In one sentence
For 90% of users, free versions are more than sufficient (Claude.ai, ChatGPT, Gemini are all free with limits). But if you use AI every day for work, a paid subscription at £20-30/month pays for itself quickly. And if you integrate AI into a product, the API is a different story altogether.
The 3 ways to pay (or not)
There are 3 different economic models for using AI:
The 3 ways to use AI
| 👤Individual | 🏢Enterprise / Dev | |
|---|---|---|
| Consumer subscription (Pro/Plus) | £20-30/month for unlimited usage | Not suitable for large scale |
| API per token | Too technical for 99% | Standard for product integration |
| Self-hosting (open-source) | Complex, GPU required | Sovereign, full control, but expertise needed |
Option 1: Free versions
All the leaders have a free version. They're very powerful but with limits.
Free version limits in 2026
⚠️ Warning: free versions often have a less powerful model. You use GPT-5 mini instead of full GPT-5, Claude Sonnet instead of Opus, etc.
When free is more than enough
- You use AI occasionally (several times a week, not per day)
- You mostly do simple tasks (summaries, emails, research, translations)
- You don't need advanced features (large files, long documents, bulk image generation, agents that take actions)
When free becomes frustrating
- You hit message limits several times a week
- You need files/images regularly (limited or absent in free)
- You want the latest model available as soon as it's released
- You do long prompts (free model often has shorter context)
Option 2: Consumer subscriptions
£20 to 30/month to have the most powerful model without limits. This is the standard offering from all leaders.
Consumer subscription prices (£/month)
What you unlock with a subscription
- ✅ The best model (GPT-5 vs GPT-5 mini, Opus vs Sonnet)
- ✅ No (or very few) usage limits
- ✅ Longer context (can analyse large documents)
- ✅ Unlimited image generation (on certain plans)
- ✅ Early access to new features
- ✅ Voice mode, agents, custom chatbot creation
The economic calculation
2026 subscription comparison
Claude Pro vs ChatGPT Plus
| 🟣Claude Pro (£18/month) | 🟢ChatGPT Plus (£23/month) | |
|---|---|---|
| Model included | Claude Opus 4.7 + Sonnet 4.6 | GPT-5 + GPT-5 thinking |
| French quality | Excellent | Very good |
| Image generation | No (integrated soon) | DALL-E 3 unlimited |
| Voice mode | No | Yes (advanced) |
| Message limit | 5x more than free | Virtually unlimited |
| Web search | Yes | Yes |
| Agent creation | Yes (Projects) | Yes (GPTs) |
| GDPR compliance | Yes | Yes (with opt-out) |
My personal recommendation
- Claude Pro if you write a lot in French, do complex code, or want the best writing quality
- ChatGPT Plus if you want the widest palette (image, voice, agents, multimodal)
- Mistral Le Chat Pro if European sovereignty is important
- Gemini Advanced if you're in the Google ecosystem (Workspace, Android)
Option 3: API (for developers)
The API allows you to integrate AI into your own applications. You pay per token (≈ 1 word = 1.3 tokens in French).
Current API prices (per million tokens)
API input price - 2026 ($/M tokens)
What does it really cost?
