What's the difference between GPT-4, Claude, and Gemini?

GPT-4 (OpenAI): Best for general tasks, largest ecosystem, highest cost. Claude (Anthropic): Strong at analysis, long documents, and safety. Gemini (Google): Great for multimodal (images + text), Google integration. For Japanese: All handle Japanese well, Claude and Gemini slightly stronger in nuanced Japanese.

Which LLM is best for business use?

Depends on use case. Customer service: GPT-4o-mini (fast, cheap). Document analysis: Claude 3.5 Sonnet (long context). Research/creative: GPT-4o. Multimodal (images): Gemini Pro Vision. Japanese-heavy: Claude or Gemini. We recommend testing multiple models for your specific use case—performance varies by task.

Are there free LLMs for business?

Open-source options: LLaMA 3 (Meta), Mistral, Qwen. Run on your servers—no per-token cost, full privacy. Cons: Setup complexity, need GPU servers, not as capable as GPT-4. Good for: privacy-sensitive applications, high-volume use, or long-term cost optimization. Free tiers also available for GPT-4o-mini, Claude Haiku.

What Is the Difference Between GPT-4 and Other LLMs?

GPT-4 isn't your only option. Here's how the major LLMs compare and when to use each.

Major LLMs Compared

Model	Provider	Strength	Cost
GPT-4o	OpenAI	General purpose	$$$
GPT-4o-mini	OpenAI	Fast, affordable	$
Claude 3.5 Sonnet	Anthropic	Analysis, long docs	$$
Claude 3.5 Haiku	Anthropic	Fast responses	$
Gemini Pro	Google	Multimodal, Google	$$
LLaMA 3	Meta (open)	Self-hosted	Free (hosting $$)

GPT-4 Family (OpenAI)

Best for: General business tasks, widest integration

GPT-4o: Most capable, handles images and text
GPT-4o-mini: Cheaper, faster, 80% of capability
o1: Complex reasoning (slower, more expensive)

Japanese: Good, sometimes awkward phrasing

Claude Family (Anthropic)

Best for: Document analysis, nuanced writing

Claude 3.5 Sonnet: Best for analysis, 200k context
Claude 3.5 Haiku: Fast, affordable
Safety focus: Less prone to harmful outputs

Japanese: Very natural, culturally aware

Gemini Family (Google)

Best for: Multimodal, Google integration

Gemini Pro: General purpose, good at images
Gemini Flash: Faster, cheaper
Google ecosystem: Docs, Sheets, etc.

Japanese: Strong, benefits from Google's Japanese data

Open-Source Models

Best for: Privacy, control, long-term cost

LLaMA 3: Meta's model, good all-around
Mistral: European, efficient
Qwen: Strong for Asian languages

Trade-off: Setup complexity vs. privacy and cost

Use Case Recommendations

Use Case	Recommended Model	Why
Chatbots	GPT-4o-mini or Claude Haiku	Fast, affordable
Document analysis	Claude 3.5 Sonnet	Long context
Japanese writing	Claude or Gemini	Natural language
Image + text	GPT-4o or Gemini Pro	Multimodal
Private data	LLaMA 3 (hosted)	No data leaves
High volume	GPT-4o-mini	Low per-call cost

Cost Comparison

Per 1M tokens (approximate):

Model	Input	Output
GPT-4o	$2.50	$10.00
GPT-4o-mini	$0.15	$0.60
Claude 3.5 Sonnet	$3.00	$15.00
Claude 3.5 Haiku	$0.25	$1.25
Gemini Pro	$0.50	$1.50
LLaMA 3 (hosted)	Hosting cost only

How to Choose

Define use case: What task will AI do?
Test multiple: Run same prompts through several
Measure quality: Rate output for your need
Consider cost: Calculate monthly usage cost
Factor privacy: Where does data go?

Greene Recommendation

Most businesses start with:

Primary: GPT-4o-mini for cost-effective general use
Secondary: Claude 3.5 Sonnet for documents, Japanese
Special: Gemini if heavy Google integration

Need help choosing an LLM?

We'll test models for your specific use case and recommend the best fit.

Book Free Assessment →