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ChatGPT Plus vs Claude Pro vs DeepSeek API: squeezing the most work out of ~₩30,000 a month

A 2026 subscription-cost guide for developers and operators. We compare code generation, long-document analysis, and output per dollar — not vendor slogans.

AIAI Tech Engine Lab
Checked on our independent test-bed
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ChatGPT Plus vs Claude Pro vs DeepSeek API: squeezing the most work out of ~₩30,000 a month

One-line take: ChatGPT Plus for general chat, Claude 3.5 Sonnet (wired through Cursor) for messy refactors and architecture, DeepSeek API when you need volume and a lower bill.


1. What the three services actually look like at work

ChatGPT Plus ($20/mo) Claude Pro ($20/mo) DeepSeek API (pay as you go)
Workhorse model GPT-4o / o1-preview Claude 3.5 Sonnet / Opus DeepSeek-V3 / R1
Coding (HumanEval) 90.2% 93.7% (highest of the three) 91.6%
Context window 128k tokens 200k tokens (most stable here) 64k ~ 128k tokens
Cost per 1M tokens $20 flat (usage capped) $20 flat (strict message cap) $0.14 in / $0.28 out (~95% cheaper)
Best fit General work, images, web search Senior engineers, large codebases Pipelines, bots, students

2. Pros and cons from the desk, not the brochure

1) Claude 3.5 Sonnet: still the default for developers

  • Pros: Least hallucination when generating frontend UI or refactoring messy backend logic.
  • Cons: Rate limits are tight. A few long code sessions over 4–5 hours and you get blocked.
  • Workaround: Skip the Claude Pro web UI. Cursor IDE or an API-key tool is more productive.

2) DeepSeek-V3 / R1: price destruction plus open weights

  • Pros: Roughly 1/20 of OpenAI’s price at similar quality. R1’s thinking pass holds up on math and awkward algorithms, close to o1.
  • Cons: Official servers can wobble when traffic spikes.
  • Workaround: Run a Distill model (Qwen 32B) on a local workstation, or dual-home a paid API endpoint as failover.

3. A ~₩30,000 portfolio that actually ships work

Recommended mix:
1. Cursor Pro ($20/mo) → near-unlimited Claude 3.5 Sonnet coding
2. DeepSeek API ($5 credit) → bulk parsing, scripts, summary bots
3. Local Ollama ($0) → private or sensitive data stays on the box
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Spend: about $25 (~₩34,000) → a full-stack pipeline without an enterprise contract
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