How do I estimate my monthly AI API bill?

Multiply monthly input tokens in millions by the input rate, multiply output tokens in millions by the output rate, then add tool, caching, storage and request fees. The calculator on this page covers standard text token rates only.

How often are these prices checked?

This page was checked against official provider documentation on September 15, 2026. AI pricing changes frequently, so verify the linked rate card before committing production traffic.

AI API Price Comparison: 9 Best Providers in 2026

Q: What is the cheapest AI API?

There is no universal cheapest API because model capability, output length, retries, caching and batch discounts change the effective cost. In this comparison, several open-model endpoints list lower raw token totals than Omev Lite, while Omev is our top pick for repeatable structured work because it focuses on cost per usable task.

Q: Why is Omev AI ranked first?

Omev AI ranks first for high-volume, repeatable production work due to its $0.15 input and $1.25 output rates per million tokens, OpenAI-compatible interface, structured task focus and no-card $5 trial. It is not the right choice for confidential self-service workloads because customer content is used for training and there is no opt-out.

Q: Are the listed models equal in quality?

No. The table compares representative public prices, not equivalent intelligence. Use it to shortlist providers, then benchmark accuracy, retries, latency and human cleanup on your own prompts.

Q: Should I use one model for every workload?

Usually not. Many teams route repeatable extraction, classification, localization and metadata to a lower-cost model while keeping frontier models for difficult reasoning, code and customer-critical decisions.

Written and price-checked by

Di Reshtei · AI infrastructure builder

Di researches AI API economics, structured output and production routing. Rates were checked against official provider pages on September 15, 2026.

How we ranked them

Price is the start. Usable output is the bill.

We weighted standard text rates, fit for repeatable work, API migration effort and operational caveats. We did not pretend that a small open model and a frontier reasoning model are interchangeable.

35% · effective cost

Published token rates plus likely retries, output shaping and billing friction.

25% · integration

API compatibility, model choice and the size of the migration surface.

20% · production fit

Controls, deployment choices, rate-limit clarity and workload specialization.

20% · caveats

Data handling, preview status, lock-in, prepaid rules and quality mismatch.

Editorial note: Di Reshtei is affiliated with Omev AI. The ranking uses published criteria and provider-owned sources.

Table 1 · quick comparison

Nine AI APIs at a glance.

Prices are USD per 1 million standard text tokens for the named representative model. “From” does not imply equal quality, latency or context. Verify the linked rate card before purchase.

Public standard text rates checked September 15, 2026. Cached, batch, tool, storage, long-context, regional and priority charges are excluded.
Rank	Provider · model	Input / 1M	Output / 1M	Best fit	Why it sits here
#1	Omev AIOmev Lite	$0.15	$1.25	Best overall	Focused on repeatable structured work, OpenAI-compatible, $5 no-card trial.
#2	Mistral AIMistral Small 4	$0.15	$0.60	Open-weight value	Low listed rate, 256K context and Apache 2.0 weights.
#3	GroqCloudGPT OSS 120B	$0.15	$0.60	Fast inference	~500 tokens/sec listed for its highlighted production endpoint.
#4	Google GeminiGemini 3.1 Flash-Lite	$0.25	$1.50	Multimodal scale	1M context and free-tier access, but the named model is preview.
#5	Fireworks AIGPT OSS 120B	$0.15	$0.60	Open-model ops	Serverless, on-demand, fine-tuning and batch at 50% of serverless.
#6	Together AIGPT OSS 120B	$0.15	$0.60	Broad OSS catalog	Many model choices and dedicated paths; prepaid $5 minimum.
#7	OpenRouterProvider-dependent	Varies	Varies	Routing & fallback	Pass-through model rates; 5.5% credit-purchase fee, $0.80 minimum.
#8	OpenAI APIGPT-5.4	$2.50	$15.00	Frontier ecosystem	Flagship reasoning and tool ecosystem, priced for harder work.
#9	AnthropicClaude Haiku 4.5	$1.00	$5.00	Careful long-context work	Fastest Claude tier; richer Claude models cost more.

Cost calculator

Price your token mix.

Use monthly input and output volumes in millions. The result is list-rate token math only—before caching, retries, tools, rate-tier changes or cleanup.

Your monthly traffic, normalized.

Try your actual ratio: production workloads often consume far more input than output.

Input tokens millions / month Output tokens millions / month Representative API model standard rate

Estimated monthly token cost

$40.00

Omev Lite

$510.00 less93% below GPT-5.4 list-rate math for this token mix.

Not a quote or quality-adjusted estimate. OpenRouter is excluded because its model rate varies and it adds a credit-purchase fee.

