Overview
Concentrate provides access to 160+ models from 21 authors across 21 providers through a single unified API. Use any model slug below in themodel field of your request.
{
"model": "claude-opus-4-8",
"input": "Hello, world!"
}
provider/model format:
{
"model": "anthropic/claude-opus-4-8",
"input": "Hello, world!"
}
Pricing, context windows, and provider availability are kept current in the Model Fortress dashboard. You can also query the List Models endpoint for real-time data.
Models by Author
- OpenAI
- Anthropic
- Google
- xAI
- Meta
- Mistral
- Alibaba
- More
OpenAI (26 models)
Frontier
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
gpt-5.6-sol | GPT 5.6 Sol | openai, azure | 1,050,000 | 128,000 |
gpt-5.6-terra | GPT 5.6 Terra | openai, azure | 1,050,000 | 128,000 |
gpt-5.6-luna | GPT 5.6 Luna | openai, azure | 1,050,000 | 128,000 |
gpt-5.5 | GPT 5.5 | openai, azure | 1,050,000 | 128,000 |
gpt-5.4 | GPT 5.4 | openai, azure | 1,050,000 | 128,000 |
gpt-5.4-mini | GPT 5.4 Mini | openai, azure | 128,000 | 128,000 |
gpt-5.4-nano | GPT 5.4 Nano | openai, azure | 128,000 | 128,000 |
gpt-5.4-pro | GPT 5.4 Pro | openai, azure | 1,050,000 | 128,000 |
gpt-5.2 | GPT 5.2 | openai, azure | 400,000 | 128,000 |
gpt-5.1 | GPT 5.1 | openai, azure | 400,000 | 128,000 |
gpt-5 | GPT 5 | openai, azure | 400,000 | 128,000 |
gpt-5-mini | GPT 5 Mini | openai, azure | 400,000 | 128,000 |
gpt-5-nano | GPT 5 Nano | openai, azure | 400,000 | 128,000 |
Codex (Agentic Coding)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
gpt-5.3-codex | GPT 5.3 Codex | openai, azure | 400,000 | 128,000 |
Reasoning
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
o1 | OpenAI o1 | openai | 200,000 | 100,000 |
o3 | OpenAI o3 | openai | 200,000 | 100,000 |
o3-mini | OpenAI o3-mini | openai | 200,000 | 100,000 |
o4-mini | OpenAI o4-mini | openai | 200,000 | 100,000 |
Previous Generation
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
gpt-4.1 | GPT 4.1 | openai, azure | 1,047,576 | 32,768 |
gpt-4.1-mini | GPT 4.1 Mini | openai, azure | 1,047,576 | 32,768 |
gpt-4o | GPT 4o | openai, azure | 128,000 | 16,384 |
gpt-4o-mini | GPT 4o Mini | openai, azure | 128,000 | 16,384 |
Open-Weight (GPT-OSS)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
gpt-oss-120b | OpenAI gpt-oss 120B | azure, cloudflare, bedrock, bluelobster, fireworks | 131,072 | 128,000 |
gpt-oss-20b | OpenAI gpt-oss 20B | cloudflare, bedrock, bluelobster, fireworks | 131,072 | 128,000 |
gpt-oss-safeguard-120b | OpenAI gpt-oss Safeguard 120B | bedrock | 128,000 | 128,000 |
gpt-oss-safeguard-20b | OpenAI gpt-oss Safeguard 20B | bedrock | 128,000 | 128,000 |
Anthropic (12 models)
Anthropic models support Zero Data Retention when accessed via the Anthropic, Azure, or Bedrock provider, except where noted in the ZDR column.Current Generation
| Model Slug | Name | Providers | Context | Max Output | ZDR |
|---|---|---|---|---|---|
claude-fable-5 | Claude Fable 5 | anthropic, vertex, azure | 1,000,000 | 128,000 | No |
claude-opus-5 | Claude Opus 5 | anthropic, vertex, azure | 1,000,000 | 128,000 | Yes |
