Meta: Llama 3.3 70B Instruct

Text input Text output Free Option
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...

Key Specifications
Cost
$
Context
131K
Parameters
70B
Released
Dec 06, 2024
Speed
Ability
Reliability
Supported Parameters

This model supports the following parameters:

Seed Tools Frequency Penalty Top P Min P Response Format Temperature Stop Presence Penalty Tool Choice Max Tokens
Features

This model supports the following features:

Response Format Tools
Performance Summary

The Meta Llama 3.3 70B Instruct model, released on December 6, 2024, demonstrates a strong overall performance profile, particularly excelling in cost-efficiency and reliability. It consistently offers among the most competitive pricing, ranking in the 85th percentile across benchmarks, and exhibits high reliability with a 92% success rate. While its speed performance is generally in the top tier (61st percentile), specific benchmark durations vary. The model shows exceptional accuracy in Instruction Following, achieving perfect scores in one instance and being noted as the most accurate among models of comparable speed. It also performs perfectly in Email Classification, standing out as the most accurate at its price point and speed. Hallucination rates are low at 96% accuracy, indicating a good ability to acknowledge uncertainty. General Knowledge and Ethics benchmarks also show strong performance, with 98% and 99% accuracy respectively. However, the model exhibits notable weaknesses in more complex cognitive tasks. Its Mathematics accuracy is 64% (24th percentile), and Reasoning is 58% (36th percentile). Coding performance is a significant area for improvement, with only 37% accuracy (17th percentile). This suggests the model is highly effective for dialogue, classification, and instruction-following tasks, but less proficient in advanced mathematical, logical, and programming challenges.

Model Pricing

Current Pricing

Feature Price (per 1M tokens)
Prompt $0.1
Completion $0.32

Price History

Available Endpoints
Provider Endpoint Name Context Length Pricing (Input) Pricing (Output)
DeepInfra
DeepInfra | meta-llama/llama-3.3-70b-instruct 131K $0.1 / 1M tokens $0.32 / 1M tokens
Kluster
Kluster | meta-llama/llama-3.3-70b-instruct 131K $0.1 / 1M tokens $0.32 / 1M tokens
Lambda
Lambda | meta-llama/llama-3.3-70b-instruct 131K $0.1 / 1M tokens $0.32 / 1M tokens
Phala
Phala | meta-llama/llama-3.3-70b-instruct 131K $0.1 / 1M tokens $0.32 / 1M tokens
Novita
Novita | meta-llama/llama-3.3-70b-instruct 131K $0.135 / 1M tokens $0.4 / 1M tokens
Crusoe
Crusoe | meta-llama/llama-3.3-70b-instruct 131K $0.25 / 1M tokens $0.75 / 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 $0.1 / 1M tokens $0.32 / 1M tokens
Parasail
Parasail | meta-llama/llama-3.3-70b-instruct 131K $0.1 / 1M tokens $0.32 / 1M tokens
NextBit
NextBit | meta-llama/llama-3.3-70b-instruct 32K $0.1 / 1M tokens $0.32 / 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 $0.1 / 1M tokens $0.32 / 1M tokens
InoCloud
InoCloud | meta-llama/llama-3.3-70b-instruct 131K $0.1 / 1M tokens $0.32 / 1M tokens
Hyperbolic
Hyperbolic | meta-llama/llama-3.3-70b-instruct 131K $0.1 / 1M tokens $0.32 / 1M tokens
Atoma
Atoma | meta-llama/llama-3.3-70b-instruct 104K $0.1 / 1M tokens $0.32 / 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 $0.1 / 1M tokens $0.32 / 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 $0.1 / 1M tokens $0.32 / 1M tokens
InferenceNet
InferenceNet | meta-llama/llama-3.3-70b-instruct 128K $0.1 / 1M tokens $0.32 / 1M tokens
Crusoe
Crusoe | meta-llama/llama-3.3-70b-instruct 131K $0.1 / 1M tokens $0.32 / 1M tokens
GMICloud
GMICloud | meta-llama/llama-3.3-70b-instruct 131K $0.1 / 1M tokens $0.32 / 1M tokens
WandB
WandB | meta-llama/llama-3.3-70b-instruct 128K $0.71 / 1M tokens $0.71 / 1M tokens
SambaNova
SambaNova | meta-llama/llama-3.3-70b-instruct 16K $0.45 / 1M tokens $0.9 / 1M tokens
Nebius
Nebius | meta-llama/llama-3.3-70b-instruct 131K $0.25 / 1M tokens $0.75 / 1M tokens
Parasail
Parasail | meta-llama/llama-3.3-70b-instruct 131K $0.22 / 1M tokens $0.5 / 1M tokens
Inceptron
Inceptron | meta-llama/llama-3.3-70b-instruct 131K $0.12 / 1M tokens $0.38 / 1M tokens
Akash
Akash | meta-llama/llama-3.3-70b-instruct 131K $0.1 / 1M tokens $0.32 / 1M tokens
AkashML
AkashML | meta-llama/llama-3.3-70b-instruct 131K $0.1 / 1M tokens $0.32 / 1M tokens
AkashML
AkashML | meta-llama/llama-3.3-70b-instruct 131K $0.13 / 1M tokens $0.4 / 1M tokens
Hyperbolic
Hyperbolic | meta-llama/llama-3.3-70b-instruct 131K $0.1 / 1M tokens $0.32 / 1M tokens
Benchmark Results
Benchmark Category Reasoning Strategy Free Executions Accuracy Cost Duration
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