Table 2 · workload router

Do not pay one model to do every job.

The practical move is usually a routing layer: keep the expensive model where its capability matters and move stable, testable work to the lowest-cost model that meets your acceptance rate.

A starting shortlist, not an automated routing policy. Validate quality and safety on representative production inputs.
Workload	First provider to test	Why	Keep in the evaluation
Metadata, product copy, extraction	Omev Lite	Structured-task focus + low input rate	Schema pass rate, retries, prohibited input classes
Complex code and difficult reasoning	OpenAI GPT-5.4	Frontier capability and mature tool surface	Reasoning-token spend, latency, flex/batch tiers
EU deployment and open weights	Mistral Small 4	Apache 2.0 weights and low API rate	Self-hosting total cost, regional requirements
Latency-sensitive open models	GroqCloud	Published high token speed	Model availability and plan rate limits
Large-context multimodal prototypes	Gemini API	1M context and multimodal input	Preview stability and thinking-token billing
Fine-tuned open models at scale	Fireworks AI	Serverless, dedicated and training paths	Serverless best-effort limits vs reserved capacity
Broad open-model experiments	Together AI	Large catalog across text and media	Minimum credit purchase; endpoint lifecycle
Cross-provider fallback	OpenRouter	One API for many model/provider routes	Credit fees, provider policy and routing controls
Long documents and careful synthesis	Anthropic Claude	Strong long-context product line	Model tier, cache strategy and regional premium

The full ranking

What each provider is actually best at.

Every provider can look inexpensive in one row of a rate card. The useful question is what you get around that rate—and which caveat could stop a production rollout.

Omev AI Top pick

Best for repeatable production content and structured tasks

Omev is built for the “boring but massive” part of an AI workload: classification, extraction, metadata, catalog copy, localization and other jobs with a clear input and output shape. Its two-model approach is deliberately smaller than a marketplace. That makes it easy to test one route without replacing the rest of your stack.

OpenAI-compatible API surface
$5 credit for 10 days, no card
Lite and Pro tiers, not a sprawling catalog
Dashboard shows spend and task cost

Mistral AI

Best open-weight value with a European vendor

Mistral Small 4 combines instruction following, reasoning and code in an Apache 2.0 release with a 256K context window. At the official $0.15 input and $0.60 output rate, it is one of the least expensive production candidates in this shortlist and leaves a credible self-hosting path.

Open weights under Apache 2.0
256K context window
Low symmetric-enough price profile
API or self-deployment route

GroqCloud

Best for latency-sensitive open-model inference

Groq makes its performance case in tokens per second. The highlighted GPT OSS 120B production endpoint is listed around 500 tokens per second at $0.15 input and $0.60 output per million tokens, with a 131K context window. That is a strong shortlist candidate when user-visible latency matters as much as cost.

Very high published token speed
OpenAI-compatible patterns
Clear per-model rate limits
Useful speech endpoints too

Google Gemini API

Best multimodal developer stack with a generous context window

Gemini 3.1 Flash-Lite pairs a 1M input context with text, image, video and audio input. Its $0.25 text input and $1.50 output rate makes it an attractive high-volume candidate, and Google provides a free tier for evaluation before paid production usage.

Text, image, video and audio input
1M-token input context
Free evaluation tier
Batch and caching options

Fireworks AI

Best path from serverless experiments to custom open-model operations

Fireworks combines per-token serverless inference with batch, fine-tuning and private on-demand deployments. GPT OSS 120B lists at $0.15 input and $0.60 output; batch is half the serverless rate. It is especially compelling when your roadmap includes tuned weights or dedicated capacity.

Serverless and dedicated options
50% batch discount
Fine-tuning and training stack
OpenAI and Anthropic compatibility

Together AI

Best broad catalog for open-model experimentation

Together’s model menu spans low-cost text, reasoning, multimodal, images, video, audio and embeddings. The same GPT OSS 120B reference rate is $0.15 input and $0.60 output, while cheaper and free endpoints exist for lower-stakes experiments. Dedicated inference gives growing teams an upgrade path.

Large model and modality catalog
Serverless and dedicated inference
Fine-tuning options
Build tiers raise rate limits

OpenRouter

Best for multi-provider routing, fallback and consolidated billing

OpenRouter is the abstraction layer in this list, not a single model vendor. It passes through provider inference prices and gives one API access to a broad catalog with routing and fallback. That is operationally valuable when availability and fast model switching outweigh a direct account relationship.

