GLM 5.3

zai-org/GLM-5.3

Get API key Chat Completions API reference

GLM 5.3 serves text only, using an NVIDIA NVFP4 artifact governed by the NVIDIA Open Model Agreement and the GLM-5.3 License. RunInfra serves it as zai-org/GLM-5.3 at $1.40 per 1M input tokens and $4.40 per 1M output tokens. Its context window is 1,048,576 tokens. The API provides OpenAI-compatible chat completions and Anthropic-compatible Messages, POST /v1/messages.

Pricing

USD, pay per token

per 1M input tokens: $1.40
per 1M cached input tokens: $0.14
per 1M output tokens: $4.40

Access

Confirm how your client reaches this model.

Provider: Z.ai
API compatibility: OpenAI-compatible chat completions
Anthropic compatibility: Anthropic-compatible Messages, POST /v1/messages
Accepted input: Text only
Availability: Available
Data retention: Zero data retention by default. Never used for training.

Capacity

Check the limits your workload must fit.

Context window: 1,048,576 tokens
Maximum request size: 3.5 MB per request
Maximum generated output: 1,048,576 tokens

Capabilities

See which request modes the API supports.

Tool calling: Supported
JSON mode: Supported
Streaming: Supported

View full spec

Gateway compatibility: OpenAI- and Anthropic-compatible APIs for compatible clients, tools, and gateways
Prefix caching: Automatic prefix caching runs on every replica, and requests from the same session or conversation are routed back to the replica that holds their cached prefix. A stable session hint or prompt_cache_key provides explicit grouping; otherwise RunInfra derives it from the start of the conversation or, failing that, the workspace. Hits remain best effort until eviction or a serve restart, never guaranteed. Cached input is billed at the cached input rate. Responses report cached token counts.
Cache retention: Prefix cache is held on the serving GPU and evicted under memory pressure. Retention is best effort.
Upstream model: View model

Code examples

Set RUNINFRA_GATEWAY_KEY to your workspace API key before using an example.

ShellChat completion

# Set RUNINFRA_GATEWAY_KEY to your API key before running this example.
curl -X POST "https://api.runinfra.ai/v1/chat/completions" \
  -H "Authorization: Bearer $RUNINFRA_GATEWAY_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"glm-5-3","messages":[{"role":"user","content":"Hello"}],"max_tokens":16384}'

# Set RUNINFRA_GATEWAY_KEY to your API key before running this example.
import os
import uuid
from openai import OpenAI

api_key = os.environ.get("RUNINFRA_GATEWAY_KEY")
if not api_key: raise RuntimeError("Set RUNINFRA_GATEWAY_KEY first.")

client = OpenAI(
    api_key=api_key,
    base_url="https://api.runinfra.ai/v1",
)

response = client.chat.completions.create(
    model="glm-5-3",
    messages=[{"role": "user", "content": "Hello"}],
    max_tokens=16384,
    extra_headers={"X-Client-Request-Id": str(uuid.uuid4())},
)
print(response.choices[0].message.content)

// Set RUNINFRA_GATEWAY_KEY to your API key before running this example.
import { randomUUID } from "node:crypto";
import OpenAI from "openai";

const apiKey = process.env.RUNINFRA_GATEWAY_KEY;
if (!apiKey) throw new Error("Set RUNINFRA_GATEWAY_KEY first.");

const client = new OpenAI({
  apiKey,
  baseURL: "https://api.runinfra.ai/v1",
});

const response = await client.chat.completions.create(
  {
    model: "glm-5-3",
    messages: [{ role: "user", content: "Hello" }],
    max_tokens: 16384,
  },
  { headers: { "X-Client-Request-Id": randomUUID() } },
);

console.log(response.choices[0]?.message.content ?? "");

// Set RUNINFRA_GATEWAY_KEY to your API key before running this example.
// Server-side only: never expose RUNINFRA_GATEWAY_KEY in browser code.
import { createOpenAICompatible } from "@ai-sdk/openai-compatible";
import { generateText } from "ai";

const apiKey = process.env.RUNINFRA_GATEWAY_KEY;
if (!apiKey) throw new Error("Set RUNINFRA_GATEWAY_KEY first.");

const runinfra = createOpenAICompatible({
  name: "runinfra",
  baseURL: "https://api.runinfra.ai/v1",
  apiKey,
});

const { text } = await generateText({
  model: runinfra.chatModel("glm-5-3"),
  maxOutputTokens: 16384,
  messages: [
    { role: "user", content: "Write a TypeScript retry helper." },
  ],
});

console.log(text);

# Set RUNINFRA_GATEWAY_KEY to your API key before running this example.
import os
from anthropic import Anthropic

api_key = os.environ.get("RUNINFRA_GATEWAY_KEY")
if not api_key: raise RuntimeError("Set RUNINFRA_GATEWAY_KEY first.")

client = Anthropic(
    # The SDK appends /v1, so use the bare host.
    base_url="https://api.runinfra.ai",
    api_key=api_key,
)

message = client.messages.create(
    model="glm-5-3",
    max_tokens=16384,
    messages=[{"role": "user", "content": "Hello"}],
)
print(message.content[0].text)

# Set RUNINFRA_GATEWAY_KEY to your API key before running this example.
export ANTHROPIC_BASE_URL="https://api.runinfra.ai"
export ANTHROPIC_AUTH_TOKEN=$RUNINFRA_GATEWAY_KEY
export ANTHROPIC_MODEL="glm-5-3"
export ANTHROPIC_DEFAULT_SONNET_MODEL="glm-5-3"
export ANTHROPIC_DEFAULT_OPUS_MODEL="glm-5-3"
export ANTHROPIC_DEFAULT_HAIKU_MODEL="glm-5-3"
export CLAUDE_CODE_SUBAGENT_MODEL="glm-5-3"
claude

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RunInfra is a sub-product of RightNow Research Lab.

SOC 2 Type IIAudited access, logging, and incident response.
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NVIDIA InceptionMember of NVIDIA Inception.