Models

Mesh API routes to models across multiple upstream providers. Models are identified by a brand/model-name slug, the same format used in all inference requests. The brand is the organization that trained the model, not the provider that serves it.

Looking for the full catalog? Models & Pricing lists every model Mesh can route to today, with live pricing and context lengths.

What a model is

Mesh acts as a router, forwarding your standardized API calls to an expansive list of underlying foundational models. A model is a distinct neural network trained by an AI organization (OpenAI, Google, Anthropic, Meta, and others). Each model handles a different maximum context length — the number of tokens it can process in a single request. Fast, small models may have smaller limits but respond almost instantly; large models can handle whole documents and are optimized for reasoning, at higher latency and cost. When choosing one, weigh three things:

Cost — do you need high intelligence, or just rapid categorization?
Latency — lighter models offer much lower time-to-first-token.
Context length — passing an entire codebase or large PDF needs a long-context model.

Model ID format

<brand>/<model-name>

Examples:

Model ID	Brand	Notes
`openai/gpt-5.5`	OpenAI	GPT flagship
`openai/gpt-4o-mini`	OpenAI	Fast, cheap
`anthropic/claude-opus-5.5`	Anthropic	Claude flagship
`anthropic/claude-haiku-4.5`	Anthropic	Fastest Claude
`google/gemini-3.1-pro`	Google	Long context
`meta-llama/llama-3.3-70b-instruct`	Meta	Open weights
`sarvam/bulbul:v3`	Sarvam	Indian TTS

There are no provider-specific IDs such as bedrock/... or vertex/...: one ID covers every provider that serves the model, and routing picks the provider. See Provider routing.

Listing available models

curl https://api.meshapi.ai/v1/models \
  -H "Authorization: Bearer rsk_YOUR_KEY"

The response is a JSON array of enabled models with pricing:

[
  {
    "id": "openai/gpt-4o-mini",
    "name": "GPT-4o-mini",
    "brand": "openai",
    "model_type": "text",
    "context_length": 128000,
    "is_free": false,
    "input_modalities": ["text"],
    "output_modalities": ["text"],
    "supports_tools": true,
    "supports_embeddings": false,
    "supports_realtime": false,
    "supports_structured_output": true,
    "supports_system_prompt": true,
    "supports_batching": false,
    "supports_thinking": false,
    "supports_completions_api": true,
    "supports_responses_api": true,
    "pricing": {
      "pricing_unit": "per_1m_tokens",
      "prompt_usd_per_1m": "0.15000000",
      "completion_usd_per_1m": "0.60000000",
      "input_usd_per_unit": "0.1500000000",
      "output_usd_per_unit": "0.6000000000",
      "cache_read_input_usd_per_1m": "0.07500000",
      "effective_date": "2026-04-14",
      "discount_pct": null
    }
  }
]

The pricing object carries a field per billing dimension the model supports — cache read/write, long context, batch, audio, per-image, and a flat request_usd where one applies. Dimensions the model does not bill for are null. See Pricing for how the units work.

Query parameters

Parameter	Type	Description
`free`	boolean	`true` = free models only, `false` = paid only, omit = all
`type`	string	Filter by model type: `text`, `embedding`, `image`, `audio`, `video`, `evaluation`. `tts` and `stt` models cannot be selected with this filter; read `model_type` instead
`provider`	string	Filter by provider slug, e.g. `openai`, `vertex`, `fireworks`, `deepseek` (`amazon-bedrock` and `azure-foundry` are accepted as aliases)

Additional endpoints

Endpoint	Description
`GET /v1/models/{model_id}`	Returns a single enabled model by its full model ID (e.g. `openai/gpt-4o`)
`GET /v1/models/{model_id}/providers`	Every provider that can serve the model, each with its own price and capabilities
`GET /v1/models/search`	Search the catalog by name, ID, or description

The catalog is also readable without a key, at list price: GET /v1/public/models, GET /v1/public/models/{model_id}, GET /v1/public/models/{model_id}/providers, and GET /v1/public/models/search, rate-limited per IP. GET /v1/public/brands returns brand and provider display names and logos.

Choosing a model

By task type

Task	Recommended models
General chat	`openai/gpt-4o-mini`, `anthropic/claude-haiku-4.5`
Complex reasoning	`openai/gpt-5.5`, `anthropic/claude-opus-5.5`
Long documents	`google/gemini-3.1-pro` (1M context), `google/gemini-3.5-flash`
Code generation	`openai/gpt-4o`, `meta-llama/llama-3.3-70b-instruct`
Embeddings	`openai/text-embedding-3-small`, `cohere/embed-v4`
Text to speech	`google/gemini-3.1-flash-tts`, `sarvam/bulbul:v3` (Indian languages)
Image generation	`openai/gpt-image-1-mini`, `openai/gpt-image-2`

By cost

Free models (is_free: true) cost $0 for both prompt and completion tokens. They are rare: the moderation model openai/omni-moderation-latest is currently the only one. Check GET /v1/models?free=true rather than planning around them. Paid model pricing varies widely — a frontier reasoning model may cost 100× more per token than a lightweight model. Check pricing.prompt_usd_per_1m and pricing.completion_usd_per_1m in the API response for live pricing.