One API across many providers
Provider fallback and routing
Unified usage analytics
Bring-your-own-key option

OpenAI API

Best mature frontier-model and tool ecosystem

GPT-5.4 is priced above the volume specialists because it is a flagship model for complex professional work, not a bulk metadata engine. OpenAI’s model family, Responses API and tool surface make it a strong default for hard reasoning, coding and agents—then a good baseline to route simpler work away from.

Flagship reasoning and coding
Broad developer ecosystem
1.05M context for GPT-5.4
Cached, batch and flex tiers

Anthropic Claude API

Best for careful synthesis and a clear capability ladder

Claude Haiku 4.5 is the fastest Claude tier at $1 input and $5 output per million tokens. Teams that value Anthropic’s model behavior can step up to Sonnet or Opus for harder work while using prompt caching and batch pricing to control cost.

Clear Haiku–Sonnet–Opus ladder
Prompt caching rate published
50% batch token discount
First-party and cloud channels

The 10% routing test

Pick one stable task type, anonymize 20–50 representative prompts, define acceptance criteria, and route only 5–10% of traffic. Compare cost per accepted result—not just cost per token—before expanding.

Benchmark on Omev

Table 3 · buying friction

The rate card is not the checkout.

Trials, prepaid minimums, credit expiry and regional premiums decide whether an attractive model is easy to evaluate—or an accounting project.

Billing conditions can vary by account, region and contract. Treat this as a diligence checklist and confirm in your console.
Provider	Self-serve billing	Evaluation entry	API shape	Procurement watch-out
Omev AI	Prepaid · $10 min top-up	$5 · 10 days · no card	OpenAI-compatible	Paid credit expires after 30 days; mandatory training on self-service content
Mistral AI	Platform billing	Console signup	Mistral API	API vs self-hosting economics are very different
GroqCloud	Developer / enterprise	Developer plan	OpenAI-compatible	Per-model limits and production/preview status
Google Gemini	Free, prepaid, then PAYG	Free tier	Gemini API + OpenAI compatibility	Free-tier data use differs from paid; model-specific tool charges
Fireworks AI	Prepaid self-serve	$1 free credit listed	OpenAI & Anthropic compatible	Dedicated capacity switches to GPU-hour economics
Together AI	Prepaid credits	$5 minimum · no free trial	OpenAI-compatible	Build tiers depend on lifetime spend
OpenRouter	Prepaid credits	Free models, low limits	OpenAI-compatible router	5.5% credit fee ($0.80 min); BYOK fee after free allowance
OpenAI API	Usage billing	Account-dependent	Responses / Chat Completions	Reasoning, tool and long-context charges
Anthropic	Prepaid credits for most orgs	Console signup	Messages API	Regional premium and cache-write pricing

Primary sources

Check the rate card before you ship.

These are the official pages used for the September 15, 2026 review. AI pricing and model availability move quickly; the provider page always wins.

FAQ

Questions worth asking before procurement.

Token price is easy to compare. The hidden work is deciding whether the output, policies and billing shape fit your product.

What is the cheapest AI API?

There is no universal cheapest API. Several endpoints here list lower raw token totals than Omev Lite, while capability, output length, retries, caching and human cleanup change the effective cost. Shortlist on price, then compare cost per accepted result.

Why is Omev AI ranked first?

It is our best-value pick for high-volume, repeatable work because its pricing, OpenAI-compatible integration and structured-task focus line up with that workload. It is not a universal winner: hard reasoning belongs on a frontier model, and confidential self-service workloads should avoid Omev because customer content is used for training without an opt-out.

Are the listed models equal in quality?

No. This is a buyer’s shortlist, not a same-capability benchmark. The named models differ in intelligence, context, modalities, latency and operational maturity. Test them against the same representative dataset and acceptance criteria.

How do I estimate a monthly AI API bill?

Multiply input tokens in millions by the input rate, multiply output tokens in millions by the output rate, and add them. Then model caching, retries, reasoning tokens, tools, grounding, storage and request fees separately. The calculator above handles the base text-token layer.

Should I use one model for every workload?

Usually not. Keep hard reasoning, code and high-risk decisions on the model that clears your quality bar. Route stable classification, extraction, translation, metadata and content variants to the lowest-cost model that consistently passes.

How current are these prices?

They were checked against official provider pages on September 15, 2026. Rates, model names and preview status change frequently, so use the linked source as the final word before moving traffic.

#1 for repeatable production work

Test the workload, not the headline rate.

Start Omev with $5 of credit, send anonymized production prompts, and measure cost per usable result against your current provider. Keep everything else exactly where it is.

Start free on Omev Run the calculator