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...

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

This model supports the following parameters:

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

Meta's Llama 3.1 8B Instruct model, released on July 22, 2024, demonstrates a compelling balance of efficiency and performance. It performs among the fastest models, ranking in the 61st percentile for speed across six benchmarks. A significant competitive advantage is its consistently competitive pricing, placing it in the 95th percentile. The model also exhibits strong reliability, achieving a 92% success rate, indicating consistent and usable responses. In terms of specific benchmarks, Llama 3.1 8B Instruct shows notable strengths in cost-efficiency, often being the most accurate model at its price point for General Knowledge and Email Classification. It achieves high accuracy in Ethics (98.5%) and Email Classification (95.0%). However, its performance in General Knowledge (87.5%) and Coding (69.0%) is moderate, while Instruction Following (32.2%) and especially Reasoning (18.0%) represent significant weaknesses, ranking in the lower percentiles for accuracy. This suggests the model excels in tasks requiring factual recall and straightforward classification but struggles with complex, multi-step logical deduction and intricate instruction adherence.

Model Pricing

Current Pricing

Feature Price (per 1M tokens)
Prompt $0.02
Completion $0.05

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 $0.05 / 1M tokens
DeepInfra
DeepInfra | meta-llama/llama-3.1-8b-instruct 131K $0.02 / 1M tokens $0.05 / 1M tokens
InferenceNet
InferenceNet | meta-llama/llama-3.1-8b-instruct 16K $0.02 / 1M tokens $0.05 / 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 $0.05 / 1M tokens
DeepInfra
DeepInfra | meta-llama/llama-3.1-8b-instruct 131K $0.02 / 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 $0.02 / 1M tokens $0.05 / 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 $0.02 / 1M tokens $0.05 / 1M tokens
Fireworks
Fireworks | meta-llama/llama-3.1-8b-instruct 131K $0.02 / 1M tokens $0.05 / 1M tokens
Avian
Avian | meta-llama/llama-3.1-8b-instruct 131K $0.02 / 1M tokens $0.05 / 1M tokens
SiliconFlow
SiliconFlow | meta-llama/llama-3.1-8b-instruct 32K $0.02 / 1M tokens $0.05 / 1M tokens
Nebius
Nebius | meta-llama/llama-3.1-8b-instruct 131K $0.03 / 1M tokens $0.09 / 1M tokens
DeepInfra
DeepInfra | meta-llama/llama-3.1-8b-instruct 131K $0.02 / 1M tokens $0.05 / 1M tokens
Benchmark Results
Benchmark Category Reasoning Strategy Free Executions Accuracy Cost Duration
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