Kimi K2.6 is $1.26 cheaper per 1M input tokens (63% lower; 2.7x difference).
API cost decision in 10 seconds
🔥Kimi K2.6 vs 🔥Gemini 3.1 Pro Preview
Pick Kimi K2.6 for lower cost; pick Gemini 3.1 Pro Preview only if the larger context window matters more.
Pricing data updated:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Kimi K2.6 for lower cost; pick Gemini 3.1 Pro Preview only if the larger context window matters more.
On the standard 1M input plus 500K output workload, Kimi K2.6 is estimated at $2.49 vs $8 for Gemini 3.1 Pro Preview, saving $5.51 (68.9% lower).
Cost-first pickKimi K2.6
Context-first pickGemini 3.1 Pro Preview
Sample savings$5.5168.9%
10x traffic gap$55.1
Gemini 3.1 Pro Preview has more context, but Kimi K2.6 saves $5.51 on the standard workload. At 10x that traffic, the same price gap is about $55.1. Use the calculator below to replace the sample workload with your own token volume.
Kimi K2.6 is $8.5 cheaper per 1M output tokens (70.8% lower; 3.43x difference).
Gemini 3.1 Pro Preview has 786.43K more context (4x larger).
Kimi K2.6 is $5.51 cheaper on the standard workload (68.9% lower).
Estimate your workload cost
Your Workload Cost
This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.
Quick Decision
Kimi K2.6 has the lower input price; Kimi K2.6 has the lower output price; Gemini 3.1 Pro Preview offers the larger context window. For the 1M input plus 500K output sample, Kimi K2.6 is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $2.49 for Kimi K2.6 and $8 for Gemini 3.1 Pro Preview.
Choose Kimi K2.6 when you care most about lower input-token price, and lower output-token price.
Choose Gemini 3.1 Pro Preview when you care most about larger context window.
- On the standard 1M input plus 500K output workload, Kimi K2.6 is estimated at $2.49 vs $8 for Gemini 3.1 Pro Preview, saving $5.51 (68.9% lower).
- Kimi K2.6 is $5.51 cheaper on the standard workload (68.9% lower).
- Kimi K2.6 is $1.26 cheaper per 1M input tokens (63% lower; 2.7x difference).
- Kimi K2.6 is $8.5 cheaper per 1M output tokens (70.8% lower; 3.43x difference).
- Gemini 3.1 Pro Preview has 786.43K more context (4x larger).
| Feature | 🔥Kimi K2.6 (MoonshotAI) | 🔥Gemini 3.1 Pro Preview (Google) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.74 | $2 |
| Completion Price per 1M tokens | $3.5 | $12 |
| Sample Workload Cost 1M input + 500K output | $2.49 | $8 |
| Context Window | 262.14K | 1.05M |
| Release Date | 2026-04-20 | 2026-02-19 |
| Popularity Rank current rank | #5 | #20 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Kimi K2.6 | On the standard 1M input plus 500K output workload, Kimi K2.6 is estimated at $2.49 vs $8 for Gemini 3.1 Pro Preview, saving $5.51 (68.9% lower). |
| High-volume input processing | Kimi K2.6 | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Kimi K2.6 | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Gemini 3.1 Pro Preview | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
Cheaper alternatives
Review low-cost models ranked by a standard 1M input plus 500K output workload.
Open cheapest modelsLarger context alternatives
Find models with larger context windows for RAG, long documents, and codebase review.
Open largest context modelsProvider catalogs
Compare models within provider hubs before choosing a final API vendor.
Open provider hubsMoonshotAI catalog
Review all tracked MoonshotAI models before deciding whether this matchup is the right shortlist.
Open MoonshotAI modelsGoogle catalog
Check other Google models with comparable pricing, context, or release timing.
Open Google modelsKimi 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...
Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation...