Claude Haiku 5.5
Anthropic's October 7, 2026 low-cost model and the first Haiku with adjustable reasoning effort — thinking can be switched off for simple requests or raised to max, at $0.10/$0.50 per 1M under 100K input tokens.
The cheapest capable AI API in October 2026 costs $0.10 per million input tokens: OpenAI's GPT-6 Luna and Anthropic's Claude Haiku 5.5 both charge $0.10/$0.50. Mistral Small 3.1 is cheaper on output at $0.10/$0.30 but is an older, smaller model. You do not need to be a developer to use any of them: tools like Zapier and Make.com connect to these APIs with no code at all. This page covers the best cheap options whether you are building a product, automating a workflow, or just want to understand what an API actually charges you for.
Last verified:
/Rankings refresh daily when model data changesOpenAI's budget tier at half the old price.
GPT-6 Luna and Claude Haiku 5.5 put current models from the two biggest labs at $0.10 per million input tokens — a fortieth of the price of Claude Opus 5.5.
Both have long-prompt surcharges (Haiku above 100K input tokens, Luna above 272K), so keeping prompts short is the simplest way to control the bill.
All of these APIs work through no-code tools such as Zapier and Make.com, so you can use them in automations without writing code.
Choose GPT-6 Luna when you are already on OpenAI's SDK, need long prompts, or can use the Flex tier at $0.05/$0.25 for work that is not urgent.
Choose Claude Haiku 5.5 for tool calls, extraction and sub-agent steps, with reasoning switched off for simple requests.
Choose DeepSeek V4.1 Flash when you want open weights you can move to your own servers later; check the host's rate, which varies.
Use the controls to see how the recommendation changes when your workflow shifts toward quality, cost, speed, or long-context work.
Anthropic / Budget / Oct 10, 2026
Anthropic's budget model, now with adjustable reasoning, at $0.10/$0.50.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
Your prompts routinely exceed 100K tokens, where the price quintuples, or the task needs sustained reasoning that Sonnet 5.5 handles far better.
$0.10/$0.50 per 1M — half of GPT-5.6 Luna's $0.20/$1.20
Flex tier at $0.05/$0.25 for batch-style work
Reasoning effort can be turned off entirely for the cheapest calls
Artificial Analysis scores it 38 on its Intelligence Index, behind Claude Haiku 5.5 (43) and Gemini 3.8 Flash (41)
Prompts above 272K input tokens are billed at a higher rate
Strong backups depending on your budget, workload, and preferred tradeoffs.
Anthropic's October 7, 2026 low-cost model and the first Haiku with adjustable reasoning effort — thinking can be switched off for simple requests or raised to max, at $0.10/$0.50 per 1M under 100K input tokens.
Fast, low-cost model with a 1M token context window — the best budget default for teams running high prompt volumes.
Llama 3.2 1B Instruct is Meta's smallest production language model, designed for lightweight text tasks with an extremely low cost footprint. It excels at simple instruction-following, text classification, and on-device or edge deployment scenarios.
Google's fastest and most cost-effective 3.5-generation model — low-latency, high-throughput agentic workflows at a fraction of Flash pricing.
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| GPT-6 LunaOpenAI | $0.10/1M | $0.50/1M | $2.00 | 1.1M tokens | Very fast | 84 | 82 | 80 |
| Claude Haiku 5.5Anthropic | $0.10/1M | $0.50/1M | $2.00 | 1M tokens | Very fast | 86 | 84 | 82 |
| Gemini 3.1 FlashGoogle | $0.50/1M | $3.00/1M | $11 | 1M tokens | Very fast | 68 | 75 | 76 |
| Llama 3.2 1B InstructMeta | $0.03/1M | $0.20/1M | $0.67 | 60k tokens | Very fast | 28 | 32 | 22 |
| Gemini 3.5 Flash-LiteGoogle | $0.30/1M | $2.50/1M | $8.00 | 1.0M tokens | Very fast | 78 | 76 | 78 |
Scores out of 100 — how we evaluate models. “Est. month” is 10M in / 2M out at list price: a ceiling, no discounts.
