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AI Startup Metrics & Valuations 2026

By TLDL

AI startup valuation benchmarks and investment framework. ARR multiples, growth rates, and what investors are paying in 2026.

AI Startup Metrics & Valuations 2026

Valuation benchmarks and metrics for AI investors.

Current Market Reality (Feb 2026)

Valuation State

  • Foundation models: 20-50x ARR (down from 100x in 2023)
  • AI infrastructure: 15-25x ARR
  • AI applications: 8-20x ARR (highly variable)

Key Trends

  1. Revenue matters more - No revenue = $0 valuation
  2. Gross margins critical - Below 60% = problematic
  3. Burn rate scrutinized - Path to profitability now required
  4. Down rounds happening - 20-30% of 2024 raises

Stage-Based Metrics

Pre-Seed / Seed

Metric Good Great Red Flag
Users 1K+ DAU 10K+ DAU <100
Growth 20% MoM 50%+ MoM <10%
Engagement 5 min/day 15+ min/day <1 min
Team 2 founders 2+ technical Solo non-technical

Series A

Metric Good Great Red Flag
ARR $1M $3M+ <$500K
Growth 3x YoY 5x+ YoY <2x
NPS 40+ 60+ <20
Retention 90% MoM 95%+ MoM <80%

Series B

Metric Good Great Red Flag
ARR $10M $25M+ <$5M
Growth 80% YoY 150%+ YoY <50%
Gross Margin 70% 80%+ <60%
NRR 110% 140%+ <100%

Series C+

Metric Good Great Red Flag
ARR $50M $100M+ <$25M
Growth 50% YoY 100%+ YoY <30%
Gross Margin 75% 85%+ <65%
EBITDA Positive 20%+ margin Negative

AI-Specific Metrics

Model Performance

Metric Benchmark Notes
Token cost <$1/1M input Falling 50%/year
Latency <500ms p99 Critical for UX
Accuracy +5% vs baseline Measurable improvement
Cost/response <$0.01 Must scale

User Engagement

Metric Good Great
Messages/user/day 5+ 20+
Feature usage 30%+ using AI 60%+
Return rate 40% weekly 60% weekly

Business Metrics

Metric Formula Good
Revenue/user ARR / MAU >$10
Support cost reduction % decrease >30%
Conversion Trial → Paid >20%

Unit Economics Deep Dive

The Math

Gross Margin = (Revenue - COGS) / Revenue
- AI Apps: 70-85% (mostly compute)
- AI Infrastructure: 50-70% (heavy compute)
- Traditional SaaS: 75-85%

CAC = Sales + Marketing spend / New customers
- Good: <$1000
- Great: <$500
- Bad: >$5000

LTV = Margin × Customer lifespan
- Good: 3x CAC
- Great: 5x+ CAC
- Bad: <1x CAC

Payback = CAC / (Margin × MRR/customer)
- Good: <12 months
- Great: <6 months
- Bad: >24 months

Common Failure Modes

  1. Compute costs = COGS - Low gross margin
  2. Freemium abuse - High usage, low conversion
  3. Enterprise sales cycle - >12 months payback
  4. Model API dependency - No margin control

Valuation Multiples by Category

Foundation Models

Stage Multiple Rationale
Seed 30-50x ARR Platform optionality
A 20-40x ARR Product traction
B 15-30x ARR Revenue scaling
C+ 10-20x ARR Proven model

AI Infrastructure

Stage Multiple Rationale
Seed 20-30x ARR Tech differentiation
A 15-25x ARR Customer references
B 10-20x ARR Scale evidence
C+ 8-15x ARR Predictable growth

AI Applications

Stage Multiple Rationale
Seed 15-25x ARR Founder quality
A 10-20x ARR Product-market fit
B 8-15x ARR Growth rate
C+ 5-12x ARR Revenue maturity

Due Diligence Deep Dive

For AI Companies

Technical DD

  1. Model architecture - Proprietary vs fine-tuned?
  2. Training data - Where does it come from?
  3. Inference costs - What's the cost structure?
  4. Evaluation - How do you measure quality?
  5. Roadmap - What's the technical plan?

Business DD

  1. Revenue - Verified by Stripe/API?
  2. Customers - Who are they? (3+ references)
  3. Churn - Why do customers leave?
  4. Competition - How do you differentiate?
  5. Team - Can they execute?

Red Flags

  1. "We're building GPT-5 competitor" - Unless you have $5B+
  2. No revenue but high valuation - Show me the money
  3. Heavy LLM reliance - What's your moat?
  4. Burning $10M+/year - At what revenue?
  5. Team can't code - At least one technical founder

Investor Terms to Negotiate

Founder-Friendly

  • 1x liquidation preference
  • 4-year vesting, 1-year cliff
  • Single triggers for acceleration
  • Pro-rata rights

Investor-Friendly

  • Participation up to 2x
  • Board control
  • Full ratchet
  • MFN clauses

Last updated: February 2026

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