llama-3.1-8b-instruct

completions

bydeepinfra

llama-3.1-8b-instruct

completions

Published by: metaProvider:

deepinfra

Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance compared to leading closed-source models in human 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

Dec 31, 2023

License

llama_3_1_community_license

Context

131072

Input

$0.01 / 1M tokens

Output

$0.02 / 1M tokens

Capabilities: tools

Accepts: text

Returns: text

Released Jul 23, 2024Knowledge Cutoff: Dec 31, 2023License: llama_3_1_community_license

Context: 131072 Input: $0.01 / 1M tokensOutput: $0.02 / 1M tokensCapabilities: toolsAccepts: textReturns: text

Access llama-3.1-8b-instruct through LangDB AI Gateway

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Integrate with meta's llama-3.1-8b-instruct and 250+ other models through a unified API. Monitor usage, control costs, and enhance security.

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Benchmark Results for llama-3.1-8b-instruct

Category Performance Scores:

Academia: Score 22.52 (Top 83% - Rank #287)
Finance: Score 10.60 (Top 98% - Rank #339)
Marketing: Score 28.37 (Top 92% - Rank #318)
Maths: Score 4.30 (Top 93% - Rank #321)
Programming: Score 12.40 (Top 85% - Rank #294)
Science: Score 33.29 (Top 91% - Rank #314)
Writing: Score 27.80 (Top 93% - Rank #321)

Overall Performance: 19.897698412698414 average score across all categories

Detailed Benchmark Scores:

Benchmark	Score	Percentile	Domain
AIME	7.70	Top 68%	Mathematics
AA Coding Index	12.40	Top 85%	Programming
AAII	16.90	Top 74%	General
AA Math Index	4.30	Top 93%	Mathematics
DROP	59.50	Top 95%	General Knowledge
GPQA	28.15	Top 96%	STEM (Physics, Chemistry, Biology)
HLE	5.10	Top 31%	General Knowledge
HumanEval	72.60	Top 86%	Programming
LiveCodeBench	11.60	Top 88%	Programming
MATH-500	51.90	Top 86%	Mathematics
MMLU	69.40	Top 89%	General Knowledge
MMLU-Pro	47.95	Top 86%	General Knowledge
SciCode	13.20	Top 83%	Scientific

MMLU Score: 69.40 - Massive Multitask Language Understanding benchmark

HumanEval Score: 72.60 - Coding capability benchmark

GPQA Score: 28.15 - Graduate-level reasoning benchmark

Model Comparison:

Provider: deepinfra

Model Type: completions

Context Size: 131072 tokens

Comparing against 345 models in the database

Performance Analytics for llama-3.1-8b-instruct

Usage Statistics (Last 3 Days):

Total Requests: 13 API calls
Average TPS: 2980.74 tokens per second
Average Response Time: 1446.10ms
Average Time to First Token: 1446.10ms
Total Cost: $0.00
Average Request Cost: $0.0001

Daily Performance Breakdown:

Date	Requests	TPS	Response Time	TTFT	Cost
9/16/2025	2	2059.62	1673.40ms	1673.40ms	$0.00
9/17/2025	8	2846.27	1535.50ms	1535.50ms	$0.00
9/19/2025	3	4475.19	1056.00ms	1056.00ms	$0.00

Performance Summary:

Model: llama-3.1-8b-instruct by deepinfra

Monitoring Period: 9/13/2025 to 9/20/2025

Average Daily Requests: 4

Peak Daily Requests: 8

Statistics

View Full Statistics

Request Volume

Daily API requests

Performance (TPS)

Tokens per second

2980.74 tokens/s

Category Scores

Benchmark Tests

View Other Benchmarks

AIME

7.7

Mathematics

AA Coding Index

12.4

Programming

AAII

16.9

General

AA Math Index

4.3

Mathematics

DROP

59.5

General Knowledge

GPQA

28.1

STEM (Physics, Chemistry, Biology)

HLE

5.1

General Knowledge

HumanEval

72.6

Programming

LiveCodeBench

11.6

Programming

MATH-500

51.9

Mathematics

MMLU

69.4

General Knowledge

MMLU-Pro

48.0

General Knowledge

SciCode

13.2

Scientific

Metric	AIME	AA Coding Index	AAII	AA Math Index	DROP	GPQA	HLE	HumanEval	LiveCodeBench	MATH-500	MMLU	MMLU-Pro	SciCode
Score	7.7	12.4	16.9	4.3	59.5	28.1	5.1	72.6	11.6	51.9	69.4	48.0	13.2

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Code Examples

Integration samples and API usage

Code Samples for llama-3.1-8b-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-3.1-8b-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-3.1-8b-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-3.1-8b-instruct",
    "messages": [
        {"role": "user", "content": "Hello, how are you?"}
    ]
  }'

Model: llama-3.1-8b-instruct

Provider: deepinfra

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

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llama-3.1-8b-instruct by deepinfra - AI Model Details, Pricing, and Performance Metrics

llama-3.1-8b-instruct

llama-3.1-8b-instruct

Access llama-3.1-8b-instruct through LangDB AI Gateway

Statistics

Category Scores

Benchmark Tests

Compare with Similar Models

Code Examples

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