Why each one is on the shortlist for cheap AI API, what it is genuinely good at, and when we would steer you away from it.
Our pick for cheap AI API. It scores 97/100 on the budget axis we weight this page by, and nothing else in this shortlist matches it on output quality.
OpenAI's September 22, 2026 low-cost reasoning model, replacing GPT-5.6 Luna at $0.10/$0.50 per 1M — half the predecessor's price, with the same 1.05M context.
You are choosing a budget model from scratch — Claude Haiku 5.5 costs the same and scores higher on Artificial Analysis's index.
A cheaper Luna rather than a smarter one. At $0.10/$0.50 it matches Claude Haiku 5.5 on price, but independent scoring puts Haiku 5.5 slightly ahead; choose Luna when you are already on the OpenAI stack.
Full pricing, benchmark table and release notes on the GPT-6 Luna page.
The fastest model in this shortlist for cheap AI API. Pick it when turnaround is what your readers or users notice.
Anthropic's October 7, 2026 low-cost model and the first Haiku with adjustable reasoning effort — thinking can be switched off for simple requests or raised to max, at $0.10/$0.50 per 1M under 100K input tokens.
Your prompts routinely exceed 100K tokens, where the price quintuples, or the task needs sustained reasoning that Sonnet 5.5 handles far better.
The cheapest way to put an Anthropic model in a high-volume pipeline. Keep requests under 100K tokens to stay on the low rate, and set effort per task — at low effort it is a fast classifier, at max it handles real tool-use work.
Full pricing, benchmark table and release notes on the Claude Haiku 5.5 page.
Also worth a look for cheap AI API, at 97/100 on the budget axis.
Best cheap AI for broad day-to-day work — now with 1M context. Full Gemini 3.1 Flash review →
Where most budgets should land for cheap AI API — about 62% less per token than GPT-6 Luna, and still 97/100 on the budget axis.
The go-to model when cost per token matters more than output quality. Full Llama 3.2 1B Instruct review →
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For cheap AI API, GPT-6 Luna (OpenAI) is our pick. OpenAI's budget tier at half the old price. It costs $0.1/1M input and $0.5/1M output tokens, with a 1.05M-token context window — enough headroom for all but the largest cheap AI API jobs. Claude Haiku 5.5 is the closest alternative if it doesn't fit your setup.
Because the work it is built for overlaps closely with cheap AI API: summarization, extraction and tagging at very high volume and routine steps inside agent pipelines where a Sol-tier model would be overkill. A cheaper Luna rather than a smarter one. At $0.10/$0.50 it matches Claude Haiku 5.5 on price, but independent scoring puts Haiku 5.5 slightly ahead; choose Luna when you are already on the OpenAI stack.
On a moderate month — 10M input and 2M output tokens — GPT-6 Luna runs about $2.00 at list price, with no batch or caching discounts applied, so treat that as a ceiling. Llama 3.2 1B Instruct is the cheaper route at roughly $0.67 for the same volume, if cheap AI API is high-volume enough for price to lead the decision.
Artificial Analysis scores it 38 on its Intelligence Index, behind Claude Haiku 5.5 (43) and Gemini 3.8 Flash (41). Prompts above 272K input tokens are billed at a higher rate. Avoid it if you are choosing a budget model from scratch — Claude Haiku 5.5 costs the same and scores higher on Artificial Analysis's index. None of that rules it out for cheap AI API on its own — but if one of those limits maps onto how you actually work, take the alternative on this page seriously rather than defaulting to the top pick.
Llama 3.2 1B Instruct at $0.027/1M input is the budget option here. The go-to model when cost per token matters more than output quality. Expect a quality step down on the hardest cases — the usual pattern is to route routine cheap AI API volume to Llama 3.2 1B Instruct and keep GPT-6 Luna for the work where a wrong answer is expensive.
