Gemini vs GPT vs Claude: Which LLM Is Cheapest for Building a SaaS?

Building a SaaS? Your LLM Choice Matters More Than You Think

You've decided to use an AI coding agent to build your SaaS product. Smart move — it'll save you weeks of development time. But here's the question most developers skip: which LLM should you run it on? The difference between the cheapest and most expensive provider for the exact same project can be 10x or more.

We ran the numbers through the AI Cost Estimator on this site to find out. The setup: a typical SaaS MVP — small size (~5,000 lines of code), 4 core features (authentication, database layer, REST API, payments integration), standard quality, CLI mode (like Claude Code). This maps to roughly 367 turns, ~24.1 million input tokens, and ~294K output tokens.

The Three Providers, Head to Head

Each of the big three providers offers a premium model and a budget model. The premium models (Claude Sonnet 4.6, GPT-4o, Gemini 2.5 Pro) deliver the best code quality and autonomous capability. The budget models (Claude Haiku 4.5, GPT-4.1, Gemini 2.5 Flash) trade some reasoning ability for dramatically lower costs.

Anthropic (Claude)

Anthropic offers two models relevant to SaaS development. Claude Sonnet 4.6 ($3/$15 per million tokens) is the workhorse — excellent at multi-file refactors, understanding complex codebases, and following detailed instructions. Claude Haiku 4.5 ($1/$5 per million tokens) is the budget option — surprisingly capable for straightforward code generation but may need more iteration on tricky logic.

Anthropic's big advantage is prompt caching, which can reduce input costs by up to 90% on repeated prefixes. For a SaaS project where your agent re-reads the same codebase structure every turn, this is a massive cost saver.

OpenAI (GPT)

OpenAI's lineup starts with GPT-4o ($2.50/$10 per million tokens) — a strong general-purpose model that handles coding well, though it sometimes produces more verbose output than Claude. GPT-4.1 ($2/$8 per million tokens) is the newer, more efficient option — better at following instructions and producing concise code, at a lower price point.

OpenAI has partial prompt caching support, but it's not as aggressive as Anthropic's implementation. Your mileage will vary depending on your specific coding workflow.

Google (Gemini)

Google offers the most competitive pricing of the three. Gemini 2.5 Pro ($1.25/$10 per million tokens) has the lowest input price among premium models and a massive 1M token context window. Gemini 2.5 Flash ($0.30/$2.50 per million tokens) is the budget champion — cheap enough to run large projects without wincing at the bill.

The catch? Gemini models occasionally struggle with complex multi-file refactors compared to Claude or GPT. For a SaaS with interconnected features (auth flows, database schemas, API routes), you might need a few more iterations to get things right.

Cost Table: Building a SaaS on Each Model

Here's what it actually costs to build our reference SaaS project (5K LOC, 4 features, CLI mode, standard quality) on each model. All numbers assume ~24.1M input tokens and ~294K output tokens across ~367 turns.

The range is staggering: from $7.97 with Gemini 2.5 Flash to $76.71 with Claude Sonnet 4.6 — nearly a 10x difference for the same project. And notice how input costs dominate: Claude Sonnet's $72.30 in input costs vs just $4.41 in output costs. This is the context accumulation effect in action.

Factor In Prompt Caching

The raw numbers above don't account for prompt caching, and that changes the picture significantly for Anthropic users. In a 367-turn CLI session, your agent re-reads the same codebase structure and system prompt every turn. Anthropic caches these repeated prefixes at 90% off the normal input price.

If roughly 70% of your input tokens hit the cache (a realistic estimate for a coding session), Claude Sonnet's effective input cost drops from $72.30 to about $26.81 — bringing the total down to roughly $31.22. That's competitive with Gemini 2.5 Pro's uncached price, and you get Sonnet-level code quality.

OpenAI and Google have partial caching support, but the savings are less predictable and typically smaller. Anthropic's implementation is the most aggressive and reliable for coding workflows.

Quality vs Cost: What You Actually Get

Cheaper isn't always better if it takes more turns to get the same result. Here's what we've found from real SaaS builds:

• Claude Sonnet 4.6 nails complex SaaS patterns on the first try — auth flows with edge cases, database migrations, payment webhooks. Fewer iterations means potentially lower actual cost than the raw token math suggests.
• GPT-4.1 is close behind in quality, with better instruction following than GPT-4o and cleaner output. A solid mid-range choice at $50.55.
• Gemini 2.5 Pro handles most SaaS tasks well but occasionally requires clarification on complex business logic. The $33.07 price tag is hard to argue with.
• Claude Haiku 4.5 is great for boilerplate and standard CRUD but may need hand-holding on custom payment flows or complex API design. At $25.57 (or ~$10 with caching), the value is excellent.
• Gemini 2.5 Flash at $7.97 is the budget king. Best for early prototyping where you'll refine later with a stronger model.

Our Recommendation

For building a SaaS MVP, the sweet spot depends on your priorities:

• Best quality, regardless of cost: Claude Sonnet 4.6 with prompt caching enabled (~$31). You'll spend less time fixing bugs.
• Best value: Gemini 2.5 Pro ($33) or Claude Haiku 4.5 with caching (~$10). Both deliver solid results at a fraction of the premium price.
• Cheapest viable option: Gemini 2.5 Flash ($8). Use it for the first pass, then refine critical paths with a stronger model.

Want exact numbers for your specific SaaS scope? Run your project through the AI Cost Estimator — it lets you adjust features, codebase size, and quality level to match your exact build.