Sulat.com
AI models
$10 off the fastest DeepSeek V4.1 Flash, Kimi K3 and GLM 5.3 from Synthetic
NovitaAI logo

Model details

Llama 3.1 8B Instruct

Llama 3.1 8B Instruct is part of Meta's Llama family of open language models, released as an instruction-tuned variant designed for conversational assistants, multilingual text generation, and agentic workflows that chain model calls into broader automation pipelines. The official Hugging Face repository distributes the weights under the Llama 3.1 Community License Agreement, with the license version release date recorded as July 23, 2024, confirming Meta's authorship and the intended open redistribution model for developers building on top of the base architecture.

Positioned as a compact 8-billion-parameter option in the Llama 3.1 lineup, this Instruct-tuned release is aimed at practical deployment scenarios where a balance between responsiveness and capability matters more than flagship-scale reasoning. Meta's framing emphasizes versatility across chat, multilingual text generation, and integration into agent-style systems, making it a sensible fit for teams that need a permissive, instruction-following model to power assistants, retrieval-augmented tools, and lightweight production services on commodity hardware.

NovitaAImeta-llama/llama-3.1-8b-instructllama

Quick Info

Powered by
Provider
NovitaAI
Model key
meta-llama/llama-3.1-8b-instruct
Release date
Jul 24, 2024
Last updated
Jul 24, 2024
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.02
Output token cost
$0.05

Limits

Output tokens
16,384 tokens
Context window
16,384 tokens

Transparent token rates

Compare Llama 3.1 8B Instruct pricing

Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

Browse this family

Latest news about Llama 3.1 8B Instruct

Pioneer

CoverageBenchmark

The benchmarklist.com page for Llama 3.1 8B Instruct surfaces an AgentCollabBench evaluation that explicitly tested this Meta variant alongside GPT 4.1 mini, Gemini 2.5 Flash Lite, and Qwen-3.5-35B-A3B across 900 multi-agent tasks designed to expose silent process failures such as instruction decay, false-belief contag The same page lists standard reference pricing ($0.02/$0.03 per 1M tokens) and comparator list pricing, but its most actionable content for developers is the AgentCollabBench finding: using Llama 3.1 8B Instruct as one node in a multi-agent topology can silently drop constraints carried by minority branches at synthesi

Pioneer

CoverageBenchmark

The llm-stats benchmark page for Llama 3.1 8B Instruct compiles tracked evaluation scores sourced from the model's Hugging Face scorecard, positioning the variant at overall rank 339 and providing concrete numbers including GSM-8K (chain-of-thought) at 0.84, ARC-Challenge at 0.83, API-Bank tool-use at 0.83, and IFEval The page is explicitly marked as a third-party composite aggregating publicly available scores rather than an independent re-run, with some methodology entries listed as unspecified, so the numbers are best used as a reference baseline rather than as definitive eval results. For a developer evaluating Llama 3.1 8B Inst

Videos about Llama 3.1 8B Instruct

More models around Llama 3.1 8B Instruct