |
| Context window | 262K | 1049K |
| Max output tokens | 8192 | 8192 |
| Input price / 1K tokens | $0.0007 | $0.0001 |
| Output price / 1K tokens | $0.0035 | $0.0006 |
| Vision support | Yes | Yes |
| Function calling | No | No |
| License | Open Weights | Proprietary |
About MoonshotAI: Kimi K2.6
CN·Open weightsKimi K2.6 is Moonshot AI's next-generation multimodal model, designed for long-horizon coding, coding-driven UI/UX generation, and multi-agent orchestration. It handles complex end-to-end coding tasks across Python, Rust, and Go, and...
View MoonshotAI: Kimi K2.6 reliability and benchmark history →About Meta: Llama 4 Maverick
US·ClosedLlama 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...
View Meta: Llama 4 Maverick reliability and benchmark history →Try them yourself
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