Marrying one AI model is betting that today's best will still be best tomorrow.
The model market changes leaders in months: OpenAI went from 50% to 25% of enterprise usage between 2023 and 2025, according to Menlo Ventures, and models get retired with little notice. Building on a single provider means migrating every time. In Shimli, FusionAI picks the right model for each task and adopts better ones without you changing anything.
Why choosing well matters
- 50% → 25%
- is how far OpenAI's share of enterprise model usage fell between 2023 and mid-2025; Anthropic took the lead with 32%Menlo Ventures · 2025 ↗
- 4.5 months
- is how long GPT-4.5 Preview lasted on OpenAI's API: launched in February 2025 and removed on July 14OpenAI, developer notice · 2025 ↗
- The norm
- is to run several models in production; picking the right one for each use case is the main reasona16z, CIO survey · 2025 ↗
What depending on a single provider costs
No model is best at everything: one reasons better, another is faster, another costs less. And the ranking changes every few months.
With a single model, your team
- Uses the same model for everything, even if another is better at a task
- Pays the large model's price even for simple tasks
- Migrates against the clock when the model is retired
- Retests the agent with every new version
- Depends on a single provider's prices and terms
Every provider change becomes a project.
With FusionAI
The agent has to read a receipt, decide on an extension and reply fast on WhatsApp.
- FusionAI picks the right model for each task
- We use the best models and evaluate them constantly
- When a better one appears, it's adopted without you changing anything
- Only stable, tested models run in production
Three different tasks, the right model for each, without you choosing anything.
The comparison, point by point
It isn't about which model is best today, but what happens when it stops being so.
| Criterion | A single modelone provider |  Multi-LLM with FusionAIautomatic |
|---|---|---|
| When a better model comes out | The code has to change and be retested | FusionAI evaluates and adopts it |
| When the provider retires a model | Forced migration, on the provider's deadline | FusionAI moves the task to another model |
| Different tasks | The same model for everything | The right model for each: reasoning, reading, replying fast |
| Who picks the model | Your team, and it decides again with every change | FusionAI, automatically |
| Provider dependency | Total: one provider's prices, limits and terms | None: the agent and its memory don't depend on the model |
AI usage is paid in blocks of $49 per 2,450 queries, whichever model FusionAI uses. No accounts or contracts with model providers. See pricing
When each one fits
It isn't a contest: they're tools for different problems.
A single model may be enough if…
- It's a prototype or a small internal use.
- You have a team that can migrate when needed.
Multi-LLM fits if…
- The agent serves customers and can't stop for a provider change.
- It does different tasks that are better solved by different models.
- You don't want your operation to depend on one provider's prices.
Frequently asked questions
What people ask when comparing.
Create your first agent in under 10 minutes.
Describe what you need to the assistant and watch the agent work. Or we book 30 minutes and look at it on your operation.
