Meta: Llama 3.1 8B Instruct

Text input Text output
Author's Description

Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance compared to leading closed-source models in human evaluations. To read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3-1/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).

Key Specifications
Cost
$
Context
131K
Parameters
8B
Released
Jul 22, 2024
Speed
Ability
Reliability
Supported Parameters

This model supports the following parameters:

Top Logprobs Logit Bias Logprobs Stop Seed Min P Top P Max Tokens Frequency Penalty Temperature Presence Penalty
Performance Summary

Meta's Llama 3.1 8B Instruct model, released on July 22, 2024, demonstrates a strong overall profile, particularly excelling in cost-efficiency and reliability. It consistently offers among the most competitive pricing, ranking in the 97th percentile across six benchmarks. The model also exhibits high reliability with a 92% success rate, indicating consistent and usable responses. In terms of speed, it performs competitively, ranking in the 59th percentile. Across benchmark categories, Llama 3.1 8B Instruct shows notable strengths in cost-effectiveness for specific tasks, being the most accurate model at its price point for General Knowledge and Email Classification. It achieves a high 98.5% accuracy in Ethics, showcasing strong moral reasoning capabilities. However, the model exhibits weaknesses in complex Reasoning and Instruction Following, with accuracy scores of 18.0% and 32.2% respectively. Its performance in General Knowledge and Coding is moderate, with accuracy around the 30th percentile. The model's 131,000 context length supports extensive interactions.

Model Pricing

Current Pricing

Feature Price (per 1M tokens)
Prompt $0.02
Completion $0.03

Price History

Available Endpoints
Provider Endpoint Name Context Length Pricing (Input) Pricing (Output)
Kluster
Kluster | meta-llama/llama-3.1-8b-instruct 131K $0.02 / 1M tokens $0.03 / 1M tokens
DeepInfra
DeepInfra | meta-llama/llama-3.1-8b-instruct 131K $0.02 / 1M tokens $0.03 / 1M tokens
InferenceNet
InferenceNet | meta-llama/llama-3.1-8b-instruct 16K $0.02 / 1M tokens $0.03 / 1M tokens
Novita
Novita | meta-llama/llama-3.1-8b-instruct 16K $0.02 / 1M tokens $0.05 / 1M tokens
Nebius
Nebius | meta-llama/llama-3.1-8b-instruct 131K $0.02 / 1M tokens $0.06 / 1M tokens
Lambda
Lambda | meta-llama/llama-3.1-8b-instruct 131K $0.02 / 1M tokens $0.03 / 1M tokens
DeepInfra
DeepInfra | meta-llama/llama-3.1-8b-instruct 131K $0.03 / 1M tokens $0.05 / 1M tokens
Cloudflare
Cloudflare | meta-llama/llama-3.1-8b-instruct 32K $0.15 / 1M tokens $0.29 / 1M tokens
Groq
Groq | meta-llama/llama-3.1-8b-instruct 131K $0.05 / 1M tokens $0.08 / 1M tokens
Hyperbolic
Hyperbolic | meta-llama/llama-3.1-8b-instruct 131K $0.1 / 1M tokens $0.1 / 1M tokens
Cerebras
Cerebras | meta-llama/llama-3.1-8b-instruct 32K $0.1 / 1M tokens $0.1 / 1M tokens
Friendli
Friendli | meta-llama/llama-3.1-8b-instruct 131K $0.1 / 1M tokens $0.1 / 1M tokens
SambaNova
SambaNova | meta-llama/llama-3.1-8b-instruct 16K $0.1 / 1M tokens $0.2 / 1M tokens
Together
Together | meta-llama/llama-3.1-8b-instruct 131K $0.18 / 1M tokens $0.18 / 1M tokens
Fireworks
Fireworks | meta-llama/llama-3.1-8b-instruct 131K $0.2 / 1M tokens $0.2 / 1M tokens
Avian
Avian | meta-llama/llama-3.1-8b-instruct 131K $0.02 / 1M tokens $0.03 / 1M tokens
SiliconFlow
SiliconFlow | meta-llama/llama-3.1-8b-instruct 32K $0.06 / 1M tokens $0.06 / 1M tokens
Benchmark Results
Benchmark Category Reasoning Strategy Free Executions Accuracy Cost Duration
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