Kimi K3.1 Pro vs Mercury 2.5
Pricing, context window and real answers (October 2026)
Kimi K3.1 Pro (Moonshot) and Mercury 2.5 (Inception), compared as you can actually call them on FastMetal. Both are served from the same OpenAI-compatible endpoint and API key; switching is a change to the model string.
Specs and pricing
| Mercury 2.5 | ||
|---|---|---|
| Provider | Moonshot | Inception |
| Input (per 1M tokens) | $2.11 | $0.044 |
| Output (per 1M tokens) | $10.55 | $0.165 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | $7.39 | $0.1265 |
| Context window | 1,048,576 tokens | 260,000 tokens |
| Release date | 10/23/2026 | 9/8/2026 |
| Input modalities | text, image, video | text |
| Throughput (p50) | — | — |
| Arena · overall | Unranked | Unranked |
| Arena · Japanese | Unranked | Unranked |
| Arena · coding | Unranked | Unranked |
Prices are FastMetal's rates, before tax.
Rankings: LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), CC BY 4.0, snapshot 2026-10-22; category names mapped and ratings rounded by FastMetal.
Which should you pick?
- On price, Mercury 2.5: $0.165 per 1M output tokens, 98% less than Kimi K3.1 Pro.
- For long documents, Kimi K3.1 Pro: a 1,048,576-token context window against 260,000 for Mercury 2.5.
- If in doubt, try both on the same key. Switching is a change to the model string, and each is billed at its own rate.
Real answers to the same prompts
Exactly what the FastMetal gateway returned, side by side. Not benchmark scores: actual output.
Count the number of 'r's in 'strawberry'
Count the number of 'r's in 'strawberry'. Explain your reasoning step by step.
Kimi K3.1 Pro
Mercury 2.5
Debug This Error
I'm getting the following error in my Node.js application: TypeError: Cannot read properties of undefined (reading 'map') at UserList (/app/components/UserList.js:12:25) at renderWithHooks (/app/node_modules/rea…
Kimi K3.1 Pro
Mercury 2.5
Code Review
Please review the following Python function and suggest improvements for readability, performance, and best practices: def get_data(url, retries=3): import requests import time for i in range(retries):…
Kimi K3.1 Pro
Mercury 2.5
Frequently asked questions
- Which is cheaper, Kimi K3.1 Pro or Mercury 2.5?
- Per 1M output tokens, Kimi K3.1 Pro is $10.55 and Mercury 2.5 is $0.165 on FastMetal (US dollars, before tax), so Mercury 2.5 is cheaper.
- How do the context windows of Kimi K3.1 Pro and Mercury 2.5 compare?
- Kimi K3.1 Pro takes 1,048,576 tokens; Mercury 2.5 takes 260,000.
- Can I use Kimi K3.1 Pro and Mercury 2.5 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "kimi-k3.1-pro" or "mercury-2.5" as the model. Each is billed at its own rate from the same prepaid balance.
Try both on one API key
Create an account and add credit to call Kimi K3.1 Pro and Mercury 2.5 from the browser chat and the API. No monthly fee.