Author's Description
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model is optimized for multilingual dialogue use cases and outperforms many of the available open source and closed chat models on common industry benchmarks. Supported languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai. [Model Card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_3/MODEL_CARD.md)
Key Specifications
Supported Parameters
This model supports the following parameters:
Features
This model supports the following features:
Performance Summary
Meta's Llama 3.3 70B Instruct, released December 6, 2024, demonstrates a strong overall performance profile, particularly excelling in cost-efficiency and reliability. The model consistently offers competitive pricing, ranking in the 84th percentile across benchmarks, making it a cost-effective choice. Its reliability is also a significant strength, with a 92% success rate indicating consistent and usable responses. In terms of speed, the model shows competitive response times, placing in the 58th percentile. Analyzing benchmark results, Llama 3.3 70B Instruct exhibits perfect accuracy in Instruction Following (one instance) and Email Classification, often achieving these results with impressive speed and cost-efficiency. It also performs well in Hallucinations (96.0% accuracy) and Ethics (99.0% accuracy), suggesting a robust understanding of ethical principles and an ability to acknowledge uncertainty. General Knowledge is strong at 98.0% accuracy. However, the model shows notable weaknesses in more complex domains such as Mathematics (64.0% accuracy, 30th percentile) and Coding (37.0% accuracy, 20th percentile), indicating areas for potential improvement in advanced problem-solving and programming tasks. Reasoning also presents a moderate challenge at 58.0% accuracy. Its multilingual support for English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai further enhances its utility for diverse applications.
Model Pricing
Current Pricing
Feature | Price (per 1M tokens) |
---|---|
Prompt | $0.13 |
Completion | $0.39 |
Price History
Available Endpoints
Provider | Endpoint Name | Context Length | Pricing (Input) | Pricing (Output) |
---|---|---|---|---|
DeepInfra
|
DeepInfra | meta-llama/llama-3.3-70b-instruct | 131K | $0.13 / 1M tokens | $0.39 / 1M tokens |
Kluster
|
Kluster | meta-llama/llama-3.3-70b-instruct | 131K | $0.04 / 1M tokens | $0.12 / 1M tokens |
Lambda
|
Lambda | meta-llama/llama-3.3-70b-instruct | 131K | $0.04 / 1M tokens | $0.12 / 1M tokens |
Phala
|
Phala | meta-llama/llama-3.3-70b-instruct | 131K | $0.04 / 1M tokens | $0.12 / 1M tokens |
Novita
|
Novita | meta-llama/llama-3.3-70b-instruct | 131K | $0.13 / 1M tokens | $0.39 / 1M tokens |
Crusoe
|
Crusoe | meta-llama/llama-3.3-70b-instruct | 131K | $0.04 / 1M tokens | $0.12 / 1M tokens |
Nebius
|
Nebius | meta-llama/llama-3.3-70b-instruct | 131K | $0.13 / 1M tokens | $0.4 / 1M tokens |
DeepInfra
|
DeepInfra | meta-llama/llama-3.3-70b-instruct | 131K | $0.23 / 1M tokens | $0.4 / 1M tokens |
Parasail
|
Parasail | meta-llama/llama-3.3-70b-instruct | 131K | $0.15 / 1M tokens | $0.5 / 1M tokens |
NextBit
|
NextBit | meta-llama/llama-3.3-70b-instruct | 32K | $0.04 / 1M tokens | $0.12 / 1M tokens |
Cloudflare
|
Cloudflare | meta-llama/llama-3.3-70b-instruct | 24K | $0.29 / 1M tokens | $2.25 / 1M tokens |
Cent-ML
|
Cent-ML | meta-llama/llama-3.3-70b-instruct | 131K | $0.04 / 1M tokens | $0.12 / 1M tokens |
