← Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

Mistral Medium 3.5 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 Mistral Medium 3.5 and Yi-Lightning.

Mistral

Mistral Medium 3.5

Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI. It supports text and image inputs with text output, and is designed for agentic workflows, coding, and complex...

View Full Specs
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.

View Full Specs

Technical Specifications

SpecificationMistral Medium 3.5Yi-Lightning
ProviderMistral01.AI
Context Window262,144 tokens131,072 tokens
Agent SuitabilityN/A82/100
Time to First Token (TTFT)N/A120 ms
Deployment Modelself hostablemanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-302025-10-01

API Pricing Comparison

Input Price per Million Tokens

Mistral Medium 3.5

$1.50

Yi-Lightning

$0.15

Output Price per Million Tokens

Mistral Medium 3.5

$7.50

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.

Mistral Medium 3.5 Quirks & Gotchas

No developer gotchas reported.

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