LLM-jp-3.1 8x13B instruct4 vs Solar Pro 4
Pricing, context window and real answers (August 2026)
LLM-jp-3.1 8x13B instruct4 (Llm Jp) and Solar Pro 4 (Upstage), 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
| LLM-jp-3.1 8x13B instruct4 | Solar Pro 4 | |
|---|---|---|
| Provider | Llm Jp | Upstage |
| Input (per 1M tokens) | ¥16 | ¥5.28 |
| Output (per 1M tokens) | ¥79 | ¥21.11 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥56 | ¥16 |
| Context window | 4,096 tokens | 524,288 tokens |
| Release date | 3/21/2026 | 8/10/2026 |
| Input modalities | text | text |
| Arena · overall | Unranked | #173 · ELO 1,376 |
| Arena · Japanese | Unranked | Unranked |
| Arena · coding | Unranked | #140 · ELO 1,448 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, Solar Pro 4: ¥21.11 per 1M output tokens, 73% less than LLM-jp-3.1 8x13B instruct4.
- For long documents, Solar Pro 4: a 524,288-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.
LLM-jp-3.1 8x13B instruct4
Solar Pro 4
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…
LLM-jp-3.1 8x13B instruct4
Solar Pro 4
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):…
LLM-jp-3.1 8x13B instruct4
Solar Pro 4
Frequently asked questions
- Which is cheaper, LLM-jp-3.1 8x13B instruct4 or Solar Pro 4?
- Per 1M output tokens, LLM-jp-3.1 8x13B instruct4 is ¥79 and Solar Pro 4 is ¥21.11 on FastMetal (yen, before tax), so Solar Pro 4 is cheaper.
- How do the context windows of LLM-jp-3.1 8x13B instruct4 and Solar Pro 4 compare?
- LLM-jp-3.1 8x13B instruct4 takes 4,096 tokens; Solar Pro 4 takes 524,288.
- Can I use LLM-jp-3.1 8x13B instruct4 and Solar Pro 4 with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "llm-jp-3.1-8x13b-instruct4" or "solar-pro4" 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 LLM-jp-3.1 8x13B instruct4 and Solar Pro 4 from the browser chat and the API. No monthly fee.