The go-to model when cost per token matters more than output quality.
Ultra-low-cost text classification, simple Q&A, and high-volume automation pipelines where cost per token is critical.
Extremely cheap at $0.027/1M input tokens — among the lowest cost models available
Fast inference suitable for high-throughput pipelines and real-time applications
Open-weight lineage allows fine-tuning for domain-specific classification or extraction tasks
Sufficient for structured output tasks like JSON extraction, tagging, and routing
1B parameters severely limits reasoning depth, complex instruction-following, and multi-step tasks
See what Meta: Llama 3.2 1B Instruct actually costs at your usage level
Based on Meta: Llama 3.2 1B Instruct API pricing: $0.027/1M input · $0.19999999999999998/1M output. Real costs vary by provider discounts and caching. Check the provider for exact current rates.
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4 data points · tracked daily since May 9, 2026
Ultra-low-cost text classification, simple Q&A, and high-volume automation pipelines where cost per token is critical.. Start free — no card required.
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Llama 3 8B Instruct is Meta's compact open-weight instruction-following model, optimized for efficiency and accessibility at extremely low cost. It handles everyday text tasks like summarization, Q&A, and light coding at a fraction of the price of frontier models.
Pricing moves, ranking shifts, and capability updates.
Meta: Llama 3.2 1B Instruct (Meta) is now indexed. The go-to model when cost per token matters more than output quality.
View modelMeta: Llama 3.2 1B Instruct is best for ultra-low-cost text classification, simple q&a, and high-volume automation pipelines where cost per token is critical.. It is a strong fit when that workflow matters more than the tradeoffs around budget pricing and very fast speed.
You need reliable multi-step reasoning, high-quality code generation, or nuanced creative writing — this model will underperform noticeably on all three.
Meta: Llama 3.1 8B Instruct is the lower-cost option to compare first when you want a similar workflow fit with less token spend.
Meta: Llama 3 8B Instruct is the better pick when response time matters more than maximum depth or premium quality.
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You need reliable multi-step reasoning, high-quality code generation, or nuanced creative writing — this model will underperform noticeably on all three.
60K context window is modest compared to competitors like Gemini Flash (1M) or GPT-4o Mini (128K)
Noticeably weaker than even budget rivals like GPT-4o Mini or Claude Haiku 3.5 on nuanced writing and coding
Meta's Llama 3.1 70B Instruct is a open-weight large language model with 70 billion parameters, fine-tuned for instruction following across coding, reasoning, and general-purpose tasks. It offers a strong balance of capability and cost at $0.40/1M tokens for both input and output.
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.
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