A dirt-cheap, fast open model for simple tasks — just don't expect frontier-level quality.
55
Coding
50
Writing
40
Research
0
Images
92
Value
15
Long Context
Use this when
High-volume, cost-sensitive applications where speed and price matter more than peak accuracy.
Skip this if
You need long-document processing, complex multi-step reasoning, or production-quality writing — the 8K context and model scale will be bottlenecks.
Pricing
$0.14/1M in
$0.14/1M out
↑250%since Jun 2026
Context
8k tokens
Speed
Very fast
As an open-weight model, Llama 3 8B can be self-hosted via platforms like Ollama, Replicate, or Together AI. The 8,192 token context window is a significant practical limitation. Pricing listed reflects hosted API inference; self-hosted costs vary.
Exceptionally low cost at $0.03/$0.04 per 1M tokens — one of the cheapest instruction models available
Fast inference speed suitable for real-time or high-throughput applications
Open-weight model enabling self-hosting and fine-tuning flexibility
Solid instruction-following for simple, well-defined tasks
Weaknesses
8K context window is severely limiting compared to competitors like Gemini 3.1 Pro (1M+) or GPT-5.4
Noticeably weaker on complex reasoning, multi-step logic, and nuanced writing versus larger models
Outclassed even by budget competitors like GPT-4o mini on harder tasks
Real-world use cases
What people actually use Llama 3 8B Instruct for.
Classifying or tagging large volumes of short customer support tickets
Generating boilerplate code snippets for simple CRUD operations
Summarizing short news articles or product descriptions in bulk
How Llama 3 8B Instruct compares
The nearest models people weigh against it, and what actually separates them.
vs Llama 3.1 8B Instruct — Against Llama 3.1 8B Instruct (Meta), Llama 3 8B Instruct costs about 54% more per token and gives up 2x on context. Llama 3.1 8B Instruct is the one to check first if the price difference matters more than the ceiling.
vs GPT-5.6 Luna — Against GPT-5.6 Luna (OpenAI), Llama 3 8B Instruct runs about 80% cheaper per token, gives up 128.2x on context and answers faster. Take Llama 3 8B Instruct unless you specifically need what GPT-5.6 Luna does better.
vs Llama 3 70B Instruct — Against Llama 3 70B Instruct (Meta), Llama 3 8B Instruct runs about 78% cheaper per token and answers faster. Take Llama 3 8B Instruct unless you specifically need what Llama 3 70B Instruct does better.
Price History
Llama 3 8B Instruct pricing over time
↑250% since Jun 1
90 data points · tracked daily since Jun 1, 2026
Ready to try it?
Start using Llama 3 8B Instruct
High-volume, cost-sensitive applications where speed and price matter more than peak accuracy.. Start free — no card required.
Llama 3.1 8B Instruct is Meta's smallest production-ready open-weight model, optimized for fast, low-cost inference on everyday language tasks. It delivers surprisingly capable instruction-following for its size, making it a go-to for high-volume, cost-sensitive deployments.
Verdict
The right tool for cheap, fast, high-volume tasks — not for anything that requires serious thinking.
Quality score
43%
Pricing
$0.05/1M in
$0.08/1M out
Speed
Very fast
5/5 speed
Context
16k tokens
Being open-weight, this model can be run locally or self-hosted via providers like Together AI, Fireworks, or Groq, often at even lower costs. The 16K context window is a meaningful limitation compared to other models in this price tier.
Open WeightBudgetFastSelf-HostableMeta
Best for
High-throughput applications where cost and speed matter more than frontier-level quality, such as chatbots, content classification, and text summarization.
Meta's Llama 3 70B Instruct is a 70-billion parameter open-weight language model fine-tuned for instruction following, representing Meta's most capable publicly available model at the time of release. It excels at general reasoning, coding assistance, and structured text tasks with strong multilingual support.
Verdict
A capable but now-outdated open-weight model undercut by its tiny context window and newer successors.
Quality score
53%
Pricing
$0.51/1M in
$0.74/1M out
Speed
Balanced
3/5 speed
Context
8k tokens
This is the original Llama 3 70B, not the 3.1 or 3.3 variants. Llama 3.1 70B offers a 128K context window at comparable pricing and is strongly preferred. Consider this model only if you have a specific reason to pin to the original Llama 3 checkpoint.
Open-weightInstruction-tunedMid-rangeMetaLlama 3
Best for
Developers and researchers who need a capable open-weight model for coding, analysis, and instruction-following tasks at a mid-range price point.
Llama 3 8B Instruct costs $0.14 per million input tokens and $0.14 per million output tokens on the API. A month of 10M input and 2M output tokens runs about $1.68 at list price, before any batch or caching discounts.
What is Llama 3 8B Instruct best for?
Llama 3 8B Instruct is best for high-volume, cost-sensitive applications where speed and price matter more than peak accuracy.. It is a strong fit when that workflow matters more than the tradeoffs around budget pricing and very fast speed.
When should I avoid Llama 3 8B Instruct?
You need long-document processing, complex multi-step reasoning, or production-quality writing — the 8K context and model scale will be bottlenecks.
What is a cheaper alternative to Llama 3 8B Instruct?
Llama 3.1 8B Instruct (Meta) at $0.05/1M/1M input against Llama 3 8B Instruct's $0.14/1M/1M — roughly 54% less per token all in. The right tool for cheap, fast, high-volume tasks — not for anything that requires serious thinking. Compare it first if Llama 3 8B Instruct's pricing is the thing stopping you.
What is a faster alternative to Llama 3 8B Instruct?
GPT-5.6 Luna — fast against Llama 3 8B Instruct's very fast, with 1.1M tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.
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