claude-sonnet-5 | Claude Sonnet 5 | anthropic, azure, bedrock | 1,000,000 | 128,000 | Yes |
claude-opus-4-8 | Claude Opus 4.8 | anthropic, vertex, azure, bedrock | 1,000,000 | 128,000 | Yes |
claude-opus-4-7 | Claude Opus 4.7 | anthropic, azure, bedrock | 1,000,000 | 128,000 | Yes |
claude-opus-4-6 | Claude Opus 4.6 | anthropic, vertex, azure, bedrock | 200,000 | 128,000 | Yes |
claude-opus-4-5 | Claude Opus 4.5 | anthropic, azure, bedrock | 200,000 | 64,000 | Yes |
claude-sonnet-4-6 | Claude Sonnet 4.6 | anthropic, vertex, azure, bedrock | 200,000 | 64,000 | Yes |
claude-sonnet-4-5 | Claude Sonnet 4.5 | anthropic, azure, bedrock | 200,000 | 64,000 | Yes |
claude-haiku-4-5 | Claude Haiku 4.5 | anthropic, azure, bedrock | 200,000 | 64,000 | Yes |
Previous Generation
| Model Slug | Name | Providers | Context | Max Output | ZDR |
|---|---|---|---|---|---|
claude-opus-4-1 | Claude Opus 4.1 | anthropic, bedrock | 200,000 | 32,000 | Yes |
claude-sonnet-4 | Claude Sonnet 4 | bedrock | 200,000 | 64,000 | Yes |
Google (14 models)
Gemini
Gemini models support Zero Data Retention only when accessed via the Vertex provider — theai-studio provider is not ZDR-certified. A request is only actually zero-data-retention if ZDR is enabled on the API key making it.| Model Slug | Name | Providers | Context | Max Output | ZDR |
|---|---|---|---|---|---|
gemini-3.6-flash | Gemini 3.6 Flash | vertex | 1,048,576 | 65,536 | Yes |
gemini-3.5-flash-lite | Gemini 3.5 Flash Lite | vertex | 1,048,576 | 65,536 | Yes |
gemini-3.5-flash | Gemini 3.5 Flash | vertex, ai-studio | 1,048,576 | 65,536 | Yes (vertex only) |
gemini-3.1-flash-lite-preview | Gemini 3.1 Flash Lite Preview | ai-studio | 1,048,576 | 65,536 | No |
gemini-3.1-pro-preview | Gemini 3.1 Pro Preview | vertex, ai-studio | 1,000,000 | 65,536 | Yes (vertex only) |
gemini-3-flash-preview | Gemini 3 Flash Preview | vertex, ai-studio | 1,000,000 | 65,536 | Yes (vertex only) |
gemini-2.5-pro | Gemini 2.5 Pro | vertex, ai-studio | 1,000,000 | 65,536 | Yes (vertex only) |
gemini-2.5-flash | Gemini 2.5 Flash | vertex, ai-studio | 1,000,000 | 65,536 | Yes (vertex only) |
gemini-2.5-flash-lite | Gemini 2.5 Flash Lite | vertex, ai-studio | 1,048,576 | 65,536 | Yes (vertex only) |
Gemma (Open-Weight)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
gemma-3-12b | Gemma 3 12B | bedrock | 128,000 | 8,192 |
gemma-3-4b | Gemma 3 4B IT | bedrock | 128,000 | 8,192 |
gemma-3-27b | Gemma 3 27B | bedrock | 128,000 | 8,192 |
gemma-4-26b | Gemma 4 26B A4B | deepinfra | 262,144 | 16,384 |
gemma-4-31b | Gemma 4 31B | deepinfra, novita | 262,144 | 131,072 |
xAI (14 models)
Grok 4.20 & 4.1
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
grok-4.20-multi-agent-0309 | Grok 4.20 Multi-Agent | xai | 2,000,000 | 131,072 |
grok-4.20-0309-reasoning | Grok 4.20 Reasoning | xai | 2,000,000 | 131,072 |
grok-4.20-0309-non-reasoning | Grok 4.20 Non Reasoning | xai | 2,000,000 | 131,072 |
grok-4-1-fast-reasoning | Grok 4.1 Fast Reasoning | xai | 2,000,000 | 131,072 |
grok-4-1-fast-non-reasoning | Grok 4.1 Fast | xai | 2,000,000 | 131,072 |
Grok 4 & 4.x
