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Llama 3.1 8B vs Yi-Lightning

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Llama 3.1 8B and Yi-Lightning.

Meta

Llama 3.1 8B

Llama 3.1 8B is Meta's lightweight open-weight model from the Llama 3.1 generation, optimized for efficient deployment on consumer hardware and edge devices. Despite its compact 8-billion-parameter size, it delivers strong performance on instruction following, text summarization, and lightweight coding tasks. Lllama 3.1 8B is the most downloaded model in the Llama family and runs efficiently on laptops, single GPUs, and CPU via quantization β€” making it the default choice for on-device AI applications and local prototyping.

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01.AI

Yi-Lightning

Yi-Lightning is 01.AI's (離一万物) fastest and most cost-efficient model, purpose-built for high-throughput production workloads. It delivers competitive performance against GPT-4o-mini and Claude Haiku at a fraction of the cost, with exceptional bilingual Chinese-English capabilities. Yi-Lightning excels at classification, entity extraction, summarization, and high-frequency API tasks where latency and cost-per-call are critical constraints.

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Technical Specifications

SpecificationLlama 3.1 8BYi-Lightning
ProviderMeta01.AI
Context Window131,072 tokens131,072 tokens
Agent Suitability74/10082/100
Time to First Token (TTFT)80 ms120 ms
Deployment Modelself hostablemanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-07-232025-10-01

API Pricing Comparison

Input Price per Million Tokens

Llama 3.1 8B

$0.04

Yi-Lightning

$0.15

Output Price per Million Tokens

Llama 3.1 8B

$0.04

Yi-Lightning

$0.30

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

Llama 3.1 8B Quirks & Gotchas

  • β–ΈPerfect for CPU/edge deployment β€” runs on Raspberry Pi with quantization
  • β–ΈLimited tool calling vs larger models β€” best for simple classification and chat

Yi-Lightning Quirks & Gotchas

  • β–ΈBest cost-efficiency for high-volume bilingual applications
  • β–ΈSelf-hostable via Ollama β€” excellent open-weight option for Asian-language pipelines