Ornith 1.5 122B

ornith-ai/Ornith-1.5-122B

Get API key Chat Completions API reference

Ornith 1.5 122B is a mixture-of-experts reasoning model with about 10B active parameters. It takes text and image input. RunInfra serves it as ornith-ai/Ornith-1.5-122B at $0.20 per 1M input tokens and $0.80 per 1M output tokens. Its context window is 262,144 tokens. The API provides OpenAI-compatible chat completions and Anthropic-compatible Messages, POST /v1/messages.

Pricing

USD, pay per token

per 1M input tokens: $0.20
per 1M cached input tokens: $0.02
per 1M output tokens: $0.80

Measured performance

Output speed

302output tokens per second, model only

Time to first token

72milliseconds to first reasoning token

Cache hit rate

87.6%last 24 hours

Access

Confirm how your client reaches this model.

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

Capacity

Check the limits your workload must fit.

Context window: 262,144 tokens
Maximum request size: 3.5 MB per request
Maximum generated output: 262,144 tokens

Capabilities

See which request modes the API supports.

Tool calling: Supported
JSON mode: Supported
Streaming: Supported
Precision: BF16, unquantized

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":"ornith-1-5-122b","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="ornith-1-5-122b",
    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: "ornith-1-5-122b",
    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.
import base64
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",
)

# Images travel inline as base64 data URLs (png, jpeg, webp or gif,
# up to 8 per request). Remote image URLs are not fetched.
with open("photo.jpg", "rb") as image_file:
    image_b64 = base64.b64encode(image_file.read()).decode("ascii")

response = client.chat.completions.create(
    model="ornith-1-5-122b",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "What is in this photo?"},
                {
                    "type": "image_url",
                    "image_url": {"url": f"data:image/jpeg;base64,{image_b64}"},
                },
            ],
        }
    ],
    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.
// 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("ornith-1-5-122b"),
  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="ornith-1-5-122b",
    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="ornith-1-5-122b"
export ANTHROPIC_DEFAULT_SONNET_MODEL="ornith-1-5-122b"
export ANTHROPIC_DEFAULT_OPUS_MODEL="ornith-1-5-122b"
export ANTHROPIC_DEFAULT_HAIKU_MODEL="ornith-1-5-122b"
export CLAUDE_CODE_SUBAGENT_MODEL="ornith-1-5-122b"
claude

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NVIDIA InceptionMember of NVIDIA Inception.