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
grok-4.5 | Grok 4.5 | xai | 500,000 | 500,000 |
grok-4.3 | Grok 4.3 | xai, azure | 1,000,000 | 1,000,000 |
grok-4-0709 | Grok 4 (0709) | xai | 256,000 | 131,072 |
grok-4 | Grok 4 | xai | 256,000 | 256,000 |
grok-4-fast-reasoning | Grok 4 Fast Reasoning | xai | 2,000,000 | 131,072 |
grok-4-fast-non-reasoning | Grok 4 Fast | xai | 2,000,000 | 131,072 |
Grok 3
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
grok-3 | Grok 3 | xai | 131,072 | 131,072 |
grok-3-mini | Grok 3 Mini | xai | 131,072 | 131,072 |
Code & Build
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
grok-build-0.1 | Grok Build 0.1 | xai | 256,000 | 256,000 |
Meta (8 models)
Llama 4
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
llama-4-scout | Llama 4 Scout | cloudflare, bedrock | 131,000 | 32,768 |
llama-4-maverick | Llama 4 Maverick | bedrock | 1,048,576 | 8,192 |
Llama 3.x
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
llama-3.3-70b-instruct | Llama 3.3 70B Instruct | cloudflare, bedrock | 128,000 | 8,192 |
llama-3.2-1b-instruct | Llama 3.2 1B Instruct | cloudflare | 60,000 | 2,048 |
llama-3.1-8b-instruct | Llama 3.1 8B Instruct | bedrock | 128,000 | 8,192 |
llama-3.1-70b-instruct | Llama 3.1 70B Instruct | bedrock | 128,000 | 8,192 |
Llama 3
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
llama-3-70b-instruct | Llama 3 70B Instruct | bedrock | 8,000 | 2,048 |
llama-3-8b-instruct | Llama 3 8B Instruct | bedrock | 8,000 | 2,048 |
Mistral (13 models)
Frontier
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
mistral-large-3 | Mistral Large 3 | mistral, bedrock | 256,000 | 32,000 |
mistral-medium-3 | Mistral Medium 3 | mistral | 128,000 | 32,000 |
mistral-medium-3.1 | Mistral Medium 3.1 | mistral | 128,000 | 32,000 |
Magistral (Reasoning)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
magistral-medium-1.2 | Magistral Medium 1.2 | mistral | 128,000 | 128,000 |
magistral-small-1.2 | Magistral Small 1.2 | mistral, bedrock | 128,000 | 128,000 |
Code
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
codestral | Codestral | mistral | 128,000 | 32,000 |
devstral-2 | Devstral 2 | mistral | 256,000 | 32,000 |
Small & Efficient
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
mistral-nemo | Mistral Nemo | mistral | 128,000 | 32,000 |
mistral-small-3.1 | Mistral Small 3.1 | cloudflare | 128,000 | 8,192 |
mistral-small-3.2 | Mistral Small | mistral | 128,000 | 32,000 |
ministral-3-3b | Ministral 3 3B | mistral, bedrock | 256,000 | 32,000 |
ministral-3-8b | Ministral 3 8B | mistral, bedrock | 256,000 | 32,000 |
ministral-3-14b | Ministral 3 14B | mistral, bedrock | 256,000 | 32,000 |
Alibaba Cloud (24 models)
Qwen 3.7
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
qwen3.7-max | Qwen3.7 Max | alibaba | 1,000,000 | 64,000 |
qwen3.7-plus | Qwen3.7 Plus | alibaba | 1,000,000 | 64,000 |
Qwen 3.6
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
qwen3.6-35b | Qwen3.6 35B A3B | alibaba, deepinfra | 262,144 | 64,000 |
qwen3.6-plus | Qwen3.6 Plus | alibaba | 1,000,000 | 64,000 |
