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Meta: Llama 3.1 8B Instruct

🇺🇸 Meta · Llama 3.1

Input Price $0.020 per million tokens NT$0.64
Output Price $0.030 per million tokens NT$0.96
Context Window 131K tokens Output limit: 16K
OpenRouter Route Price Please verify with official pricing pages
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Overview

Meta: Llama 3.1 8B Instruct is a large language model API from Meta, part of its Llama 3.1 model family. At $0.020 per million input tokens and $0.030 per million output tokens, it sits in the budget tier — among the cheaper options for high-throughput or cost-sensitive workloads. Output tokens cost about 2× as much as input, so prompt-heavy workloads run noticeably cheaper than generation-heavy ones. The 131K-token context window — around 197 pages of text — comfortably handles long documents, multi-file code, or extended conversations. On Artificial Analysis's Intelligence Index it scores 8 (F grade), a useful proxy for its general reasoning strength relative to the other models tracked here. All prices on this page reflect OpenRouter's routed rates and are re-synced automatically every day; confirm against the provider's official pricing before committing to production.

Dimension Unit Price (USD) Price (TWD) Effective From
Input per 1M tokens $0.020 NT$0.64
Output per 1M tokens $0.030 NT$0.96

Provider
Meta
Model Family
Llama 3.1
Version String
meta-llama/llama-3.1-8b-instruct
Status
Active
Modality
Text
Context Window
131,072 tokens
Output Limit
16,384 tokens

Index Metrics

Cross-domain capability indexes evaluated by Artificial Analysis — Artificial Analysis

Agentic Index 1 F Measured: 2026-07-01
Coding Index 5 F Measured: 2026-07-01
Intelligence Index 8 F Measured: 2026-07-01

Benchmark Scores

Data source: Artificial Analysis

AA-LCR 15.7% F Measured: 2026-07-01
GPQA Diamond 25.9% F Measured: 2026-07-01
HLE 5.1% D Measured: 2026-07-01
IFBench 28.6% F Measured: 2026-07-01
Non-Hallucination 58.2% Measured: 2026-07-01
Omniscience Accuracy 8.1% Measured: 2026-07-01
SciCode 13.2% D Measured: 2026-07-01
Tau2 16.4% Measured: 2026-07-01
TerminalBench 0.8% Measured: 2026-07-01

Performance Metrics

Real-world benchmarks, updated every 72 hours by Artificial Analysis — Artificial Analysis

First Token Latency 0.9s Measured: 2026-07-01
Output Speed 142 t/s Measured: 2026-07-01
Response Time 4.4s Measured: 2026-07-01

Use Case Analysis

Model strengths, weaknesses, and ideal use cases based on benchmarks and official documentation

Strength

  • Exceptional Efficiency MMLU (CoT) 73.0%, GSM8K 84.5%. Best-in-class for 8B parameter models. Benchmark
  • Runs on Consumer Hardware Fits on single RTX 4090 (24GB VRAM) or even smaller GPUs with quantization. Official

Best For

  • Personal/Small Business AI Can run locally on personal computers; no cloud dependency or API costs. Official
  • Fine-tuning Base Model Excellent starting point for domain-specific fine-tuning with limited compute. Official

Not Recommended

  • Complex Reasoning Tasks Use 70B or 405B for multi-step logic, advanced math, or scientific reasoning. Official

90-Day Price Trend

Input / Output price (USD per 1M tokens)

Past 90 days of records; every price change is shown here

Date Dimension Price (USD) Source
Output $0.030 OpenRouter
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Key Insights

Key data points from this page for quick reference and citation.

  • Meta: Llama 3.1 8B Instruct Input price: $0.02/M tokens
  • Meta: Llama 3.1 8B Instruct Output price: $0.03/M tokens
  • Context window: 131,072 tokens
  • Provider: Meta
  • Model family: Llama 3.1
  • Modalities: Text
  • Data source: OpenRouter, updated daily