Model comparison

Grok 4.6 vs LLM-jp-3.1 8x13B instruct4

Pricing, context window and real answers (August 2026)

Grok 4.6 (xAI) and LLM-jp-3.1 8x13B instruct4 (Llm Jp), 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

x-ai logoGrok 4.6LLM-jp-3.1 8x13B instruct4
ProviderxAILlm Jp
Input (per 1M tokens)¥357.4¥16
Output (per 1M tokens)¥1,072.2¥79
Typical cost (1,000 in + 500 out tokens × 1,000 calls)¥894¥56
Context window500,000 tokens4,096 tokens
Release date8/12/20263/21/2026
Input modalitiestext, image, filetext
Arena · overall#48 · ELO 1,461Unranked
Arena · JapaneseUnrankedUnranked
Arena · coding#44 · ELO 1,510Unranked

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

Which should you pick?

  • On price, LLM-jp-3.1 8x13B instruct4: ¥79 per 1M output tokens, 93% less than Grok 4.6.
  • For long documents, Grok 4.6: a 500,000-token context window against 4,096 for LLM-jp-3.1 8x13B instruct4.
  • 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.

Grok 4.6

The word "strawberry" consists of the following letters in order: s-t-r-a-w-b-e-r-r-y Checking each one: - s: not r - t: not r - r: yes (count = 1) - a: not r - w: not r - b: not r - e: not r - r: yes (count = 2) - r: yes (count = 3) - y: not r There are exactly 3 r's. Final answer: 3
3.9s451 output tokens

LLM-jp-3.1 8x13B instruct4

To count the number of 'r's in the word 'strawberry', follow these steps: 1. Identify the word: The word we are examining is 'strawberry'. 2. Understand the task: We need to find and count all occurrences of the letter 'r' in this word. 3. Begin with the first letter: The first letter is 's', which is not 'r', so we move on to the next letter. 4. Proceed to the second letter: The second letter is 't', which is also not 'r', so we continue to the third letter. 5. Reach the third letter: The third letter is 'r'. We have found one 'r'. 6. Continue to the fourth letter: The fourth letter is 'a', which is not 'r', so we move on to the fifth letter. 7. Examine the fifth letter: The fifth letter i…
4.0s400 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…

Grok 4.6

**The error happens because `users` is `undefined` when `.map()` is called.** `UserList` destructures `{ users }` from its props. If the parent doesn't pass a `users` prop (or passes `undefined`/`null`), `users` is `undefined` and `undefined.map` throws. This is extremely common when: - Data is loaded asynchronously (initial render happens before the fetch finishes). - The parent component forgets to pass the prop or uses a different name. - The component is rendered before the data is ready (e.g. in a loading state). ### Quick fixes **1. Default to an empty array (recommended)** ```jsx function UserList({ users = [] }) { return ( <ul> {users.map(user => ( <li key={us…
20.3s598 output tokens

LLM-jp-3.1 8x13B instruct4

The error TypeError: Cannot read properties of undefined (reading 'map') suggests that the 'users' argument passed to the UserList component is undefined or does not have a 'map' method. The cause of the problem may be that the users variable is not being passed correctly or is not defined in the parent component. Check the props being passed to the UserList component to ensure that they are defined and contain the expected data. To fix the issue, you can add some error handling and debugging to your component. Try logging the users variable to the console to verify that it is not undefined: ```jsx function UserList({ users }) { console.log("Users:", users); if (!users) { return <…
3.0s279 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):…

Grok 4.6

Here is a focused review of the function, followed by a cleaned-up version. ## Issues **Imports inside the function** `requests` and `time` should live at module level. Importing on every call is slower, hides dependencies, and is harder to mock in tests. **Bare `except:`** This swallows `KeyboardInterrupt`, `SystemExit`, and programming errors. Catch `requests.RequestException` (network/timeout/HTTP adapter errors) and JSON/`KeyError`/`TypeError` separately. **Retrying the wrong things** A 404 or 400 will never succeed on retry. Retry transient failures (timeouts, connection errors, 429, 5xx). Fail fast on most 4xx responses. **Sleep after the last attempt** On the final failur…
27.9s1770 output tokens

LLM-jp-3.1 8x13B instruct4

The provided Python function aims to get data from a URL using the requests library, filter out specific items based on their "active" field, and return the result. Here are some suggestions to improve readability, performance, and adherence to best practices: 1. Configure the linter (e.g., flake8 or pylint) to ensure code quality and enforce a consistent coding style. 2. Use type hints to improve readability and maintainability. 3. Use context managers (with statement) for handling requests: 4. Rewrite the function using a more functional programming style: Here's the improved version of the function: ```python import requests import time from typing import List, Dict, Any def get_da…
3.9s406 output tokens

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Frequently asked questions

Which is cheaper, Grok 4.6 or LLM-jp-3.1 8x13B instruct4?
Per 1M output tokens, Grok 4.6 is ¥1,072.2 and LLM-jp-3.1 8x13B instruct4 is ¥79 on FastMetal (yen, before tax), so LLM-jp-3.1 8x13B instruct4 is cheaper.
How do the context windows of Grok 4.6 and LLM-jp-3.1 8x13B instruct4 compare?
Grok 4.6 takes 500,000 tokens; LLM-jp-3.1 8x13B instruct4 takes 4,096.
Can I use Grok 4.6 and LLM-jp-3.1 8x13B instruct4 with the same API key?
Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "grok-4.6" or "llm-jp-3.1-8x13b-instruct4" 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 Grok 4.6 and LLM-jp-3.1 8x13B instruct4 from the browser chat and the API. No monthly fee.

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