Llama 3.1 405B Instruct

Released
2024-07-23
Last refreshed
2026-10-12
Status
Researched 180d ago
Open weightsCommercial use: conditionalRAGLong contextClassificationJSON / Tool use
AI at Meta releases · 11 in the last 12 monthsChangelog →
Specifications
Family
Llama 3.1
Released
2024-07-23
Context
128K
Parameters
405B
Architecture
Decoder Only
Knowledge cutoff
2023-12
Specialization
general
Openness
Open weights
License
Llama 3 CommunityCommercial use: conditional
Weights
Available
Code
Unknown
Training
Fine-tuned
Created by

Large-scale open-source AI for social technologies.

Menlo Park, California, United States
Founded 2013
Website
Pricing
Output / 1M
$2.40
Input / 1M
$2.40

Cheapest of 7 routes · AWS Bedrock

About

Llama 3.1 405B Instruct is Meta's advanced large language model released on July 23, 2024, featuring 405 billion parameters. It utilizes an optimized transformer architecture with supervised fine-tuning and reinforcement learning for enhanced instruction-following capabilities. The model supports multiple languages, was trained on 15 trillion tokens, and fine-tuned with 25 million synthetic examples. It excels in multilingual dialogue and text generation, making it ideal for assistant-like applications. Llama 3.1 incorporates robust safety measures and ethical considerations, outperforming many existing models on various industry benchmarks.

Providers(7)

Compare all 7

Compare API pricing across 7 tracked provider routes for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
AWS Bedrock$2.40$2.40
Serverless
Fireworks AI$3.00$3.00
Serverless
Hyperbolic AI Inference$4.00$4.00
Serverless
IBM watsonx$3.00$9.00
Serverless
GCP Vertex AI$5.00$16.00
Serverless
Microsoft Foundry$5.33$16.00
Provisioned
Scale AI GenAI Platform--
ServerlessPartial

Deprecated provider routes(4)

ProviderStatusCatalog ID
OctoAI API (Deprecated)Deprecated—
Together AIDeprecated—
NVIDIA NIMDeprecated—
Databricks Foundation Model ServingDeprecated—

Available via routers & gateways(16)

Capabilities

Structured Outputs

Benchmark peer barsfor Classification

Benchmark scores(1)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionEvaluationSource
Massive Multitask Language Understanding88.65-shotObserved 2026-03-07—Source

Migration checks

No linked migration route is available for this model yet.

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