Models & pricing

One API, many models. The catalogue at https://console.mirapi.ai lists 200+ models from multiple vendors, and you call any of them through the same endpoints — for chat, you only change the model field. The catalogue is also an API, so you can browse and filter it programmatically.

Browsing the catalogue

GET /v1/models returns every entry, and a Gemini-compatible list is available at /v1beta/models:

# OpenAI-compatible
curl https://api.mirapi.ai/v1/models \
  -H "Authorization: Bearer $MIRAPI_API_KEY"

# Gemini-compatible
curl "https://api.mirapi.ai/v1beta/models" \
  -H "x-goog-api-key: $MIRAPI_API_KEY"

The list accepts Authorization: Bearer (the scheme is case-insensitive, and a bare key without the scheme also works). On /v1/models you can use x-api-key instead; the Gemini variant accepts x-goog-api-key or a ?key= query parameter.

Each entry carries the fields you need to choose:

Field	What it tells you
id / name	The exact name to send in requests
context_length	Maximum context window, in tokens
pricing	USD per 1M tokens — input / output / cache read
supported_parameters	Which request features the model supports (tools, vision, reasoning, …)
output_modalities	What the model can produce: text, image, video, audio, embeddings

Entries fall into two classes:

• Available — MirAPI operates a channel today; the card shows real channel pricing and you can call it now.
• Coming soon — listed with the vendor’s official pricing, but no channel yet. You can’t call it until it flips to available.

Choosing a model

Start from what the task needs:

1. Capabilities first — does it need tool calling, vision input, reasoning, or JSON output? Filter by those.
2. Context window — long documents or large codebases need a larger window.
3. Price — compare input/output per-1M-token prices; the model detail page shows the exact numbers.
4. Send the exact id the catalogue returns — model names are passed through verbatim.

The console supports filtering by context size, capabilities, vendor, series, and output type, so you can narrow hundreds of models to a shortlist in seconds.

Model names

Call models by the name the catalogue returns — for example deepseek-chat. That string is passed through verbatim.

The catalogue also displays a browsing ID with a vendor/ prefix (for example deepseek/deepseek-chat). The prefix is only used for browsing and filtering in the console — it is not part of an API request. When in doubt, copy the exact name from the model card.

Capabilities

supported_parameters tells you which request features a model accepts. The common ones, and what they unlock:

Capability	What it enables
Tool calling	Send tools / tool_choice so the model can call your functions
Vision input	Pass images via image_url (HTTP(S) URL or base64 data URI)
Reasoning	Control effort with reasoning_effort; reasoning tokens are billed as output
Structured output	Use response_format (json_schema or JSON mode) for guaranteed JSON
Prompt caching	OpenAI-compatible models cache automatically; Anthropic uses cache_control
Web search	The model must be marked as web-search capable in the catalogue

output_modalities lists what the model returns — text, image, video, audio, or embeddings — so pick a model whose output matches your task.

Pricing

For text and multimodal models, price is quoted per 1M tokens in three tiers:

Tier	What it covers
Input	Tokens in the request
Cache read	Tokens served from prompt cache — cheaper than fresh input; enable it per Prompt caching
Output	Generated tokens, including reasoning/thinking tokens

Image generation is billed per image and video generation per second of output. Catalogue prices are in USD and are the authoritative source; this page describes the mechanism rather than fixed numbers.

Billing runs on a prepaid USD balance that never expires — no subscription, no minimum spend. When the balance runs out, requests return 403 and the same key works again immediately after you top up. See Billing for reconciling usage.

Discount badges

A model card may carry a discount badge (for example “up to X% off”). It compares MirAPI’s combined input+output price against the vendor’s official list price for the same model. The badge is a price comparison, not a quality claim — the model and its output are identical.

Channels and failover

Each available model can be served by several channels (different upstream routes). The displayed price is the model’s real channel price.

MirAPI routes each request to a healthy channel and steers around degraded ones automatically — you don’t configure failover. If every channel for a model is down, the request fails with a 5xx rather than silently substituting a different model — there is no model-level fallback.

Key whitelists

A key can be restricted to a whitelist of models at creation time. A whitelisted key calling a model outside the list gets 403 even though the key itself is valid. Keys can also carry a validity period, a quota cap, and an IP allowlist — see Authentication.

Troubleshooting

Status	Meaning	What to do
401	Key missing, invalid, or unknown	Check the key; see Authentication
403	Key valid but rejected — balance, whitelist, quota, or IP	Fix the cause; top up if the balance is empty
413	Payload too large	Reduce the request size
429	Rate limited (no Retry-After header)	Retry with jittered exponential backoff (1s → 2s → 4s, capped ~30s)
5xx	Upstream or channel failure	Retry idempotent requests; attach the request ID from the error to any ticket

Every error message ends with a request ID — include it when you open a support ticket. Full error shapes are in Errors.

Related links

• Billing
• OpenAI compatibility
• Prompt caching
• Authentication