InoCloud
|
InoCloud | meta-llama/llama-3.3-70b-instruct | 131K | $0.04 / 1M tokens | $0.12 / 1M tokens |
Hyperbolic
|
Hyperbolic | meta-llama/llama-3.3-70b-instruct | 131K | $0.4 / 1M tokens | $0.4 / 1M tokens |
Atoma
|
Atoma | meta-llama/llama-3.3-70b-instruct | 104K | $0.04 / 1M tokens | $0.12 / 1M tokens |
Groq
|
Groq | meta-llama/llama-3.3-70b-instruct | 131K | $0.59 / 1M tokens | $0.79 / 1M tokens |
Friendli
|
Friendli | meta-llama/llama-3.3-70b-instruct | 131K | $0.6 / 1M tokens | $0.6 / 1M tokens |
SambaNova
|
SambaNova | meta-llama/llama-3.3-70b-instruct | 131K | $0.6 / 1M tokens | $1.2 / 1M tokens |
Google
|
Google | meta-llama/llama-3.3-70b-instruct | 128K | $0.72 / 1M tokens | $0.72 / 1M tokens |
Cerebras
|
Cerebras | meta-llama/llama-3.3-70b-instruct | 131K | $0.85 / 1M tokens | $1.2 / 1M tokens |
Together
|
Together | meta-llama/llama-3.3-70b-instruct | 131K | $0.88 / 1M tokens | $0.88 / 1M tokens |
Fireworks
|
Fireworks | meta-llama/llama-3.3-70b-instruct | 131K | $0.9 / 1M tokens | $0.9 / 1M tokens |
InferenceNet
|
InferenceNet | meta-llama/llama-3.3-70b-instruct | 128K | $0.04 / 1M tokens | $0.12 / 1M tokens |
Crusoe
|
Crusoe | meta-llama/llama-3.3-70b-instruct | 131K | $0.04 / 1M tokens | $0.12 / 1M tokens |
GMICloud
|
GMICloud | meta-llama/llama-3.3-70b-instruct | 131K | $0.25 / 1M tokens | $0.75 / 1M tokens |
WandB
|
WandB | meta-llama/llama-3.3-70b-instruct | 128K | $0.04 / 1M tokens | $0.12 / 1M tokens |
SambaNova
|
SambaNova | meta-llama/llama-3.3-70b-instruct | 16K | $0.45 / 1M tokens | $0.9 / 1M tokens |
Benchmark Results
Benchmark | Category | Reasoning | Strategy | Free | Executions | Accuracy | Cost | Duration |
---|
Other Models by meta-llama
|
Released | Params | Context |
|
Speed | Ability | Cost |
---|---|---|---|---|---|---|---|
Meta: Llama Guard 4 12B | Apr 29, 2025 | 12B | 163K |
Text input
Image input
Text output
|
— | ★ | $$ |
Meta: Llama 4 Maverick | Apr 05, 2025 | 17B | 1M |
Text input
Image input
Text output
|
★★★★★ | ★★★ | $$$ |
Meta: Llama 4 Scout | Apr 05, 2025 | 17B | 327K |
Text input
Image input
Text output
|
★★★★ | ★★ | $$ |
Llama Guard 3 8B | Feb 12, 2025 | 8B | 131K |
Text input
Text output
|
★★ | ★ | $$ |
Meta: Llama 3.2 1B Instruct | Sep 24, 2024 | 1B | 131K |
Text input
Text output
|
★★ | ★ | $ |
Meta: Llama 3.2 3B Instruct | Sep 24, 2024 | 3B | 131K |
Text input
Text output
|
★★★ | ★ | $ |
Meta: Llama 3.2 11B Vision Instruct | Sep 24, 2024 | 11B | 128K |
Text input
Image input
Text output
|
★★ | ★★ | $$ |
Meta: Llama 3.2 90B Vision Instruct | Sep 24, 2024 | 90B | 131K |
Text input
Image input
Text output
|
★★★ | ★★ | $$$$ |
Meta: Llama 3.1 405B (base) | Aug 01, 2024 | 405B | 32K |
Text input
Text output
|
★ | ★ | $$$ |
Meta: Llama 3.1 70B Instruct | Jul 22, 2024 | 70B | 131K |
Text input
Text output
|
★★★★ | ★★ | $$ |
Meta: Llama 3.1 405B Instruct | Jul 22, 2024 | 405B | 32K |
Text input
Text output
|
★★★★ | ★★ | $$$ |
Meta: Llama 3.1 8B Instruct | Jul 22, 2024 | 8B | 131K |
Text input
Text output
|
★★★ | ★★ | $ |
Meta: LlamaGuard 2 8B | May 12, 2024 | 8B | 8K |
Text input
Text output
|
★★★★ | ★ | $$ |
Meta: Llama 3 8B Instruct | Apr 17, 2024 | 8B | 8K |
Text input
Text output
|
★★★ | ★★ | $ |
Meta: Llama 3 70B Instruct | Apr 17, 2024 | 70B | 8K |
Text input
Text output
|
★★★★ | ★★ | $$$ |
Meta: Llama 2 70B Chat Unavailable | Jun 19, 2023 | 70B | 4K |
Text input
Text output
|
— | — | $$$$ |