Models

Mesh API routes to models across multiple upstream providers. Models are identified by a provider/model-name slug — the same format used in all inference requests.

Looking for the full catalog? Available Models 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

<provider>/<model-name>

Examples:

Model ID	Provider	Notes
`openai/gpt-4o`	OpenAI	GPT-4o flagship
`openai/gpt-4o-mini`	OpenAI	Fast, cheap
`anthropic/claude-opus-4-8`	OpenRouter → Anthropic	Via OpenRouter
`anthropic/claude-haiku-4.5`	OpenRouter → Anthropic	Fastest Claude
`google/gemini-pro-1.5`	OpenRouter → Google	Long context
`meta-llama/llama-3.3-70b-instruct`	OpenRouter	Open weights
`bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0`	AWS Bedrock	Native Bedrock
`vertex/gemini-1.5-pro-002`	Google Vertex AI	Native Vertex
`sarvam/bulbul:v3`	Sarvam	Indian TTS

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`
`provider`	string	Filter by upstream provider: `amazon-bedrock`, `vertex`, `openai`

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/search`	Search the catalog by name, ID, or description

Choosing a model

By task type

Task	Recommended models
General chat	`openai/gpt-4o-mini`, `anthropic/claude-haiku-4.5`
Complex reasoning	`openai/gpt-4o`, `anthropic/claude-opus-4-8`
Long documents	`google/gemini-pro-1.5` (1M context)
Code generation	`openai/gpt-4o`, `meta-llama/llama-3.3-70b-instruct`
Embeddings	`openai/text-embedding-3-small`, `bedrock/amazon.titan-embed-text-v2:0`
Text to speech	`openai/tts-1`, `sarvam/bulbul:v3` (Indian languages)
Image generation	`openai/gpt-image-1-mini`, `openai/dall-e-3`

By cost

Free models (is_free: true) cost $0 for both prompt and completion tokens. Check the Dashboard → Models tab to filter for free models by provider. 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`, or `video`
`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_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_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`
`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

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

Each model is backed by one upstream provider. The provider determines authentication, latency, and regional availability:

Provider slug	Upstream
`openrouter`	OpenRouter (aggregator — proxies Anthropic, Meta, Mistral, etc.)
`openai`	OpenAI direct
`bedrock`	AWS Bedrock
`vertex`	Google Vertex AI
`qwen`	Alibaba Cloud DashScope
`sarvam`	Sarvam AI
`byteplus`	BytePlus (video)

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 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