Gemini 3.5 Flash vs Llama 3.3 70B Instruct
Pricing, context window and real answers (September 2026)
Gemini 3.5 Flash (Google) and Llama 3.3 70B Instruct (Meta), 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
 Gemini 3.5 Flash |  Llama 3.3 70B Instruct | |
|---|---|---|
| Provider | Meta | |
| Input (per 1M tokens) | ¥268.05 | ¥17.87 |
| Output (per 1M tokens) | ¥1,608.3 | ¥57.18 |
| Typical cost (1,000 in + 500 out tokens × 1,000 calls) | ¥1,072 | ¥46 |
| Context window | 1,048,576 tokens | 131,072 tokens |
| Release date | 5/19/2026 | 12/6/2024 |
| Input modalities | text, image, video, file, audio | text |
| Throughput (p50) | — | — |
| Arena · overall | #25 · ELO 1,478 | #250 · ELO 1,318 |
| Arena · Japanese | #19 · ELO 1,468 | #210 · ELO 1,212 |
| Arena · coding | #55 · ELO 1,506 | #263 · ELO 1,346 |
Prices are FastMetal's yen rates before tax. Arena ranks are as of the latest leaderboard scrape.
Which should you pick?
- On price, Llama 3.3 70B Instruct: ¥57.18 per 1M output tokens, 96% less than Gemini 3.5 Flash.
- On the Overall arena board, Gemini 3.5 Flash ranks higher (#25; Llama 3.3 70B Instruct is #250).
- On the Japanese arena board, Gemini 3.5 Flash ranks higher (#19; Llama 3.3 70B Instruct is #210).
- On the Coding arena board, Gemini 3.5 Flash ranks higher (#55; Llama 3.3 70B Instruct is #263).
- For long documents, Gemini 3.5 Flash: a 1,048,576-token context window against 131,072 for Llama 3.3 70B Instruct.
- 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.
Gemini 3.5 Flash
There are **3** 'r's in the word "strawberry".
Here is the step-by-step breakdown of how to count them:
1. **Break the word down into its individual letters:**
* 1st letter: **s**
* 2nd letter: **t**
* 3rd letter: **r** (First 'r')
* 4th letter: **a**
* 5th letter: **w**
* 6th letter: **b**
* 7th letter: **e**
* 8th letter: **r** (Second 'r')
* 9th letter: **r** (Third 'r')
* 10th letter: **y**
2. **Identify and count only the 'r's:**
* s - t - **r** (1) - a - w - b - e - **r** (2) - **r** (3) - y
By counting them as we go through the word, we find a total of **3** 'r's.
4.8s601 output tokens
Llama 3.3 70B Instruct
To count the number of 'r's in 'strawberry', I'll break down the word into its individual letters and then examine each one to identify the 'r's. Here are the steps:
1. **Write down the word 'strawberry' with its individual letters separated**: s-t-r-a-w-b-e-r-r-y
2. **Examine each letter to find the 'r's**: Going through the word letter by letter, I identify the 'r's.
- The first 'r' appears after 't', so that's one 'r'.
- Continuing through the word, I find another 'r' after 'e', which gives me a second 'r'.
- Then, immediately after this second 'r', I find a third 'r'.
3. **Count the total number of 'r's identified**: From the step above, I've identified a total of 3 'r's in th…
12.6s217 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…
Gemini 3.5 Flash
### What is causing this error?
The error `TypeError: Cannot read properties of undefined (reading 'map')` means that your `UserList` component is trying to call `.map()` on the `users` variable, but **`users` is currently `undefined`**.
This usually happens for one of two reasons:
1. **The parent component forgot to pass the prop:** `<UserList />` was rendered without the `users` attribute.
2. **Asynchronous data fetching:** The parent component fetches the users from an API, but the API request hasn't finished yet when the component first renders, so `users` starts as `undefined`.
---
### How to fix it
Here are the three best ways to fix this, depending on how you want your UI to beh…
11.2s1524 output tokens
Llama 3.3 70B Instruct
# Step-by-step analysis of the problem:
1. **The error is occurring because the `map()` function is being called on `undefined`**: This means that the `users` prop is not being passed to the `UserList` component, or its value is `undefined`.
2. **The `map()` function is a method of arrays**: It is used to iterate over the elements of an array and apply a transformation to each element. If `users` is not an array (i.e., it's `undefined`), this method will not be available, hence the error.
3. **To fix this error, you need to ensure that `users` is always an array**: You can achieve this by adding a conditional statement to check if `users` is an array before calling `map()` on it.
# Fixed so…
28.4s560 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):…
Gemini 3.5 Flash
Here is a review of your function, followed by two improved versions (one that keeps your structure but makes it Pythonic, and one production-ready version that uses industry best practices).
---
### Key Areas for Improvement
1. **Imports inside the function:** `import requests` and `import time` should be at the top of the file (PEP 8). Keeping them inside the function slows down execution if the function is called repeatedly.
2. **Bare `except:` clause:** Using `except:` without specifying an exception type is a major anti-pattern. It catches things you don't want to catch, like `KeyboardInterrupt` (Ctrl+C) or `SystemExit`. It should target `requests.RequestException`.
3. **Implicit `Tr…
19.7s2975 output tokens
Llama 3.3 70B Instruct
### Review and Suggestions
The provided Python function `get_data` appears to be designed to fetch data from a given URL, filter active items, and return the filtered results. Here's a review of the function focusing on readability, performance, and best practices, along with suggestions for improvement.
#### Issues and Improvements:
1. **Import Statements**: Import statements should be placed at the top of the file, not inside the function. This adheres to PEP 8, the official Python style guide.
2. **Exception Handling**: The `except` block is too broad. It's better to catch specific exceptions that you anticipate might occur. For example, `requests.get` might raise `requests.RequestExc…
40.3s815 output tokens
Frequently asked questions
- Which is cheaper, Gemini 3.5 Flash or Llama 3.3 70B Instruct?
- Per 1M output tokens, Gemini 3.5 Flash is ¥1,608.3 and Llama 3.3 70B Instruct is ¥57.18 on FastMetal (yen, before tax), so Llama 3.3 70B Instruct is cheaper.
- How do the context windows of Gemini 3.5 Flash and Llama 3.3 70B Instruct compare?
- Gemini 3.5 Flash takes 1,048,576 tokens; Llama 3.3 70B Instruct takes 131,072.
- Which ranks higher, Gemini 3.5 Flash or Llama 3.3 70B Instruct?
- Gemini 3.5 Flash ranks higher on the public arena (Gemini 3.5 Flash #19, Llama 3.3 70B Instruct #210). Ranks move as the leaderboard updates.
- Can I use Gemini 3.5 Flash and Llama 3.3 70B Instruct with the same API key?
- Yes. On FastMetal's OpenAI-compatible endpoint, switch by passing "gemini-3.5-flash" or "llama-3.3-70b-instruct" 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 Gemini 3.5 Flash and Llama 3.3 70B Instruct from the browser chat and the API. No monthly fee.