qwen3.6-flash | Qwen3.6 Flash | alibaba | 1,000,000 | 64,000 |
Qwen 3.5
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
qwen3.5-122b-a10b | Qwen3.5 122B A10B | alibaba | 256,000 | 64,000 |
qwen3.5-plus | Qwen3.5 Plus | alibaba | 1,000,000 | 64,000 |
qwen3.5-flash | Qwen3.5 Flash | alibaba | 1,000,000 | 64,000 |
qwen3.5-397b-a17b | Qwen3.5 397B A17B | alibaba | 256,000 | 64,000 |
qwen3.5-35b-a3b | Qwen3.5 35B A3B | alibaba | 256,000 | 64,000 |
Qwen 3 Max (Flagship)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
qwen3-max | Qwen3 Max | alibaba | 256,000 | 64,000 |
Qwen 3 Coder (Agentic Coding)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
qwen3-coder-30b-a3b | Qwen3 Coder 30B A3B | bedrock | 256,000 | 65,536 |
qwen3-coder-next | Qwen3 Coder Next | bedrock | 256,000 | 65,536 |
qwen3-coder-plus | Qwen3 Coder Plus | alibaba | 1,000,000 | 64,000 |
qwen3-coder-flash | Qwen3 Coder Flash | alibaba | 1,000,000 | 64,000 |
Qwen 3
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
qwen3-30b | Qwen3 30B | cloudflare | 32,768 | 8,192 |
qwen3-32b | Qwen3 32B | bedrock | 32,000 | 8,192 |
qwen3-next-80b-a3b | Qwen3 Next 80B A3B | bedrock | 128,000 | 8,192 |
qwen3-vl-235b-a22b | Qwen3 VL 235B A22B | bedrock | 128,000 | 8,192 |
qwen3-vl-plus | Qwen3 VL Plus | alibaba | 256,000 | 32,000 |
qwen3-vl-flash | Qwen3 VL Flash | alibaba | 256,000 | 32,000 |
QwQ (Reasoning)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
qwq-32b | QwQ 32B | cloudflare | 24,000 | 16,384 |
Qwen Legacy
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
qwen-plus | Qwen Plus | alibaba | 1,000,000 | 32,000 |
qwen-flash | Qwen Flash | alibaba | 1,000,000 | 32,000 |
DeepSeek (6 models)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
deepseek-r1 | DeepSeek R1 | bedrock | 128,000 | 32,768 |
deepseek-r1-0528 | DeepSeek R1 0528 | novita | 163,840 | 32,768 |
deepseek-r1-distill-32b | DeepSeek R1 Distill 32B | cloudflare | 80,000 | 80,000 |
deepseek-v3-2 | DeepSeek V3.2 | vertex, deepinfra, bedrock, azure, novita | 163,840 | 65,536 |
deepseek-v4-flash | DeepSeek V4 Flash | deepseek, novita, alibaba, fireworks | 1,048,576 | 393,216 |
deepseek-v4-pro | DeepSeek V4 Pro | deepseek, azure-fw, novita, alibaba, fireworks | 1,040,000 | 384,000 |
z.ai (9 models)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
glm-5.2 | GLM-5.2 | deepinfra, novita, cloudflare, fireworks | 1,048,576 | 256,000 |
glm-5.1 | GLM-5.1 | deepinfra, azure-fw, novita, alibaba, fireworks | 204,800 | 202,752 |
glm-5 | GLM-5 | vertex, zai, novita | 202,800 | 131,072 |
glm-4.7 | GLM-4.7 | zai, bedrock | 200,000 | 128,000 |
glm-4.7-flash | GLM-4.7 Flash | bedrock, cloudflare | 200,000 | 131,072 |
glm-4.6 | GLM-4.6 | zai | 200,000 | 128,000 |
glm-4.6v | GLM-4.6v | zai | 131,072 | 32,768 |
glm-4.5 | GLM-4.5 | zai | 128,000 | 96,000 |
glm-4.5v | GLM-4.5v | zai | 131,072 | 16,384 |
Amazon (5 models)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
nova-lite | Amazon Nova Lite | bedrock | 300,000 | 5,000 |
nova-micro | Amazon Nova Micro | bedrock | 128,000 | 5,000 |
nova-pro | Amazon Nova Pro | bedrock | 300,000 | 5,000 |
