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Llama 3.1 8B Instruct

Up to 30%Deprecated 27 May 2026

Llama 3.1 8B Instruct brings Meta conversational intelligence to LLM.API so teams can ship assistants and agents without juggling multiple vendor SDKs.

Start Using API

What is Llama 3.1 8B Instruct?

On LLM.API, Llama 3.1 8B Instruct (llama-3.1-8b-instruct) serves as a Meta conversational model for products that need 128K tokens context windows and predictable token pricing. llama-3.1-8b-instruct provided by aws-bedrock, nebius, novita. It is wired for API access through LLM.API with OpenAI-compatible patterns.

Providers

LLM.API routes Llama 3.1 8B Instruct to the providers below, with discounted effective rates versus list price.

List price by provider ($ / 1M tokens)

InputOutput
aws-bedrock$0.22 in
$0.22 out
nebius$0.02 in
$0.06 out
novita$0.02 in
$0.05 out

Provider list prices; the LLM.API discount applies on top.

ProviderPricingContextCapabilities
aws-bedrock30% offin $220; out $220 per 1M tokens128K tokenstools, streaming, JSON, structured
nebius30% offin $20; out $60 per 1M tokens128K tokenstools, streaming, JSON, structured
novita30% offin $20; out $50 per 1M tokens128K tokenstools, streaming, JSON

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 21 Sept 2026.

Try this model

Test Llama 3.1 8B Instruct right here — free to start.

Llama 3.1 8B Instruct
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call Llama 3.1 8B Instruct through the OpenAI-compatible API — POST /v1/chat/completions.

python
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_LLMAP_KEY",
    base_url="https://api.llmapi.ai/v1",
)

resp = client.chat.completions.create(
    model="llama-3.1-8b-instruct",
    messages=[
        {"role": "system", "content": "You are a precise product assistant."},
        {"role": "user", "content": "Give me three crisp launch checklist items."},
    ],
)
print(resp.choices[0].message.content)
{
  "model": "llama-3.1-8b-instruct",
  "messages": [
    {"role": "system", "content": "You are a precise product assistant."},
    {"role": "user", "content": "Give me three crisp launch checklist items."}
  ]
}

5 Core Capabilities

  • Structured outputs

    Can produce JSON-friendly or schema-oriented responses when prompted carefully. Relevant for `llama-3.1-8b-instruct` workloads on LLM.API.

  • Analytical writing

    Produces clear analyses, comparisons, and decision memos from messy source material. Relevant for `llama-3.1-8b-instruct` workloads on LLM.API.

  • Multi-step reasoning

    Breaks down complex problems into intermediate steps before answering. Reflects Meta positioning for this endpoint.

  • Multilingual drafting

    Drafts and translates professional content across major business languages. Tuned to how teams typically call Llama 3.1 8B Instruct.

  • Conversational UX

    Maintains coherent multi-turn assistant behavior for product chat surfaces.

6 Most Valuable Use Cases

  • Sales and success email drafting with CRM context with Llama 3.1 8B Instruct
  • Policy Q&A bots with careful refusal behavior
  • Internal knowledge assistants grounded with your retrieval layer with Llama 3.1 8B Instruct
  • Product analytics narration and anomaly explanations
  • Research synthesis across long documents and tickets with Llama 3.1 8B Instruct
  • Data extraction into JSON for downstream systems

Why Build on LLM.API?

One unified API. Every major model. Built-in reliability, cost control, and observability.

  • Intelligent AI Routing

    Automatically route each request to the best model across providers based on latency, cost, and quality—without changing your integration or redeploying code.

    One endpoint, every model.

  • Cost-Aware Execution

    Control spend with per-request cost estimation, smart model selection, and centralized quotas so teams can experiment fast without runaway bills or manual tracking.

    More performance, less spend.

  • Resilient Fallback Flows

    Define automatic, provider-agnostic fallbacks to keep your app up during outages, rate limits, or timeouts—no brittle failover logic scattered through your codebase.

    Never go dark on users.

  • Deep LLM Observability

    Trace every call across providers with logs, metrics, and request replay so you can debug, tune prompts, and optimize model choices from one unified dashboard.

    See every token, everywhere.

  • Task-Level Orchestration

    Describe tasks, not models. LLM.API maps them to the right tools, models, and prompts so you ship complex AI workflows with minimal glue code.

    Think tasks, not models.

