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Llama API
Download models

Meet Llama 3.1

The open source AI model you can fine-tune, distill and deploy anywhere. Our latest instruction-tuned model is available in 8B, 70B and 405B versions.
Start building
Download models
Try 405B on Meta AI

Llama 3.1 models

Documentation Hub

405B

Flagship foundation model driving widest variety of use cases.
Download

70B

Highly performant, cost effective model that enables diverse use cases.
Download

8B

Light-weight, ultra-fast model you can run anywhere.
Download

Key capabilities

Start building more advanced use cases, leveraging our resources.
Get started with Llama Recipes
Start developing with Llama Agents
Tool use
Upload a dataset and analyze it. Prompt model to plot graphs and fetch market data.
Get Started in GitHub
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Multi-lingual agents
Prompt: Translate the story of Hansel and Gretel into Spanish.
Try 405B on Meta AI
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Complex reasoning
Prompt: I have 3 shirts and 5 shorts, and 1 sun dress. I'm traveling for 10 days do I have enough for my vacation?
Try 405B on Meta AI
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Coding assistants
Prompt: Create a program that generates a perfect maze, using a recursive backtracking algorithm or a depth-first search algorithm, with customizable size and complexity.
Try 405B on Meta AI
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Make Llama your own

Using our open ecosystem, build faster with a selection of differentiated product offerings to support your use cases.
See all services
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Inference

Choose from real-time inference or batch inference services. Download model weights to further optimize cost per token.
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Fine-tune, Distill & Deploy

Adapt for your application, improve with synthetic data and deploy on-prem or in the cloud.
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RAG & Tool Use

Use Llama system components and extend the model using zero shot tool use and RAG to build agentic behaviors.
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Synthetic Data Generation

Leverage 405B high quality data to improve specialized models for specific use cases.

Quick start with partners

Partner starter guides
Features for
405B models
Real-time inference
Batch inference
Fine-tuning
Model evaluation
RAG
Continual pre-training
Safety guardrails
Synthetic data generation
Distillation recipe
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Model evaluations

As measured on over 150 benchmark datasets that span a wide range of languages and extensive human evaluations.

Model card
Research paper

Instruction-tuned benchmarks

Llama 3.1 Performance
Benchmarks
Category
Benchmark

General

MMLU

(CoT)

MMLU PRO

(5-shot, CoT)

IFEval

Code

HumanEval

(0-shot)

MBPP EvalPlus

(base) (0-shot)

Math

GSM8K

(8-shot, CoT)

MATH

(0-shot, CoT)

Reasoning

ARC Challenge

(0-shot)

GPQA

(0-shot, CoT)

Tool use

API-Bank

(0-shot)

BFCL

Gorilla Benchmark API Bench

Nexus

(0-shot)

Multilingual

Multilingual MGSM

Llama 3.1
8B

73.0

48.3

80.4

72.6

72.8

84.5

51.9

83.4

32.8

82.6

76.1

8.2

38.5

68.9

Llama 3
8B - April

65.3

45.5

76.8

60.4

70.6

80.6

29.1

82.4

34.6

48.3

60.3

1.7

18.1

-

Llama 3.1
70B

86.0

66.4

87.5

80.5

86.0

95.1

68.0

94.8

46.7

90.0

84.8

29.7

56.7

86.9

Llama 3
70B - April

80.9

63.4

82.9

81.7

82.5

93.0

51.0

94.4

39.5

85.1

83.0

14.7

47.8

-

Llama 3.1
405B

88.6

73.3

88.6

89.0

88.6

96.8

73.8

96.9

51.1

92.3

88.5

35.3

58.7

91.6

Lightweight
Benchmarks
Category
Benchmark

General

MMLU
(5-shot)
Open-rewrite eval
(0-shot, rougeL)
TLDR9+
(test, 1-shot, rougeL)

IFEval

Math

GSM8K
(0-shot, CoT)
MATH
(0-shot, CoT)

Reasoning

ARC Challenge
(0-shot)
GPQA
(0-shot)
Hellaswag
(0-shot)

Tool use

BFCL V2
Nexus

Long context

InfiniteBench/En.MC
(128k)
InfiniteBench/En.QA
(128k)
NIH/Multi-needle

Multilingual

MGSM
(0-shot, CoT)

Llama 3.2 1B

49.3

41.6

16.8

59.5

44.4

30.6

59.4

27.2

41.2

25.7

13.5

38.0

20.3

75.0

24.5

Llama 3.2 3B

63.4

40.1

19.0

77.4

77.7

48.0

78.6

32.8

69.8

67.0

34.3

63.3

19.8

84.7

58.2

Gemma 2 2B IT(5-shot)

57.8

31.2

13.9

61.9

62.5

23.8

76.7

27.5

61.1

27.4

21.0

-

-

-

40.2

Phi-3.5 - Mini IT(5-shot)

69.0

34.5

12.8

59.2

86.2

44.2

87.4

31.9

81.4

58.4

26.1

39.2

11.3

52.7

49.8

Details of our evals can be found here along with the raw data generated as part of our evals.

Model Pricing

Hosted Llama 3.1 inference API public pricing per million tokens as of 12pm PST on 9/5/24. This table will be updated as more pricing becomes available.
Model
AWS
Azure
Databricks
Fireworks.ai
IBM
Octo.ai
Snowflake
Together.AI

8B

70B

405B

Input

$0.22

$0.30

-

$0.20

$0.60

$0.15

$0.57

$0.18

Output

$0.22

$0.61

-

$0.20

$0.60

$0.15

$0.57

$0.18

Input

$0.99

$2.68

$1.00

$0.90

$1.80

$0.90

$3.63

$0.88

Output

$0.99

$3.54

$3.00

$0.90

$1.80

$0.90

$3.63

$0.88

Input

$5.32

$5.33

$5.00

$3.00

$5.00

$3.00

$9.00

$5.00

Output

$16.00

$16.00

$15.00

$3.00

$16.00

$9.00

$9.00

$15.00

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