Last refreshed 2026-07-09. Next refresh: weekly.
Why use Llama 3.1 405B Instruct on Fireworks AI?
Fireworks AI offers Llama 3.1 405B Instruct with pay-as-you-go pricing at $3.00/1M input tokens. Fireworks AI offers a generative AI platform as a service, focusing on rapid product iteration and cost-efficient AI deployment.
Compare Llama 3.1 405B Instruct across 11 providers to find the best fit for your use caseSetup recipe
Python + curlpip install openaiexport FIREWORKS_API_KEY=...import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],accounts/fireworks/models/llama-v3p1-405b-instructRequest example
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],
base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
model="accounts/fireworks/models/llama-v3p1-405b-instruct",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "accounts/fireworks/models/llama-v3p1-405b-instruct", not the LLMReference slug "llama3.1-405b-instruct".
- Fireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
- The examples expect FIREWORKS_API_KEY; rename it only if your application config maps the new variable.
Compare Llama 3.1 405B Instruct Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| OctoAI API (Deprecated) | — | — |
| Together AI | $5.00 | $15.00 |
| Fireworks AI | $3.00 | $3.00 |
| IBM watsonx | $3.00 | $9.00 |
| Scale AI GenAI Platform | — | — |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $3.00 |
| Output tokens | $3.00 |
Capabilities
About Llama 3.1 405B Instruct
Llama 3.1 405B Instruct is Meta's advanced large language model released on July 23, 2024, featuring 405 billion parameters. It utilizes an optimized transformer architecture with supervised fine-tuning and reinforcement learning for enhanced instruction-following capabilities. The model supports multiple languages, was trained on 15 trillion tokens, and fine-tuned with 25 million synthetic examples. It excels in multilingual dialogue and text generation, making it ideal for assistant-like applications. Llama 3.1 incorporates robust safety measures and ethical considerations, outperforming many existing models on various industry benchmarks.