InferX Endpoint | Agents-A1

Metadata

Name

Agents-A1

Provider

InternScience

Parameter Size

—

GPU Count

2

Context Length

262000

Concurrency

—

Cold Start TTFT

—

Recommended Use Cases

—

Detailed Intro

—

Log In To Use This Endpoint

This public page shows the published endpoint metadata and integration shape. Log in to get a tenant-scoped endpoint URL, inference API key, and the interactive playground. Log in

Integration

Start with the shared setup below, then choose the endpoint mode that fits your workload: token-based shared serving or a tenant-scoped dedicated GPU endpoint.

API Key

<INFERENCE_API_KEY>

An inference API key is required for both endpoint modes. Until one is available, the fields below keep the correct request shape and use a placeholder token.

Token-Based

Use the shared OpenAI-compatible endpoint. The base URL is shared across published endpoints, and usage is billed per token.

API Base URL

https://model.inferx.net/endpoints/v1

Model Name

Agents-A1

Sample REST Call

curl https://model.inferx.net/endpoints/v1/chat/completions \
  -H "Authorization: Bearer $INFERX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "Agents-A1", "messages": [{"role": "user", "content": "Hello"}]}'

Dedicated GPU

Model Spec

{
    "image": "inferx/vllm-openai:v0.20.2-cu129",
    "commands": [
        "--model",
        "InternScience/Agents-A1",
        "--enable-auto-tool-choice",
        "--tool-call-parser",
        "qwen3_coder",
        "--trust-remote-code",
        "--gpu-memory-utilization",
        "0.92",
        "--max-model-len",
        "262000",
        "--max-num-batched-tokens",
        "26200",
        "--mm-processor-cache-gb",
        "0",
        "--uvicorn-log-level",
        "warning",
        "--enable-prefix-caching",
        "--tensor-parallel-size",
        "2"
    ],
    "resources": {
        "GPU": {
            "Count": 2,
            "vRam": 70000
        }
    },
    "envs": [
        [
            "VLLM_USE_DEEP_GEMM",
            "0"
        ],
        [
            "VLLM_ALLREDUCE_USE_SYMM_MEM",
            "0"
        ]
    ],
    "policy": {
        "Obj": {
            "nvidia_replica": 0,
            "min_replica": 0,
            "max_replica": 1,
            "standby_per_node": 1,
            "parallel": 50,
            "queue_len": 100,
            "queue_timeout": 30.0,
            "scalein_timeout": 1.0,
            "scaleout_policy": {
                "WaitQueueRatio": {
                    "wait_ratio": 0.1
                }
            },
            "runtime_config": {
                "graph_sync": false
            }
        }
    },
    "sample_query": {
        "apiType": "text2text",
        "raw_query": false,
        "path": "v1/completions",
        "prompt": "write a quick sort algorithm.",
        "prompts": [],
        "dataUrl": "",
        "max_tokens": 0,
        "body": {
            "max_tokens": "1000",
            "stream": "true",
            "temperature": "0"
        },
        "loadingTimeout": 90
    }
}