llama-3.1-405b-instruct

completions

bydeepinfra

llama-3.1-405b-instruct

completions

Published by: metaProvider:

deepinfra

The highly anticipated 400B class of Llama3 is here! Clocking in at 128k context with impressive eval scores, the Meta AI team continues to push the frontier of open-source LLMs. Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 405B instruct-tuned version is optimized for high quality dialogue usecases. It has demonstrated strong performance compared to leading closed-source models including GPT-4o and Claude 3.5 Sonnet in evaluations. To read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3-1/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).

Released

Jul 23, 2024

Knowledge

Jan 25, 2024

License

llama_3_1_community_license

Context

32768

Input

$0.8 / 1M tokens

Output

$0.8 / 1M tokens

Capabilities: tools

Accepts: text

Returns: text

Released Jul 23, 2024Knowledge Cutoff: Jan 25, 2024License: llama_3_1_community_license

Context: 32768 Input: $0.8 / 1M tokensOutput: $0.8 / 1M tokensCapabilities: toolsAccepts: textReturns: text

Access llama-3.1-405b-instruct through LangDB AI Gateway

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Benchmark Results for llama-3.1-405b-instruct

Category Performance Scores:

Academia: Score 38.40 (Top 58% - Rank #201)
Finance: Score 14.35 (Top 91% - Rank #314)
Marketing: Score 35.14 (Top 68% - Rank #235)
Maths: Score 3.00 (Top 96% - Rank #332)
Programming: Score 30.20 (Top 44% - Rank #152)
Science: Score 54.50 (Top 58% - Rank #201)
Writing: Score 36.15 (Top 70% - Rank #242)

Overall Performance: 30.24825396825397 average score across all categories

Detailed Benchmark Scores:

Benchmark	Score	Percentile	Domain
AIME	21.30	Top 52%	Mathematics
AA Coding Index	30.20	Top 44%	Programming
AAII	25.70	Top 58%	General
AA Math Index	3.00	Top 96%	Mathematics
DROP	84.80	Top 37%	General Knowledge
GPQA	51.10	Top 55%	STEM (Physics, Chemistry, Biology)
HLE	4.20	Top 72%	General Knowledge
HumanEval	89.00	Top 23%	Programming
LiveCodeBench	30.50	Top 50%	Programming
MATH-500	70.30	Top 63%	Mathematics
MMLU	87.30	Top 36%	General Knowledge
MMLU-Pro	73.25	Top 49%	General Knowledge
SciCode	29.90	Top 41%	Scientific

MMLU Score: 87.30 - Massive Multitask Language Understanding benchmark

HumanEval Score: 89.00 - Coding capability benchmark

GPQA Score: 51.10 - Graduate-level reasoning benchmark

Model Comparison:

Provider: deepinfra

Model Type: completions

Context Size: 32768 tokens

Comparing against 345 models in the database

Performance Analytics for llama-3.1-405b-instruct

Usage Statistics (Last 1 Days):

Total Requests: 6 API calls
Average TPS: 61.35 tokens per second
Average Response Time: 6753.90ms
Average Time to First Token: 444.60ms
Total Cost: $0.00
Average Request Cost: $0.0004

Daily Performance Breakdown:

Date	Requests	TPS	Response Time	TTFT	Cost
9/17/2025	6	61.35	6753.90ms	444.60ms	$0.00

Performance Summary:

Model: llama-3.1-405b-instruct by deepinfra

Monitoring Period: 9/12/2025 to 9/19/2025

Average Daily Requests: 6

Peak Daily Requests: 6

Statistics

View Full Statistics

Request Volume

Daily API requests

Performance (TPS)

Tokens per second

61.35 tokens/s

Category Scores

Benchmark Tests

View Other Benchmarks

AIME

21.3

Mathematics

AA Coding Index

30.2

Programming

AAII

25.7

General

AA Math Index

3.0

Mathematics

DROP

84.8

General Knowledge

GPQA

51.1

STEM (Physics, Chemistry, Biology)

HLE

4.2

General Knowledge

HumanEval

89.0

Programming

LiveCodeBench

30.5

Programming

MATH-500

70.3

Mathematics

MMLU

87.3

General Knowledge

MMLU-Pro

73.3

General Knowledge

SciCode

29.9

Scientific

Metric	AIME	AA Coding Index	AAII	AA Math Index	DROP	GPQA	HLE	HumanEval	LiveCodeBench	MATH-500	MMLU	MMLU-Pro	SciCode
Score	21.3	30.2	25.7	3.0	84.8	51.1	4.2	89.0	30.5	70.3	87.3	73.3	29.9

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Code Examples

Integration samples and API usage

Code Samples for llama-3.1-405b-instruct

Python SDK Example:

from openai import OpenAI

client = OpenAI(
    base_url="https://api.us-east-1.langdb.ai/projects/<your_project_id>",
    api_key="<your_api_key>"
)

response = client.chat.completions.create(
    model="llama-3.1-405b-instruct",
    messages=[
        {"role": "user", "content": "Hello, how are you?"}
    ]
)

print(response.choices[0].message.content)

TypeScript SDK Example:

import OpenAI from 'openai';

const client = new OpenAI({
    baseURL: "https://api.us-east-1.langdb.ai/projects/<your_project_id>",
    apiKey: "<your_api_key>"
});

const response = await client.chat.completions.create({
    model: "llama-3.1-405b-instruct",
    messages: [
        { role: "user", content: "Hello, how are you?" }
    ]
});

console.log(response.choices[0].message.content);

cURL Example:

curl -X POST "https://api.us-east-1.langdb.ai/projects/<your_project_id>/v1/chat/completions" \
  -H "Authorization: Bearer <your_api_key>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "llama-3.1-405b-instruct",
    "messages": [
        {"role": "user", "content": "Hello, how are you?"}
    ]
  }'

Model: llama-3.1-405b-instruct

Provider: deepinfra

API Endpoint: $https://api.us-east-1.langdb.ai

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llama-3.1-405b-instruct by deepinfra - AI Model Details, Pricing, and Performance Metrics

llama-3.1-405b-instruct

llama-3.1-405b-instruct

Access llama-3.1-405b-instruct through LangDB AI Gateway

Statistics

Category Scores

Benchmark Tests

Compare with Similar Models

Code Examples

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