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Command R 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 Command R and Yi-Lightning.

Cohere

Command R

Command R is Cohere's lightweight, cost-efficient model engineered for high-speed enterprise integrations, productivity automation, and retrieval-augmented generation (RAG) pipelines. Optimized for low-latency API tool use and structured JSON output, it is particularly effective in enterprise search and question-answering systems where fast, reliable responses are critical. With a 128,000-token context window and a price of $0.15/MTok for input, Command R provides strong RAG performance and multilingual support at a fraction of the cost of Command R+, making it the preferred choice for teams scaling intelligent document retrieval at high request volumes.

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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

SpecificationCommand RYi-Lightning
ProviderCohere01.AI
Context Window128,000 tokens131,072 tokens
Agent Suitability78/10082/100
Time to First Token (TTFT)200 ms120 ms
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-03-112025-10-01

API Pricing Comparison

Input Price per Million Tokens

Command R

$0.15

Yi-Lightning

$0.15

Output Price per Million Tokens

Command R

$0.60

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.

MMLUGeneral knowledge & multi-task understanding
7100.0%vsN/A
Command R
Yi-Lightning
HumanEvalPython coding & logic synthesis
7300.0%vsN/A
Command R
Yi-Lightning
MATHComplex mathematical problem solving
5400.0%vsN/A
Command R
Yi-Lightning
GPQAGraduate-level expert reasoning
3500.0%vsN/A
Command R
Yi-Lightning
HellaSwagCommonsense reasoning and inference
7800.0%vsN/A
Command R
Yi-Lightning
MT-BenchMulti-turn conversation flow quality
750.0%vsN/A
Command R
Yi-Lightning

Command R Quirks & Gotchas

  • β–ΈCost-effective RAG model β€” strong multilingual search performance
  • β–ΈLimited agentic capability β€” use Command R+ for complex multi-step tool use

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