Let the gateway decide

Set "model": "auto" and the gateway classifies your prompt and picks an appropriate model automatically. See Auto Routing.

Model capabilities

Field	Type	Meaning
`id`	string	Full model ID, `brand/model-name`
`brand`	string	The organization that trained the model, e.g. `openai`, `anthropic`
`context_length`	integer	Maximum combined prompt + completion tokens
`model_type`	string	`text`, `embedding`, `image`, `audio`, `tts`, `stt`, `video`, or `evaluation`
`input_modalities`	string[]	Accepted input types (e.g. `["text", "image"]`)
`output_modalities`	string[]	Produced output types (e.g. `["text"]`)
`supports_tools`	boolean	Supports tool/function calling
`supports_embeddings`	boolean	Can produce embedding vectors
`supports_realtime`	boolean	Supports WebSocket realtime sessions
`supports_structured_output`	boolean	Supports JSON schema-constrained output
`supports_system_prompt`	boolean	Accepts a system message
`supports_batching`	boolean	Eligible for async batch requests
`supports_flex`	boolean	Can be served on the `flex` service tier
`supports_thinking`	boolean	Exposes chain-of-thought reasoning tokens
`supports_completions_api`	boolean	Compatible with `/v1/chat/completions`
`supports_responses_api`	boolean	Compatible with `/v1/responses`
`supports_video_generation`	boolean	Can generate video
`supports_video_*`	boolean	One flag per kind of input a video model accepts — `first_frame`, `last_frame`, `reference_image`, `reference_video`, `reference_audio` — plus `negative_prompt` for the parameter of that name. Read them before sending an input a model may not take: see Video Generation
`supports_background_response`	boolean	Eligible for `background: true` on `/v1/responses`
`supports_image_*`	boolean	Image edit capabilities — `edit`, `inpaint`, `outpaint`, `mix`, `reframe`, `upscale`, `reference`, `remove_background`
`image_operations`	string[]	The image operations a request can actually use on this model. Prefer it over the `supports_image_*` flags, which can be set for an operation the serving provider rejects with `422`
`supports_generate_audio`	boolean \| null	Whether a video model can generate an audio track
`max_prompt_chars`	integer \| null	Longest prompt the provider accepts; `null` means no limit is recorded, not that there is none
`context_window` / `standard_context_threshold`	integer \| null	The provider’s context window, and the prompt size above which long-context pricing applies (`null` = no long-context tier)
`realtime_session_max_tokens` / `realtime_max_concurrent_per_owner`	integer \| null	Per-session token cap and concurrent-session limit for realtime models
`is_composite` / `composite_models`	boolean / string[]	Whether the entry fans out to several underlying models, and which
`is_free`	boolean	$0 cost for all tokens
`deprecation`	object \| null	Set when the model is deprecated: `deprecated_on`, `sunset_on` (the announced end date, `null` until announced), and `replacement_model_id`. The model stays usable while deprecated

supports_system_prompt defaults to true. Check the relevant flag before sending a request that depends on a specific capability — an unsupported feature is generally rejected by the upstream rather than silently downgraded.

Provider routing

A model ID is not tied to one upstream. Many models are served by several providers; anthropic/claude-sonnet-4.5, for example, runs on Anthropic, AWS Bedrock, and others. Resilient routing can fall back between them when one fails. GET /v1/models and GET /v1/models/{model_id} show the price a bare model ID bills at; GET /v1/models/{model_id}/providers lists every provider that can serve the model, alphabetically, each at its own price. Which provider is the default is not published, so do not depend on a specific one. Provider slugs (openai, bedrock, vertex, azure_foundry, fireworks, together, and others) appear in the provider filter above, in /providers rows, and in BYOK; GET /v1/public/brands lists them all with display names.

The model registry is live — models can be enabled or disabled by the platform team. Always use GET /v1/models at runtime rather than hardcoding a static model list.

Introduction

Accounts & Access

Core Inference

Retrieval & Search

Multimodal

Operations

Mesh Code

Mesh CLI

Platform

Reference

What a model is

Model ID format

Listing available models

Query parameters

Additional endpoints

Choosing a model

By task type

By cost

Let the gateway decide

Model capabilities

Provider routing

​What a model is

​Model ID format

​Listing available models

​Query parameters

​Additional endpoints

​Choosing a model

​By task type

​By cost

​Let the gateway decide

​Model capabilities

​Provider routing

What a model is

Model ID format

Listing available models

Query parameters

Additional endpoints

Choosing a model

By task type

By cost

Let the gateway decide

Model capabilities

Provider routing