nova-premier | Amazon Nova Premier | bedrock | 1,000,000 | 20,000 |
nova-2-lite | Amazon Nova 2 Lite | bedrock | 256,000 | 5,000 |
MiniMax (8 models)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
minimax-m2 | MiniMax M2 | minimax, bedrock | 204,800 | 8,192 |
minimax-m2-1 | MiniMax M2.1 | minimax, bedrock | 204,800 | 8,192 |
minimax-m2-1-highspeed | MiniMax M2.1 Highspeed | minimax | 204,800 | 8,192 |
minimax-m2-5 | MiniMax M2.5 | minimax | 204,800 | 8,192 |
minimax-m2-5-highspeed | MiniMax M2.5 Highspeed | minimax | 204,800 | 8,192 |
minimax-m2-7 | MiniMax M2.7 | minimax, novita, fireworks | 204,800 | 196,600 |
minimax-m2-7-highspeed | MiniMax M2.7 Highspeed | minimax | 204,800 | 131,072 |
minimax-m3 | MiniMax M3 | minimax, fireworks | 1,000,000 | 512,000 |
Moonshot AI (5 models)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
kimi-k3 | Kimi K3 | moonshot | 1,048,576 | 1,048,576 |
kimi-k2-thinking | Kimi K2 Thinking | bedrock | 256,000 | 65,535 |
kimi-k2-5 | Kimi K2.5 | bedrock, azure, novita, alibaba | 262,144 | 262,144 |
kimi-k2-6 | Kimi K2.6 | deepinfra, cloudflare, azure, azure-fw, novita, fireworks | 262,144 | 262,144 |
kimi-k2-7-code | Kimi K2.7 Code | moonshot, deepinfra, novita, cloudflare, fireworks | 262,144 | 262,144 |
NVIDIA (3 models)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
nemotron-3-120b | Nemotron 3 120B A12B | cloudflare | 256,000 | 256,000 |
nemotron-3-nano-omni | Nemotron 3 Nano Omni 30B A3B Reasoning | deepinfra | 131,072 | 16,384 |
nemotron-3-ultra-nvfp4 | Nemotron 3 Ultra NVFP4 | fireworks | 262,144 | 262,144 |
Xiaomi (2 models)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
mimo-v2.5 | MiMo V2.5 | deepinfra, novita | 1,048,576 | 131,072 |
mimo-v2.5-pro | MiMo V2.5 Pro | novita | 1,048,576 | 131,072 |
Cohere (2 models)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
command-a | Command A | cohere | 256,000 | 8,192 |
command-a-vision | Command A Vision | cohere | 128,000 | 8,000 |
Writer (2 models)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
palmyra-x4 | Palmyra X4 | bedrock | 128,000 | 8,192 |
palmyra-x5 | Palmyra X5 | bedrock | 128,000 | 8,192 |
AI21 Labs (2 models)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
jamba-1-5-large | Jamba 1.5 Large | bedrock | 256,000 | 4,096 |
jamba-1-5-mini | Jamba 1.5 Mini | bedrock | 256,000 | 4,096 |
StepFun AI (2 models)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
step-3-5-flash | Step 3.5 Flash | deepinfra | 262,100 | 16,384 |
step-3-7-flash | Step 3.7 Flash | novita, deepinfra | 262,144 | 256,000 |
IBM (1 model)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
ibm-granite-micro | IBM Granite Micro | cloudflare | 131,000 | 4,096 |
Tencent (1 model)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
hy3 | Hunyuan Hy3 | novita | 262,144 | 262,144 |
Concentrate (1 model)
| Model Slug | Name | Providers | Context | Max Output |
|---|---|---|---|---|
redact-v1 | Redact v1 | concentrate | 256,000 | 256,000 |
Providers
Models are available across 21 providers. The same model may be offered by multiple providers with different pricing, latency, and feature support.| Provider | Slug | Description |
