Cheapest AI API 2026: NanoGPT vs OpenRouter vs Direct
i spent a weekend in april tracking every API call across three different providers. openai direct, anthropic direct, and google direct. separate API keys, separate billing, separate dashboards. by the time i'd set up monitoring for all three, i realized the overhead alone was costing me more than the actual tokens.
tl;dr: Per-token pricing is similar across direct providers, NanoGPT, and OpenRouter, but NanoGPT saves money through unified billing with one account and one deposit. For a typical developer using 5M input and 2M output tokens monthly, costs are around $29 across all three approaches. NanoGPT's real advantage is convenience: one API key, one balance, and the ability to switch between 50+ models without managing multiple accounts.
key takeaways:
- Per-token pricing is nearly identical across OpenAI direct, NanoGPT, and OpenRouter for equivalent models.
- NanoGPT's savings come from unified billing with one account, one deposit, and one API key instead of managing three separate provider accounts.
- For most developers, NanoGPT or OpenRouter offer better value than going direct unless you process over 100 million tokens per month.
there are three main ways to access AI APIs in 2026: go direct to the provider, use a router like OpenRouter, or use NanoGPT. the price differences are bigger than you'd expect - but not always where you'd expect them.
how API pricing actually works
short answer: AI API pricing is per-token with input and output priced separately, output tokens costing 3-4 times more, plus hidden costs from minimum charges and separate billing.
before comparing prices, you need to understand the mechanics:
per-token pricing:
- you pay per token (roughly 4 characters = 1 token)
- input tokens (your prompt) and output tokens (AI response) are priced differently
- output tokens are usually 3-4x more expensive than input tokens
the hidden costs:
- minimum charges per provider
- rate limits that force you to upgrade
- separate billing for each provider
- no volume discounts at small scale
if you're using multiple models (GPT-4o for coding, Claude for writing, Gemini for research), going direct means managing 3+ API accounts with separate billing. that's where routers like nanoGPT and openrouter simplify things.
the price comparison
short answer: GPT-4o costs $2.50 per million input tokens and $10.00 per million output tokens across OpenAI direct, NanoGPT, and OpenRouter.
GPT-4o pricing (per 1M tokens)
short answer: GPT-4o costs $2.50 per million input tokens and $10.00 per million output tokens across all three provider options.
| Provider | Input | Output | Minimum | Notes |
|---|---|---|---|---|
| OpenAI Direct | $2.50 | $10.00 | None | Standard rates |
| NanoGPT | ~$2.50 | ~$10.00 | $8 deposit | Same models, unified billing |
| OpenRouter | $2.50 + fee | $10.00 + fee | $5 deposit | Adds small markup |
Claude 3.5 Sonnet pricing (per 1M tokens)
short answer: Claude 3.5 Sonnet costs $3.00 per million input tokens and $15.00 per million output tokens across Anthropic direct, NanoGPT, and OpenRouter.
| Provider | Input | Output | Minimum | Notes |
|---|---|---|---|---|
| Anthropic Direct | $3.00 | $15.00 | None | Standard rates |
| NanoGPT | ~$3.00 | ~$15.00 | $8 deposit | Same models, unified billing |
| OpenRouter | $3.00 + fee | $15.00 + fee | $5 deposit | Adds markup |
Gemini 1.5 Pro pricing (per 1M tokens)
short answer: Gemini 1.5 Pro costs $1.25 per million input tokens and $5.00 per million output tokens across Google direct, NanoGPT, and OpenRouter.
| Provider | Input | Output | Minimum | Notes |
|---|---|---|---|---|
| Google Direct | $1.25 | $5.00 | None | 128k context |
| NanoGPT | ~$1.25 | ~$5.00 | $8 deposit | Unified billing |
| OpenRouter | $1.25 + fee | $5.00 + fee | $5 deposit | Adds markup |
at first glance, per-token rates look similar. the real savings come from:
- unified billing (one account, one deposit)
- no separate minimum charges per provider
- ability to switch models without changing API keys
- lower overhead for small-scale usage
real-world cost math
short answer: A typical developer using 5M input and 2M output tokens monthly pays about $29 across all three approaches, with savings coming from unified billing.
let's do the math for a typical developer's monthly usage:
usage profile:
- 70% GPT-4o (coding, general tasks)
- 20% Claude 3.5 (writing, analysis)
- 10% Gemini (long document processing)
- total: ~5M input tokens, ~2M output tokens
going direct (3 separate accounts)
short answer: Going direct requires three separate accounts with a combined monthly cost of about $29.88 for the same usage across OpenAI, Anthropic, and Google.
| Provider | Input Cost | Output Cost | Monthly Total |
|---|---|---|---|
| OpenAI (3.5M tokens) | $8.75 | $14.00 | $22.75 |
| Anthropic (1M tokens) | $3.00 | $3.00 | $6.00 |
| Google (0.5M tokens) | $0.63 | $0.50 | $1.13 |
| Total | $12.38 | $17.50 | $29.88 |
using nanogpt
short answer: Using NanoGPT for the same usage costs about $29 per month with unified billing through a single account and deposit.
| Usage | Input Cost | Output Cost | Monthly Total |
|---|---|---|---|
| 5M input + 2M output | ~$12.00 | ~$17.00 | ~$29.00 |
using openrouter
short answer: Using OpenRouter for the same usage costs about $30 or more per month with similar unified billing but a small markup.