PLAIN ENGLISH
An API is just a way to talk to an AI model from your own app, tool, or automation — instead of using a chat window like ChatGPT. You send text in, get text back, and pay only for what you use.
STEP 1
You send a message
A question, a document to summarize, a task — any text
STEP 2
The AI processes it
The model reads your input and generates a response
STEP 3
You get the reply back
Plain text you can display, save, or act on — instantly
You pay per "token" — roughly 0.75 words. At DeepSeek V3 prices, 1 million tokens costs $0.07. A typical paragraph is ~100 tokens, so $0.07 buys you roughly 10,000 paragraphs of input.
You don't need to write code to use AI APIs — pick your starting point
I WRITE CODE
Call the model with any HTTP client or the OpenAI SDK. DeepSeek V3 is OpenAI-compatible — swap the base URL and you're done.
I USE ZAPIER / MAKE
Zapier, Make.com, and n8n all support AI steps natively. Connect your AI model to emails, spreadsheets, Slack, or any of thousands of apps — no code required.
I JUST WANT A CHAT APP
If you want to talk to an AI in a chat interface rather than build something, a $20/mo subscription (Claude Pro, ChatGPT Plus) is simpler and often cheaper than paying per token.
Per-token pricing is confusing — here's what common tasks cost in dollars
| Task | DeepSeek V3 | GPT-4o Mini | GPT-4o |
|---|---|---|---|
1,000 customer support replies ~500 tokens in, ~400 tokens out each | $0.15 | $0.32 | $1.65 |
Summarize 500 long documents ~2,000 tokens in, ~300 tokens out each | $0.74 | $1.65 | $8.75 |
10,000 product descriptions ~200 tokens in, ~300 tokens out each | $0.98 | $2.10 | $11.00 |
Classify 50,000 support tickets ~150 tokens in, ~20 tokens out each | $0.58 | $1.22 | $6.43 |
Estimates based on published per-token prices. Actual costs vary with prompt length and output verbosity.See live pricing →
Input cost per 1M tokens · sorted lowest first · updated daily
| Model | Provider | Input /1M | Output /1M | Speed | Best for |
|---|---|---|---|---|---|
| Llama 3.2 1B InstructCheapest | Meta | $0.027 | $0.200 | Very fast | Ultra-low-cost text classification, simple Q&A, and high-volume automation pipelines where cost per token is critical. |
| Mistral Nemo | Mistral | $0.029 | $0.030 | Fast | Teams needing a cheap, fast, multilingual workhorse for classification, summarization, or light coding tasks at scale. |
| Gemma 2 9B | $0.030 | $0.090 | Very fast | Lightweight text tasks, classification, and summarization where cost matters more than frontier-level quality. | |
| Llama 3.1 8B Instruct | Meta | $0.050 | $0.080 | Very fast | High-throughput applications where cost and speed matter more than frontier-level quality, such as chatbots, content classification, and text summarization. |
| GPT-5 Nano | OpenAI | $0.050 | $0.400 | Very fast | High-volume, latency-sensitive applications like classification, autocomplete, summarization, and lightweight chat where cost-per-token matters most. |
| gpt-oss-safeguard-20b | OpenAI | $0.070 | $0.200 | Fast | Automated content moderation pipelines and safety classification at scale. |
| Gemini 2.0 Flash Lite | $0.075 | $0.300 | Very fast | High-throughput, cost-sensitive pipelines where speed and price matter more than top-tier reasoning quality. | |
| Mistral Small 3.2 24B | Mistral | $0.075 | $0.200 | Fast | High-volume production workloads where cost matters but quality can't be sacrificed entirely — especially code generation and structured output tasks. |
NO CODE REQUIRED
These tools connect to the same underlying AI models — no programming needed
7,000+ app integrations. Native AI steps for OpenAI, Anthropic, and Google. Easiest starting point.