|---|---|---|
| OpenAI | openai | Direct OpenAI API access |
| Anthropic | anthropic | Direct Anthropic API access |
| Azure | azure | Microsoft Azure OpenAI Service |
| Azure AI Foundry | azure-fw | Azure AI Foundry hosted open-weight models |
| AWS Bedrock | bedrock | Amazon Bedrock managed inference |
| Google Vertex AI | vertex | Google Cloud Vertex AI |
| Google AI Studio | ai-studio | Google AI Studio |
| xAI | xai | xAI direct API access |
| Cohere | cohere | Cohere direct API access |
| Mistral | mistral | Mistral AI direct API access |
| Alibaba Cloud | alibaba | Alibaba Cloud Model Studio (DashScope) direct API access |
| Cloudflare | cloudflare | Cloudflare Workers AI |
| z.ai | zai | Zhipu AI direct API access |
| MiniMax | minimax | MiniMax direct API access |
| Moonshot AI | moonshot | Moonshot AI direct API access |
| DeepSeek | deepseek | DeepSeek direct API access |
| DeepInfra | deepinfra | DeepInfra inference platform |
| Fireworks | fireworks | Fireworks AI inference platform |
| Novita | novita | Novita AI inference platform |
| Blue Lobster | bluelobster | Blue Lobster inference |
| Concentrate | concentrate | Concentrate first-party hosted models |
Model Selection
There are three ways to specify which model to use:| Method | Format | Example | Behavior |
|---|---|---|---|
| Model slug | "model-slug" | "claude-opus-4-8" | Auto-routes to the best provider |
| Provider-pinned | "provider/model-slug" | "anthropic/claude-opus-4-8" | Uses specific provider, falls back to others |
| Auto | "auto" | "auto" | System selects optimal model and provider |
Querying Models Programmatically
Use the Models API to get real-time model data including current pricing and per-provider ZDR status:# List all models (OpenAI-compatible combined shape)
curl https://api.concentrate.ai/v1/models \
-H "Authorization: Bearer YOUR_API_KEY"
# Get a specific model (native shape with per-provider zdr field)
curl https://api.concentrate.ai/v1/models/claude-opus-4-8 \
-H "Authorization: Bearer YOUR_API_KEY"
# List models by author
curl https://api.concentrate.ai/v1/models/authors/anthropic \
-H "Authorization: Bearer YOUR_API_KEY"
# List models by provider
curl https://api.concentrate.ai/v1/models/providers/bedrock/models \
-H "Authorization: Bearer YOUR_API_KEY"
import requests
headers = {"Authorization": "Bearer YOUR_API_KEY"}
# List all models
res = requests.get(
"https://api.concentrate.ai/v1/models",
headers=headers,
).json()
for model in res["data"]:
print(f"{model['id']:30s} {model['owned_by']}")
const headers = { Authorization: "Bearer YOUR_API_KEY" };
// List all models
const res = await fetch("https://api.concentrate.ai/v1/models", { headers });
const { data } = await res.json();
for (const model of data) {
console.log(`${model.id.padEnd(30)} ${model.owned_by}`);
}
Related Documentation
List Models
Full API reference for querying models
Routing
How provider selection and fallback works
Zero Data Retention
ZDR-certified models and providers
Quickstart
Make your first API call