AI 코딩 에이전트의 실제 비용: 335개 수치, 모두 출처 문장과 날짜 포함

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공개 데이터셋입니다. 32편의 현장 기록에 나온 모든 수치 —— 가격, 비율, 배수, 토큰 수, 소요 시간 —— 를 한 줄씩 뽑아내고 원래 문장 전체와 게시 날짜를 함께 실었습니다.

에이전트 모델의 오늘 가격

Design Arena의 agents 부문에 순위가 있는 60개 모델의 100만 토큰당 정가입니다. 청구서가 아닙니다 — 캐시, 배치, 제공자마다 가격이 다릅니다. OpenRouter의 공개 카탈로그에서 2026-08-22에 마지막으로 읽었습니다. 가장 싼 3개:

$ in / 1M	$ out / 1M	Model	Best agents rank
$0.1875	$0.9375	Gemini 3.7 Flash `batch`	#3 androidnative
$0.25	$1.50	Gemini 3 Flash Preview `batch`	#9 agenticslides
$0.30	$1.20	MiniMax M3	#10 python-pptxslides

60개 전체 · JSON · CSV

수치 먼저

아래 줄들은 영어 원문 그대로이며 번역하지 않았습니다. 수치는 원래 문장에서 떼어내면 검증할 수 없기 때문입니다 —— $1.43이 100만 토큰당인지, 월 요금인지, 좌석당인지는 그 문장에만 적혀 있습니다.

Figure	The sentence it came from	Write-up
`$1.43`	The $1.43 and the $9.05 are both frontier models doing a job they were not specifically built for.	The Two Best AI Code Reviewers Score the Same. One Costs $1.43 a Run, the Other $9.05.
`$29`	Before writing a contract-comparison tool, one builder handled three to ten comparisons by hand at $29 a document, and only turned the routine into software once the same people kept coming back and paying for it.	Debunking the Myth of Overnight Success in Micro-SaaS
`90%`	90% of developers still rely on manual prompt writing, while top performers use Skill Package to automate 80% of repetitive tasks, saving hours weekly.	Best Practices for AI Agent Skill Management
`80%`	When the Claude Code team decided to slash 80% of their system prompts, most developers expected the model to lose its edge in complex engineering tasks.	Why Stripping 80% of System Prompts Actually Improved Claude Code’s Performance
`$30`	With a budget as low as $30 per day, developers have reached an effective lead cost of $3 to $4.	Stop Reading SimilarWeb Like a Traffic Dashboard — Read It Like a Feasibility Test
`$1,000`	Instead of chasing a 2.5% consumer conversion rate across unpredictable social channels, you sell a single $1,000 to $5,000 service package directly to one business owner — no massive ad campaigns, no hundreds of low-tier support tickets.	How Indie Developers Are Building AI-Powered “Digital Landlords” and Renting Them Out for Monthly Cash Flow
`40-second`	When an independent developer uses Agency Agents to set up a 40-second response cycle for e-commerce listings, they are building a feedback loop that reads market conditions and adjusts, which is what separates a timed automation from a script on a timer.	Stop Chatting With AI: How I Use /loop and /hook to Automate My Indie Dev Workflow
`9.1%`	One reported case moved entry-group conversion from 9.1% to 55.1% by rebuilding an automated onboarding flow around what the funnel data actually showed, rather than around what the team assumed users were doing.	Boosting AI Bot Conversion: A Deep Dive into Funnel Data
`$1.25`	Meta priced Muse Spark 1.1 at $1.25 per million input and $4.25 per million output, roughly 75% and 83% below Anthropic’s Opus, and the tradeoff is visible in the benchmarks, since it leads on MCP Atlas and JobBench while trailing on SWE-Bench Pro and DeepSWE 1.1.	1.6 Billion Free Tokens Is a Compression Ratio, Not a Strategy
`9x`	Open Code Review reports roughly 9x lower token consumption than general-purpose agents while holding accuracy, which suggests that a specialized agent aimed at one job often beats a heavy generalist on the only axis an indie developer can afford to optimize.	Token Optimization for Indie Developers’ AI API Bills
`87 percent`	The 87 percent figure and those two cases are measuring the same thing from different angles, which is time spent moving data by hand between a system that knows the answer and a system that needs it.	The 5 AI Features That Separated 27 Profitable Solopreneurs From the Rest
`40 seconds`	By using an AI agent to automate responses, negotiation, and price adjustment, the average response time can be reduced to within 40 seconds.	From AI Demo to Product: Loop Engineering for Indie Devs

335개 전체

curl -s https://cdn.jsdelivr.net/gh/xyzs996/llm-api-pricing@main/data/figures.json
curl -s https://cdn.jsdelivr.net/gh/xyzs996/llm-api-pricing@main/data/figures.csv

published는 그 기록을 게시한 날이지 그 가격이 유효하던 날이 아닙니다. 가격은 계속 바뀌므로 각 줄은 그 줄 자신의 날짜 기준으로 읽으십시오.

본문

본문은 영어이며 여기 있습니다: https://xyzs996.github.io/llm-api-pricing/ —— 수치 표, 주제별 페이지, 업체별 페이지가 있습니다. 수치만 필요하다면 위의 curl 두 줄이면 충분합니다.

한마디

이 저장소에 별을 누르면 갱신을 따라갈 수 있습니다. 데이터는 CC BY라서 별과 무관하게 무엇이든 하실 수 있습니다.
수치가 틀렸나요? 가격이 바뀌었거나 직접 재보니 다른 값이 나왔다면 issue를 열어 주십시오. 이 저장소는 그러라고 있습니다. (issue)
원하는 수치가 없나요? 어떤 지표를, 어느 업체의, 어떤 단위로 —— 한 줄이면 됩니다. 필수 항목은 하나뿐이고, 들어온 요청은 새 줄이 됩니다. (form)

CC BY 4.0: 복제, 재게시, 가공, 판매 모두 자유입니다. 조건은 하나, 출처를 밝히는 것 —— https://xyzs996.github.io/llm-api-pricing/ 링크면 됩니다.