Visual workflow builder with AI modules. More powerful than Zapier for complex branching logic.
Open-source, self-hostable. Has OpenAI and Anthropic nodes. Free to run on your own server.
No-code app builder with API connector. Build a full web app that calls AI APIs without writing backend code.
DEVELOPER QUICKSTART
DeepSeek V3 is fully OpenAI-compatible — just swap the base URL. Works with the standard OpenAI SDK in any language.
JAVASCRIPT / NODE
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: process.env.DEEPSEEK_API_KEY,
baseURL: 'https://api.deepseek.com/v1',
});
const reply = await client.chat.completions.create({
model: 'deepseek-chat',
messages: [{ role: 'user', content: 'Your prompt here' }],
});
console.log(reply.choices[0].message.content);
// ~$0.07/1M input tokensPYTHON
from openai import OpenAI
client = OpenAI(
api_key="your-deepseek-key",
base_url="https://api.deepseek.com/v1",
)
reply = client.chat.completions.create(
model="deepseek-chat",
messages=[{"role": "user", "content": "Your prompt"}],
)
print(reply.choices[0].message.content)
# ~$0.07/1M input tokensAn API is a way to talk to an AI model from your own app, website, or automation tool — instead of using a chat interface like ChatGPT. You send a message (text in), get a reply (text out), and pay only for what you use. Think of it like a phone line to the AI's brain: you dial in with your question, get the answer, and hang up. You're charged per 'token' (roughly 0.75 words), not per month.
DeepSeek V3 is the cheapest capable AI API at $0.07/1M input tokens. Gemini Flash is close behind at $0.075/1M. Both handle writing, summarisation, classification, and coding well enough for most production use cases. At these prices, 1 million tokens costs about the same as a cup of coffee.
No. Tools like Zapier, Make.com, and n8n let you connect to the same AI APIs with no code at all — through a visual drag-and-drop interface. You can build automations like 'when I get a customer email, summarize it and draft a reply' without writing a single line of code.
With DeepSeek V3 (assuming ~500 tokens in, ~400 tokens out per request): about $0.15 total. With GPT-4o Mini: about $0.32. With GPT-4o: about $1.65. Most real-world automations cost pennies or fractions of a cent per run at the cheap tier.
DeepSeek is a Chinese company. For business use cases involving sensitive customer data or regulated industries (healthcare, finance, legal), sticking with US-based providers (OpenAI, Anthropic, Google) is the safer default. For non-sensitive content generation, summarisation, or translation, DeepSeek V3's quality and price are hard to beat.
A subscription ($20/mo ChatGPT Plus, $20/mo Claude Pro) gives you a chat interface with a monthly flat fee and usage limits. An API is pay-as-you-go and lets you embed AI into your own tools, apps, or automations. Subscriptions are better for daily personal use; APIs are better for building something or automating workflows.
DeepSeek V3 ($0.07/1M) handles code generation surprisingly well for its price. Gemini Flash ($0.075/1M) is comparable. For interactive coding where you want more reliability, Claude Sonnet 4.6 at $3/1M is the best mid-tier value — it scores highest on SWE-bench among non-premium models.
Yes. Zapier has native OpenAI and Anthropic integrations that use the same underlying models. Make.com also supports OpenAI, Anthropic, and Google AI modules. Many cheap models (including DeepSeek V3) are OpenAI-compatible, so they work with any tool that supports the OpenAI API format.
Google Gemini has a free API tier (rate-limited). OpenAI and Anthropic do not offer free tiers on their production APIs, but both have free consumer apps (ChatGPT free, Claude.ai free) for personal use. For testing and prototyping, Gemini's free tier is the best starting point.
Upgrade when the cost of bad outputs exceeds the cost of better tokens. Signs: your cheap model is hallucinating in customer-facing workflows, requiring frequent human correction, or producing output that's damaging your brand. A model 10× more expensive but 30% more accurate often costs less overall when you factor in correction time.