# Llama 3.1 8B Instruct ![Organization](https://img.shields.io/badge/Org-Meta-0064e0) ![Parameters](https://img.shields.io/badge/Params-8B-1f6feb) ![Context](https://img.shields.io/badge/Context-128K%20tokens-1f6feb) ![License](https://img.shields.io/badge/License-Apache%202.0-2da44e) ![Weights](https://img.shields.io/badge/Weights-Open-2da44e) ![Released](https://img.shields.io/badge/Released-Jul%202024-555) > **Quick answer:** Llama 3.1 8B Instruct is Meta's July 2024 small instruction-tuned open-weight model, scoring 84.5% on GSM8K, 73.0% on MMLU, and 48.3% on MMLU-Pro. With a 128K context window under Apache 2.0, it is the most widely deployed open 8B model — a common first choice for low-cost server-side inference. ## At a Glance **Where Llama 3.1 8B leads** - Apache 2.0 — fully permissive commercial use - 84.5% GSM8K — strong math for an 8B model - 128K context window - Extremely cost-efficient inference at 8B scale - Most widely deployed open 8B model — extensive ecosystem support - Strong fine-tuning base (numerous Llama 3.1 8B derivatives) **Where it lags** - 48.3% MMLU-Pro — below 14B+ models on academic knowledge - Text-only: no vision support - Superseded by Llama 3.2 11B (adds vision) and later models - March 2024 knowledge cutoff **Best for:** Cost-optimised server inference; batch processing; fine-tuning foundation; first open-weight model for new deployments that later scale to 70B. ## What Llama 3.1 8B Instruct Is Llama 3.1 8B Instruct (released July 23, 2024) is the smallest instruction-tuned model in Meta's Llama 3.1 family, designed for efficient server-side deployment. At Apache 2.0, it is the most permissively licensed model in the Llama 3.1 family (the 70B and 405B use the more restrictive Llama 3.1 License). Its 84.5% GSM8K score is impressive at 8B — reflecting Meta's training improvements in Llama 3.1. Combined with a 128K context window, it handles long documents at a fraction of the cost of larger models. The model became the reference 8B open-weight model throughout 2024, with extensive ecosystem support across all major inference frameworks (vLLM, Ollama, llama.cpp, etc.) and served as the base for many fine-tuned derivatives. ## Specifications | Field | Value | |---|---| | Organization | Meta | | Parameters | 8B (dense) | | Context window | 128,000 tokens | | License | Apache 2.0 | | HuggingFace | [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) | | Release date | July 23, 2024 | | Knowledge cutoff | March 2024 | | Modality | Text only | ## Pricing Llama 3.1 8B Instruct is available as open weights under Apache 2.0 — free for self-hosting and commercial use without restrictions. The most cost-efficient option across hosted providers due to its small size. ## Context Window Llama 3.1 8B Instruct supports a **128,000-token context window** — approximately **90 pages** of text. ## Public Benchmark Scores | Benchmark | Score | Source | Date | |---|---|---|---| | [GSM8K](/benchmarks/gsm8k) | 84.5% | Benchgen evaluation | 2025-07 | | [MMLU](/benchmarks/mmlu) | 73.0% | Benchgen evaluation | 2025-07 | | [MMLU-Pro](/benchmarks/mmlu-pro) | 48.3% | Benchgen evaluation | 2025-07 | ## Llama 3.1 8B vs Alternatives | Model | GSM8K | MMLU | MMLU-Pro | License | |---|---|---|---|---| | **Llama 3.1 8B Instruct** | 84.5% | 73.0% | 48.3% | Apache 2.0 | | [Llama 3.2 3B Instruct](/models/meta/llama-3-2-3b-instruct) | 77.7% | — | — | Llama 3.2 | | [Llama 3.1 70B Instruct](/models/meta/llama-3-1-70b-instruct) | — | 86.0% | — | Llama 3.1 | | [Phi-4](/models/microsoft/phi-4) | — | — | 70.4% | Apache 2.0 | Llama 3.1 8B vs Phi-4: Phi-4 (14B) achieves 70.4% MMLU-Pro vs 8B's 48.3% at ~2× the parameters — better knowledge, but significantly higher inference cost. For maximum quality per token at 8B scale, Llama 3.1 8B is the standard. ## Related Models & Benchmarks - Compare: [Llama 3.2 3B Instruct](/models/meta/llama-3-2-3b-instruct) · [Llama 3.1 70B Instruct](/models/meta/llama-3-1-70b-instruct) · [Phi-4](/models/microsoft/phi-4) - Benchmarks: [GSM8K](/benchmarks/gsm8k) · [MMLU](/benchmarks/mmlu) · [MMLU-Pro](/benchmarks/mmlu-pro) ## Frequently Asked Questions

What is Llama 3.1 8B Instruct?

Llama 3.1 8B Instruct is Meta's July 2024 open-weight 8B model scoring 84.5% GSM8K, 73.0% MMLU, and 48.3% MMLU-Pro with 128K context under Apache 2.0.

Is Llama 3.1 8B open source?

Yes — the 8B variant is under Apache 2.0, the most permissive license in the Llama 3.1 family. Free for commercial use without restrictions.

What is the context window of Llama 3.1 8B?

Llama 3.1 8B Instruct supports a 128,000-token context window.

--- *Specs from Meta's official Llama 3.1 announcement (July 2024) and Benchgen evaluations. Last updated 2026-07-24.*

Llama 3.1 8B Instruct — Files