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Meta · Open weights

Llama 3.1 8b Instruct

Added Jan 1, 2024Open weights

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Use in the app

Fast and efficient for simple purposes.

  • Tools
Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.02
Output
$0.04

Reference prices as published by the model provider. API example

Specifications

Context window
131.1K
Max output
16.4K
Average output (7 days)
57 tokens
Longer than 5% of 465 models

Side by side

Llama 3.1 8b Instruct compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Llama 3.1 8b InstructMetaThis modelLlama 3.3 70b InstructMetaRemove
ProviderMetaMeta
Discovery tierOpen weightsOpen weights
AddedJan 1, 2024Feb 27, 2025
Limits
Context window131.07K131.07K
Max output16.38K16.38K
Average output57 tokens37 tokens
Pricing, USD per 1M tokens
Input$0.02Best$0.05
Output$0.04Best$0.23
Performance
Throughput45.2 tok/sBest18.1 tok/s
Time to first token1.8 sBest4.3 s
Request success (24h)100.0%Best99.9%
Benchmark indexes
Intelligence Index6.97.7Best
Coding Index5.411.9Best
Math Index4.37.7Best
Capabilities
ToolsYesYes
Structured outputNoYes
Reasoning effort——

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Llama 3.1 8b Instruct
  • Llama 3.3 70b Instruct

Intelligence Index

  • Llama 3.1 8b Instruct6.9
  • Llama 3.3 70b Instruct7.7

Llama 3.1 8b Instruct: Better than 8% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Llama 3.1 8b Instruct: 5.4
    • Llama 3.3 70b Instruct: 11.9Top

  • Math Index

    Composite of the math evaluations

    • Llama 3.1 8b Instruct: 4.3
    • Llama 3.3 70b Instruct: 7.7Top

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Llama 3.1 8b Instruct: 18.0%Top
    • Llama 3.3 70b Instruct: 15.7%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Llama 3.1 8b Instruct: 5.3%Top
    • Llama 3.3 70b Instruct: 3.6%

  • GPQA Diamond

    Graduate-level science questions

    • Llama 3.1 8b Instruct: 25.9%
    • Llama 3.3 70b Instruct: 49.8%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Llama 3.1 8b Instruct: 47.6%
    • Llama 3.3 70b Instruct: 71.3%Top

  • IFBench

    Following precise output instructions

    • Llama 3.1 8b Instruct: 28.6%
    • Llama 3.3 70b Instruct: 47.1%Top

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • Llama 3.1 8b Instruct: 11.6%
    • Llama 3.3 70b Instruct: 28.8%Top

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Llama 3.1 8b Instruct: 4.3%
    • Llama 3.3 70b Instruct: 7.7%Top

  • AIME

    Competition mathematics

    • Llama 3.1 8b Instruct: 7.7%
    • Llama 3.3 70b Instruct: 30.0%Top

  • MATH-500

    Competition math problems

    • Llama 3.1 8b Instruct: 51.9%
    • Llama 3.3 70b Instruct: 77.3%Top

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Llama 3.1 8b Instruct: 0.8%
    • Llama 3.3 70b Instruct: 3.0%Top

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Llama 3.1 8b Instruct: 16.4%
    • Llama 3.3 70b Instruct: 26.6%Top

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Llama 3.1 8b Instruct: 18.0%Top
    • Llama 3.3 70b Instruct: 15.7%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Throughput
45.2 tok/s
Faster than 33% of 251 models
Time to first token
1.8 s
Quicker than 80% of 251 models
Prompt cache hits
0.0%
Request success (24h)
100.0%
Reliable

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Hourly request success · last 72 hoursLowest hour 100.0%
  • Healthy (98% or more)
  • Degraded (90–98%)
  • Down (under 90%)
  • No requests

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "meta-llama/llama-3.1-8b-instruct",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="meta-llama/llama-3.1-8b-instruct",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Meta

Other Meta models, starting with the same family.