Claude vs GPT vs Gemini vs DeepSeek: the 2026 cheat sheet

After running production workloads across every major LLM for a year, here’s what we actually pick for what.

TL;DR by job

Job	First pick	Cheap alternative
Customer-facing chatbot	gpt-4o-mini	deepseek-chat
Long-document analysis	claude-3-5-sonnet	gemini-1.5-pro
Code completion (Tab)	deepseek-coder	codestral-latest
Code chat / refactor	claude-3-5-sonnet	gpt-4o
Agent / tool use	claude-3-5-sonnet	gpt-4o
Image understanding	gemini-2.0-flash	gpt-4o
Bulk classification	gpt-4o-mini	deepseek-chat
Creative writing	claude-3-opus	gpt-4o
Reasoning math/logic	o1	deepseek-reasoner
Cost-sensitive batch	deepseek-chat	qwen-turbo

Where each model genuinely wins

Claude 3.5 Sonnet — best instruction following and tool calling. If you need an agent that reliably calls 4+ tools in sequence without going off-script, this is the default. Also strongest at refusing-when-asked (helpful for content-policy-strict products).

GPT-4o — best at parallel tool calls (Claude does serial tool use better; GPT does parallel). Best JSON-mode reliability. Best multilingual coverage outside Chinese.

Gemini 1.5/2.0 — wins on long context. The 1M token window genuinely works (we’ve fed it whole textbooks). Cheapest per million input tokens at scale.

DeepSeek — ridiculously cheap for what you get. On math, code, and Chinese tasks, deepseek-chat is within 5-10% of GPT-4o at 1/15th the cost.

o1 / o1-mini — only worth it for actual reasoning chains (proof checking, optimization, code analysis). For chat or writing, it’s overkill and slower.

The cost picture

Per million output tokens (approximate):

o1                    $60.00
claude-3-opus         $75.00
claude-3-5-sonnet     $15.00
gpt-4o                $10.00
gemini-1.5-pro         $5.00
claude-3-5-haiku       $4.00
gpt-4o-mini            $0.60
deepseek-chat          $1.10
deepseek-coder         $1.10
qwen-turbo             $0.30

Notice the ~100x spread between deepseek and o1. That’s why model routing matters more than model selection — using o1 for tasks deepseek would handle is leaving 99% of your AI budget on the table.

How we’d build a new product

1. Start with claude-3-5-sonnet everywhere because it’s the most reliable.
2. Profile your traffic. Identify “easy” requests (greetings, FAQ, short summaries).
3. Route easy requests to deepseek-chat or gpt-4o-mini.
4. Reserve claude-3-5-sonnet for what actually needs it.
5. Add o1 only when you discover a class of requests that genuinely needs deep reasoning.

This typically takes a $5k/month AI bill down to $500-1000.

Why JJAPI works for this

Because the model strings above are interchangeable through one endpoint, this kind of routing takes one if/elif block — not separate accounts, billing, or SDK wrappers. The full $15/1M → $1/1M cost reduction is available behind one API key.