  • High-Throughput Batch APIs

    Process millions of inferences efficiently with optimized batch pipelines, concurrency controls, and retry logic—all behind the same simple interface you use for single calls.

    Scale from 1 to millions.

Why run Llama 3.1 8B Instruct on LLM.API?

  • Unified AI Routing

    Reach Llama 3.1 8B Instruct and sibling models through one OpenAI-compatible endpoint.

  • Cost Control

    Production: Compare provider price points and keep spend visible as you scale Llama 3.1 8B Instruct.

  • Reliability Layer

    Practical: Retry and route across configured providers when a single upstream blips.

  • Observability

    Production: Trace prompts, tokens, and errors for Llama 3.1 8B Instruct alongside the rest of your stack.

  • Drop-in SDKs

    Practical: Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.

  • Model Breadth

    Production: Swap Llama 3.1 8B Instruct for chat, media, or embedding alternatives without rewriting auth.

When to Use — When NOT to Use

Use it if...

  • You need provider failover options exposed for this model id (Llama 3.1 8B Instruct)
  • You want OpenAI-compatible chat completions through a single LLM.API key (Llama 3.1 8B Instruct)
  • You need a general-purpose text model for assistants, agents, or content workflows (Llama 3.1 8B Instruct)
  • Your prompts benefit from the model's family strengths (reasoning, speed, or cost) (Llama 3.1 8B Instruct)

Avoid if...

  • You need pure embedding, OCR, or media generation instead of chat
  • You require on-prem only deployment with no cloud inference
  • You need guaranteed real-time hard latency SLAs without benchmarking the provider
  • Your use case depends on unpublished proprietary benchmarks not listed here

COMMUNITY

What developers say about Llama models

Summarised from publicly published developer and community reviews of this model family. Opinions are the sources’, not LLM.API’s, and may not be specific to Llama 3.1 8B Instruct.

  • Independent testers were underwhelmed by Llama 4 coding performance relative to the launch messaging around its very long context window.
  • The architecture shift to mixture-of-experts and native multimodality is seen as the real story for teams self-hosting open weights.
  • Most reviewers position Llama as an integration and deployment choice rather than a benchmark leader.

SOURCES

Frequently Asked Questions

  • Where is the canonical page for Llama 3.1 8B Instruct?

    https://llmapi.ai/models/meta-llama-llama-3-1-8b-instruct/

  • Does Llama 3.1 8B Instruct support streaming?

    Yes—at least one listed provider advertises streaming.

  • Can I use tools or structured outputs with Llama 3.1 8B Instruct?

    Tool and/or structured-output flags appear on one or more providers for this model—confirm in the providers table.

  • Which providers serve Llama 3.1 8B Instruct?

    LLM.API currently lists: aws-bedrock, nebius, novita. Availability can vary by region and account.

  • How is Llama 3.1 8B Instruct priced on LLM.API?

    Listed pricing metadata shows: In $0.22 / 1M tokens · Out $0.22 / 1M tokens. LLM.API may offer discounted effective rates (illustrative ~30% callout vs list when available).. Confirm live rates in the LLM.API dashboard or docs before production budgeting.

  • What is the context length for Llama 3.1 8B Instruct?

    Reported context for Llama 3.1 8B Instruct is 128K tokens. Always verify the active provider row if multiple providers are listed.

  • What modalities does Llama 3.1 8B Instruct support?

    Llama 3.1 8B Instruct accepts text and produces text according to its architecture metadata on LLM.API.

  • How do I call Llama 3.1 8B Instruct via API?

    Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "llama-3.1-8b-instruct" and your LLM.API key. See the code snippet on this page.

  • When should I choose Llama 3.1 8B Instruct?

    You need provider failover options exposed for this model id — especially when you specifically need Llama 3.1 8B Instruct.

  • What are limitations of Llama 3.1 8B Instruct?

    Like other API models, Llama 3.1 8B Instruct can be wrong, incomplete, or uneven on edge cases. Validate outputs for high-stakes use. Media/OCR/STT models additionally depend on input quality.

  • What is Llama 3.1 8B Instruct?

    llama-3.1-8b-instruct provided by aws-bedrock, nebius, novita. It is wired for API access through LLM.API with OpenAI-compatible patterns. On LLM.API it is addressed as `llama-3.1-8b-instruct`.

  • Is Llama 3.1 8B Instruct a chat model?

    Yes—Llama 3.1 8B Instruct is exposed as a chat/completions-style endpoint on LLM.API.

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