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Llama 3.1 8B Instruct

Chat model by Meta.

Meta language model featuring a 128,000-token context window. Engineered for dialogue, instruction following, and versatile text generation.

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Models / Llama 3.1 8B InstructID: bedrock/us.meta.llama3-1-8b-instruct-v1:0

Maker

Meta

Served On: AWS Bedrock

Specifications

Context window, ranked against other chat models

Proportional scale: 0 to 1.05M tokens. Not ranked, no published context window: qwen-plus-2025-09-11, voxtral-small-24b-2507, qwen3.6-plus-2026-04-02.

Context window

—

Max output

—

Modality

chat

Vision
Function calling
System prompt

Pricing

Rates are read live

Pricing for llama3-1-8b-instruct is fetched from the live catalogue on load, so it is never served from a cache that could outlive a repricing.

Provider-Reported Capabilities

What the hosting provider reports for this model, shown as it was returned. nRouter adds nothing to this report and infers nothing that is missing from it.

Converse converse

null

Model Name modelName

Llama 3.1 8B Instruct

Description description

null

Model Family modelFamily

null

Provider Name providerName

Meta

Batch Supported batchSupported

null

Model Lifecycle modelLifecycle
Status status

ACTIVE

Legacy Time legacyTime

null

End Of Life Time endOfLifeTime

null

Public Extended Access Time publicExtendedAccessTime

null

Input Modalities inputModalities
TEXT
Output Modalities outputModalities
TEXT
Features Supported featuresSupported
Count Tokens countTokens
Prompt Caching promptCaching
Batch Inference batchInference
In Region inRegion
Cross Region crossRegion
Prompt Optimization promptOptimization
Provisioned Throughput provisionedThroughput
Intelligent Prompt Routing intelligentPromptRouting
Console IDEMetadata consoleIDEMetadata

null

Guardrails Supported guardrailsSupported
Explicit Prompt Caching explicitPromptCaching
Is Supported isSupported
Inference APIs Supported inferenceAPIsSupported
Converse converse
Sync sync
Streaming streaming
Async Invoke asyncInvoke
Invoke Model invokeModel
Sync sync
Response Streaming responseStreaming
Bidirectional Streaming bidirectionalStreaming
Open AI Responses openAiResponses
Open AI Chat Completions openAiChatCompletions
Customizations Supported customizationsSupported
Inference Types Supported inferenceTypesSupported
INFERENCE_PROFILE
Intelligent Prompt Routing intelligentPromptRouting
Is Supported isSupported
Response Streaming Supported responseStreamingSupported
Latency Optimization Supported latencyOptimizationSupported

null

Availability

Not enough data yet

We have not collected enough health probes for this model to publish an uptime or latency figure. A percentage from a handful of samples is fabricated precision, so none is shown until the sample count supports one.

How Llama 3.1 8B Instruct is billed

Billed at the provider's list price, with no per-token markup.

Exact list price
Tokens settle at the published rate of the model that served your call.
Cache discounts passed through
Provider prompt-caching discounts reach your balance with no added fee.
Cost on every response
Each response carries the x-nr-request-cost header, so you can reconcile spend per request.

More from Meta

muse-spark-1.1muse-spark-1.3-contributorNousResearch/Hermes-3-Llama-3.1-70Bmeta-models/Muse-Glimmer-30B

Start building with llama3-1-8b-instruct

One API key, three steps. Choose your tool to begin.

  1. Get a key

    Create API key

  2. Set your API key

    export NROUTER_API_KEY="<YOUR_API_KEY>"

  3. Configure Claude Code

    Choose a tool, then copy its setup from the panel.

npm install -g @anthropic-ai/claude-code
Claude Code · bedrock/us.meta.llama3-1-8b-instruct-v1:0
# Point Claude Code to nRouter gateway
export ANTHROPIC_BASE_URL="https://api.nrouter.ai"
export ANTHROPIC_API_KEY="$NROUTER_API_KEY"

# Launch with bedrock/us.meta.llama3-1-8b-instruct-v1:0
claude --model bedrock/us.meta.llama3-1-8b-instruct-v1:0

FAQs

What is Llama 3.1 8B Instruct?

Meta language model featuring a 128,000-token context window. Engineered for dialogue, instruction following, and versatile text generation.

How much does Llama 3.1 8B Instruct cost?

Llama 3.1 8B Instruct is billed at the provider's list price on nRouter with no per-token markup — tokens settle at the exact upstream rate. Input and output rates are read live, so see the pricing section above for the current figures.

Does Llama 3.1 8B Instruct support tool calling and structured outputs?

Yes. Llama 3.1 8B Instruct supports tool calling (function calling), so it can invoke external tools and APIs during a conversation.

What inputs and outputs does Llama 3.1 8B Instruct support?

Llama 3.1 8B Instruct takes text and images as input and returns text as output.

How do I use Llama 3.1 8B Instruct via nRouter?

Use any OpenAI-compatible client: point it at https://api.nrouter.ai/v1 with your nRouter API key and set the model to "bedrock/us.meta.llama3-1-8b-instruct-v1:0". The quick-start panel above has a copy-paste curl command for this model.

When was Llama 3.1 8B Instruct released?

Llama 3.1 8B Instruct was released on August 30, 2026.

Where is the Llama 3.1 8B Instruct documentation?

Start at nrouter.ai/docs. The quick-start guide (nrouter.ai/docs/getting-started/quick-start) covers API keys and your first request, and the API reference (nrouter.ai/docs/api-reference) lists every parameter.

What other text models does Meta have?

Other Meta text models on nRouter include Muse Spark 1.1 (nrouter.ai/models/muse-spark-1.1), Muse Spark 1.3 Contributor (nrouter.ai/models/muse-spark-1.3-contributor), Hermes 3 Llama 3.1 70B (nrouter.ai/models/nousresearch-hermes-3-llama-3.1-70b), Muse Glimmer 30B (nrouter.ai/models/meta-models-muse-glimmer-30b).