Model comparison

DeepSeek V4.1 Flash vs Kimi K3

Pricing, context window and real answers (September 2026)

DeepSeek V4.1 Flash (DeepSeek) and Kimi K3 (Moonshot), 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

deepseek logoDeepSeek V4.1 Flashmoonshotai logoKimi K3
ProviderDeepSeekMoonshot
Input (per 1M tokens)¥50.69¥536.1
Output (per 1M tokens)¥202.74¥2,680.5
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥152¥1,876
Context window1,048,576 tokens1,048,576 tokens
Release date9/10/20267/16/2026
Input modalitiestext, imagetext, image
Arena · overallUnranked#12 · ELO 1,489
Arena · JapaneseUnranked#3 · ELO 1,516
Arena · codingUnranked#6 · ELO 1,542

Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.

Which should you pick?

  • On price, DeepSeek V4.1 Flash: ¥202.74 per 1M output tokens, 92% less than Kimi K3.
  • 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.

DeepSeek V4.1 Flash

The word **“strawberry”** has **3** letter **“r”**s. Step-by-step: 1. Spell it out: **s t r a w b e r r y** 2. Find each **r**: - Position 3: **r** in “str” - Position 8: first **r** in “berry” - Position 9: second **r** in “berry” 3. Total: **3** **Answer: 3**
7.5s226 output tokens

Kimi K3

# Counting the 'r's in "strawberry" **Step 1: Write out each letter with its position** | Position | Letter | |----------|--------| | 1 | s | | 2 | t | | 3 | **r** ✓ | | 4 | a | | 5 | w | | 6 | b | | 7 | e | | 8 | **r** ✓ | | 9 | **r** ✓ | | 10 | y | **Step 2: Identify each 'r'** - Position 3: the 'r' in "st**r**" - Position 8: the first 'r' in "be**r**ry" - Position 9: the second 'r' in "ber**r**y" **Step 3: Verify by splitting the word** "Strawberry" = "straw" + "berry" - "straw" contains **1** r - "berry" contains **2** r's **Answer: There are 3 r's in "strawberry."** 🍓
12.2s594 output tokens

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…

DeepSeek V4.1 Flash

The error means that `users` is `undefined` when `UserList` renders, so JavaScript cannot call `.map()` on it. Your component expects a `users` prop: ```jsx function UserList({ users }) { return ( <ul> {users.map(user => <li key={user.id}>{user.name}</li>)} </ul> ); } ``` But it is being rendered without `users`, or `users` has not loaded yet. Common causes: 1. Parent renders it without the prop: ```jsx <UserList /> ``` instead of: ```jsx <UserList users={users} /> ``` 2. The prop name is different: ```jsx <UserList userList={users} /> ``` 3. The data is fetched asynchronously and is initially `undefined`: ```jsx const [users, setUsers] = useState(); useEffect(…
16.0s945 output tokens

Kimi K3

## What's causing it The error means `users` is `undefined` when the component renders — `.map()` only exists on arrays, so calling it on `undefined` throws. Your component code is fine; the problem is **upstream**: whatever renders `<UserList />` isn't passing a valid array. The most common culprit is **async data fetching with uninitialized state** in the parent: ```jsx function App() { const [users, setUsers] = useState(); // ← undefined! useEffect(() => { fetch('/api/users') .then(res => res.json()) .then(setUsers); }, []); return <UserList users={users} />; // undefined on first render } ``` The component renders *before* the fetch resolves, so `users` is `…
47.5s1756 output tokens

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):…

DeepSeek V4.1 Flash

Here are the main improvements: - Move imports to module level. - Avoid bare `except`; catch specific exceptions. - Use a `requests.Session` for connection reuse. - Retry only transient network/HTTP failures, not all errors. - Use exponential backoff and don’t sleep after the final attempt. - Use a list comprehension for readability/performance. - Add type hints, logging, constants, and basic JSON validation. - Avoid `== True`; use `is True` or a truthy check depending on API contract. Example refactor: ```python from __future__ import annotations import logging import time from typing import Any import requests logger = logging.getLogger(__name__) TIMEOUT = (3.05, 10) # connect time…
31.5s5142 output tokens

Kimi K3

This works, but there are several issues worth addressing. Here's a breakdown, followed by an improved version. ## Issues ### Correctness & best practices 1. **Bare `except:`** — catches *everything*, including `KeyboardInterrupt` and programming bugs like `KeyError` on a malformed item (which then get pointlessly retried). Catch `requests.RequestException` specifically. 2. **Silent failures** — errors are swallowed with no logging, and returning `[]` makes "API is down" indistinguishable from "no active items." At minimum, log; ideally, raise after the final attempt. 3. **Retrying non-retryable errors** — a 400/401/404 will never succeed on retry, but the code sleeps and retries anyway. O…
57.6s8060 output tokens

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Frequently asked questions

Which is cheaper, DeepSeek V4.1 Flash or Kimi K3?
Per 1M output tokens, DeepSeek V4.1 Flash is ¥202.74 and Kimi K3 is ¥2,680.5 on FastMetal (yen, before tax), so DeepSeek V4.1 Flash is cheaper.
How do the context windows of DeepSeek V4.1 Flash and Kimi K3 compare?
DeepSeek V4.1 Flash takes 1,048,576 tokens; Kimi K3 takes 1,048,576.
Can I use DeepSeek V4.1 Flash and Kimi K3 with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "deepseek-v4.1-flash" or "kimi-k3" 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 DeepSeek V4.1 Flash and Kimi K3 from the browser chat and the API. No monthly fee.

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