Llama 3 8B
An 8-billion-parameter instruction-tuned large language model from Meta's Llama 3 series. It is suited to running on a single consumer-grade GPU or edge inference node and performs reliably on narrow tasks such as summarization, classification, and formatted output.
Timeline (last 90 days)
The routing layer can be divided into three tiers: the local/edge tier (such as Llama 3 8B, Mistral 7B, cost about $0.05–$0.15/1M tokens, latency <250ms), the mid-tier hosted tier (such as Claude 3.5 Haiku, GPT-4o-mini, cost about $0.25–$0.60/1M tokens, latency <800ms), and the frontier reasoning tier (such as Claude 3.5 Sonnet, o1, GPT-4o, cost about $3.00–$15.00/1M tokens, latency 2s–8s).
Under a strict system prompt, Llama 3 8B handled structured show notes surprisingly well, rarely hallucinating wrong timestamps and rarely breaking the Markdown format.
本地可运行的模型如 Llama 3 8B、Qwen2 7B 参数仅为顶级云端模型的约百分之一
All Facts (4)
Llama 3 8B模型（80亿参数）运行约需7GB显存
80%UnverifiedThe routing layer can be divided into three tiers: the local/edge tier (such as Llama 3 8B, Mistral 7B, cost about $0.05–$0.15/1M tokens, latency <250ms), the mid-tier hosted tier (such as Claude 3.5 Haiku, GPT-4o-mini, cost about $0.25–$0.60/1M tokens, latency <800ms), and the frontier reasoning tier (such as Claude 3.5 Sonnet, o1, GPT-4o, cost about $3.00–$15.00/1M tokens, latency 2s–8s).
50%UnverifiedUnder a strict system prompt, Llama 3 8B handled structured show notes surprisingly well, rarely hallucinating wrong timestamps and rarely breaking the Markdown format.
50%Unverified本地可运行的模型如 Llama 3 8B、Qwen2 7B 参数仅为顶级云端模型的约百分之一
50%