| Usage | Input Cost | Output Cost | Monthly Total |
|---|---|---|---|
| 5M input + 2M output | ~$12.50 | ~$17.50 | ~$30.00+ |
at this usage level, per-token costs are similar. the real savings with nanoGPT come from:
- one account instead of three
- one deposit instead of three minimum charges
- one API key instead of three
- flexibility to switch models without changing code
where nanogpt actually saves money
short answer: NanoGPT saves money through unified billing, smaller effective minimums at light usage, and simplified model experimentation with one API key.
the savings become clear in specific scenarios:
scenario 1: mixed model usage
short answer: Mixed model usage saves the most with NanoGPT because you maintain one balance instead of separate balances on three or more services.
if you use multiple models, nanoGPT's unified billing saves overhead. instead of maintaining balances on 3+ services, you maintain one.
savings: administrative overhead + smaller effective minimums
scenario 2: light-to-medium usage
short answer: At light usage levels below 2 million tokens per month, NanoGPT's unified $8 deposit covers usage across all models without separate minimum charges.
at lower usage levels (1-2M tokens/month), minimum charges matter more:
| Provider | Minimum | Effective Rate at 1M tokens |
|---|---|---|
| OpenAI | None | $2.50/$10.00 |
| Anthropic | None | $3.00/$15.00 |
| NanoGPT | $8 deposit | Flexible |
| OpenRouter | $5 deposit | Flexible |
if you only use $3 worth of Anthropic API per month, you still need to maintain an account and billing relationship. with nanoGPT, that $3 comes from your unified balance.
scenario 3: model experimentation
short answer: Testing five models with NanoGPT requires one API key and one balance, while direct APIs would require five separate accounts.
want to test which model works best for your use case? with direct APIs, testing 5 models means 5 accounts. with nanoGPT, it's one API key and one balance.
i tested this: switching between GPT-4o, Claude 3.5, Gemini, and Mistral for different tasks. with nanoGPT, it was a parameter change. with direct APIs, it would have been 4 separate accounts.
API compatibility
short answer: NanoGPT and OpenRouter both use OpenAI-compatible API formats, working with any tool that supports OpenAI's API through a single endpoint.
nanogpt API
short answer: NanoGPT's API uses OpenAI-compatible format with a single API key for all 50+ models and the same request and response format.
- OpenAI-compatible format
- works with any tool that supports OpenAI's API
- single API key for all models
- same request/response format
openrouter API
short answer: OpenRouter's API uses OpenAI-compatible format with slightly different model naming conventions compared to NanoGPT.
- OpenAI-compatible format
- similar to nanoGPT in terms of compatibility
- slightly different model naming conventions
direct APIs
short answer: Direct APIs require separate API keys per provider, though most are now OpenAI-compatible, with provider-specific features like function calling.
- each provider has its own format (though most are OpenAI-compatible now)
- separate API keys per provider
- provider-specific features (function calling, vision, etc.)
if you're building an application that uses multiple models, nanoGPT or openrouter simplify the code significantly. one API endpoint, one authentication method, model selection via parameter.
quality and reliability
short answer: In four months of testing, NanoGPT had zero downtime with latency comparable to going direct, adding less than 100 milliseconds of overhead.
price isn't everything. here's how the services compare in practice:
| Factor | Direct | NanoGPT | OpenRouter |
|---|---|---|---|
| Uptime | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ |
| Latency | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ |
| Model availability | Provider-specific | 50+ models | 100+ models |
| Rate limits | Per provider | Per account | Per account |
| Support | Direct from provider | Via nanoGPT | Via openrouter |
in my 4 months of using nanoGPT, i've had zero downtime and latency is comparable to going direct. the requests go through nanoGPT's servers to the model provider, which adds a tiny amount of latency (usually <100ms).
OpenRouter is similar in quality. the main difference is pricing structure and model availability.
when to go direct
short answer: Going direct makes sense for high-volume usage over 100 million tokens per month, provider-specific features, enterprise SLAs, or single-model applications.
direct API access makes sense for:
high-volume usage (100M+ tokens/month): at massive scale, direct pricing with volume discounts beats any router. but you need to be processing millions of tokens daily for this to matter.
provider-specific features: some features are only available direct:
- OpenAI's function calling with specific configurations
- Anthropic's extended thinking mode
- Google's grounding with search
enterprise requirements: if you need SLAs, compliance documentation, or dedicated support, direct provider relationships are necessary.
single-model applications: if your app only uses GPT-4o, going direct is simpler and potentially cheaper at scale.
for everyone else - and that's most developers - nanoGPT or openrouter offer better value.
my recommendation
short answer: For most developers NanoGPT offers the best value with unified billing and multiple models, while enterprise or high-volume users should go direct.
after testing all three approaches for 4 months:
for most developers: use NanoGPT
- unified billing, multiple models, competitive pricing
- best for mixed-model usage and experimentation
- $8 minimum deposit, pay-per-use after that
for budget-conscious developers: start with nanoGPT, compare with openrouter
- both are good, pricing is similar
- nanoGPT has better crypto payment options
- openrouter has slightly more models
for enterprise/high-volume: go direct
- volume discounts matter at scale
- compliance requirements may dictate provider choice
- direct support is valuable for production applications
Last updated: July 2026
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- NanoGPT vs OpenRouter - detailed comparison
- NanoGPT for Developers - developer-focused guide
- NanoGPT API Tutorial - integration examples
- AI Subscription Fatigue - why pay-per-prompt saves money
- Pay-Per-Prompt vs Subscription - detailed cost math
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