llama-3.1-8b-instruct

completions

On:deepinfragroq

llama-3.1-8b-instruct

completions

Published by: metaProviders:

deepinfra groq

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/).

Provider	Input	Output
deepinfra	$0.01 / 1M tokens	$0.02 / 1M tokens
groq	$0.05 / 1M tokens	$0.08 / 1M tokens

Released

Jul 23, 2024

Knowledge

Dec 31, 2023

Context

131072

Input

$0.01 / 1M tokens

Output

$0.02 / 1M tokens

Capabilities: tools

Accepts: text

Returns: text

Providers	Context	Input Price	Output Price	Input Formats	Output Formats	License
deepinfra	131072 tokens	$0.01 / 1M tokens	$0.02 / 1M tokens	text	text	llama_3_1_community_license
groq	131072 tokens	$0.05 / 1M tokens	$0.08 / 1M tokens	text	text	Meta Llama Community

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

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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10,000+Monthly Requests

Available from 2 providers

Provider:

Benchmark Results for llama-3.1-8b-instruct

Category Performance Scores:

Academia: Score 22.52 (Top 87% - Rank #292)
Finance: Score 10.60 (Top 97% - Rank #325)
Marketing: Score 28.37 (Top 94% - Rank #315)
Maths: Score 4.30 (Top 94% - Rank #315)
Programming: Score 8.50 (Top 96% - Rank #322)
Science: Score 33.29 (Top 92% - Rank #309)
Writing: Score 27.80 (Top 95% - Rank #319)

Overall Performance: 19.340555555555557 average score across all categories

Detailed Benchmark Scores:

Benchmark	Score	Percentile	Domain
AIME	7.70	Top 75%	Mathematics
AA Coding Index	8.50	Top 96%	Programming
AAII	16.90	Top 81%	General
AA Math Index	4.30	Top 94%	Mathematics
DROP	59.50	Top 89%	General Knowledge
GPQA	28.15	Top 96%	STEM (Physics, Chemistry, Biology)
HLE	5.10	Top 41%	General Knowledge
HumanEval	72.60	Top 84%	Programming
LiveCodeBench	11.60	Top 91%	Programming
MATH-500	51.90	Top 90%	Mathematics
MMLU	69.40	Top 87%	General Knowledge
MMLU-Pro	47.95	Top 91%	General Knowledge
SciCode	13.20	Top 88%	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 335 models in the database

Performance Analytics for llama-3.1-8b-instruct

Usage Statistics (Last 3 Days):

Total Requests: 14 API calls
Average TPS: 1154.93 tokens per second
Average Response Time: 1941.90ms
Average Time to First Token: 1941.90ms
Total Cost: $0.00
Average Request Cost: $0.0000

Daily Performance Breakdown:

Date	Requests	TPS	Response Time	TTFT	Cost
10/2/2025	2	2128.79	977.30ms	977.30ms	$0.00
10/7/2025	8	849.98	2477.00ms	2477.00ms	$0.00
10/9/2025	4	1919.14	1354.10ms	1354.10ms	$0.00

Performance Summary:

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

Monitoring Period: 10/2/2025 to 10/9/2025

Average Daily Requests: 5

Peak Daily Requests: 8

Statistics

View Full Statistics

Request Volume

Daily API requests

Performance (TPS)

Tokens per second

1154.93 tokens/s

Category Scores

Benchmark Tests

View Other Benchmarks

AIME

7.7

Mathematics

AA Coding Index

8.5

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	8.5	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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