Here are some typical use cases to help you anticipate:
Estimated monthly cost by usage
| Use case | Monthly cost | |
|---|---|---|
| SaaS chatbot, 1,000 conversations/day | 30K tokens/conv | ≈ £200-500 |
| SEO article generation, 100/day | 20K tokens/article | ≈ £300-800 |
| Internal assistant, 50 employees | Moderate usage | ≈ £50-150 |
| B2C mobile app, 10K active users | Average usage | ≈ £1,000-3,000 |
| Document analysis (RAG) | 1,000 docs/month | ≈ £50-200 |
max_tokens to avoid surprisesOption 4: Self-hosting (open-source)
You can download open-source models and run them on your own server. Models to consider:
- Llama 4 (Meta), top quality, but huge
- DeepSeek V3 : excellent quality/price ratio
- Mistral Small 3 : lightweight, perfect for specific use cases
- Mixtral 8x22B : power/cost balance
Self-hosting vs API
| 🏠Self-hosting | ☁️API | |
|---|---|---|
| Initial cost | High (GPU) | £0 |
| Recurring cost | Electricity + maintenance | Per volume |
| Privacy | Total | Depends on provider |
| Model performance | Limited by GPU | Market leading |
| Expertise required | High (DevOps, ML) | Low |
| Updates | Manual, complex | Automatic |
| Sovereignty | Total | Depends on provider country |
When self-hosting makes sense
- ✅ Ultra-sensitive data (health, finance, defence)
- ✅ Huge volume (millions of requests/day) where API becomes too expensive
- ✅ Critical latency (video games, HFT finance)
- ✅ Sovereignty required (government, certain EU companies)
When self-hosting does NOT make sense
- ❌ You're just starting out and want to test
- ❌ You don't have a DevOps + ML team
- ❌ You want the latest model always available
- ❌ Your volume is low (< £100/month in API)
📚Going further: hidden economics of LLMs
The true cost of an AI product
Many startups underestimate the cost of integrating AI. Here's the complete checklist:
Direct costs
- API tokens (input + output)
- Embeddings for semantic search
- Vectorstore (Pinecone, Weaviate, etc.): £50-500/month
- Image model if needed
Hidden costs
- Latency: an LLM call takes 2-10 seconds → impacts UX, therefore churn
- Caching: implementing a caching system to save 50-80%
- Monitoring: prompt observability (Langfuse, Helicone, etc.): £50-200/month
- Evaluation: automated response evaluation system
- Moderation: content filters to prevent abuse
- User support: 30% of tickets will be about hallucinations or AI refusals
Human costs
- An ML/AI engineer: £80-150K/year loaded
- Prompt engineering time: 2-5 days per feature
- Documentation, team training: ongoing
The 10x rule
For every pound spent on API tokens, budget £10 in ancillary costs (infrastructure, monitoring, human resources, support).
This is why "£5 per customer in API so I charge £10" calculations are always wrong. Operating margin is closer to 30% than 50% on current AI products.
Smart strategy: multi-model
Instead of using one model for everything, route intelligently:
- Simple tasks (classification, extraction, short summary) → GPT-5 mini or Gemini Flash (50x cheaper)
- Complex tasks (reasoning, code) → GPT-5 or Claude Opus
- Verification (eval, moderation) → Claude Sonnet (quality/price ratio)
- Embeddings → text-embedding-3-small (very cheap)
This strategy can divide your bill by 5-10.
Moving between thresholds
Many companies follow this path as they grow:
- MVP: ChatGPT Plus at £23 (whole team shares 1 account)
- Early product: basic API, ~£200/month
- Product-market fit: optimisations + caching, multi-model, ~£2,000/month
- Scale: price negotiation with OpenAI/Anthropic, ~£10K/month
- Hyperscale: self-host for high volumes, keep API for premium cases
Practical cases: how much should I pay?
Student, research, occasional writing
Verdict: free version is enough. Combine ChatGPT Free + Claude Free + Gemini Free. Cost: £0
Freelancer, knowledge worker, daily usage
Verdict: 1 Pro subscription (Claude Pro or ChatGPT Plus depending on preference). Cost: £18-23/month
Small startup, AI product integration
Verdict: API + monitoring + caching. Budget £200-500/month to start. Cost: £200-500/month
Company > 50 people
Verdict: combination of Pro accounts + enterprise API + potential self-hosted for confidentiality. Cost: £500-5,000/month depending on usage
Very large company, massive volumes
Verdict: dedicated team, enterprise pricing negotiation, partial self-hosting on Llama 4 or DeepSeek. Cost: £10K-100K/month
🎯 Find the perfect model for YOUR budget
Filter by price, free tier, GDPR, open-source. 30 models compared in detail.
Quiz: your AI economics instinct
For occasional personal use, what's the best strategy?
Going further
- 🎯 Compare models with price filter: find the best quality/price ratio
- 🧠 Understand benchmarks: MMLU, HumanEval, Arena Elo... decode what really matters
- ⚡ Learn prompt engineering: a good prompt with a small model often beats a bad prompt with a large model
My final advice: start free, upgrade when you feel the friction, and don't hesitate to combine several services to get the best from each. ✨