{"slug": "ornith-1-5-122b-at-302tps", "title": "Ornith 1.5 122B at 302tps", "summary": "RunInfra is serving Ornith 1.5 122B, a mixture-of-experts reasoning model with about 10B active parameters that accepts text and image input, at $0.20 per 1M input tokens and $0.80 per 1M output tokens. The API offers a 262,144-token context window, OpenAI-compatible chat completions and Anthropic-compatible Messages via POST /v1/messages, with tool calling, JSON mode, streaming and BF16 unquantized precision. Cached input is billed at $0.02 per 1M tokens, and RunInfra states the model runs with zero data retention by default and is never used for training.", "body_md": "# Ornith 1.5 122B\n\n`ornith-ai/`\nOrnith 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.\n\n## Pricing\n\nUSD, pay per token\n\n- per 1M input tokens\n- $0.20\n- per 1M cached input tokens\n- $0.02\n- per 1M output tokens\n- $0.80\n\n## Measured performance\n\n## Access\n\nConfirm how your client reaches this model.\n\n- Provider\n- Ornith\n- API compatibility\n- OpenAI-compatible chat completions\n- Anthropic compatibility\n- Anthropic-compatible Messages, POST /v1/messages\n- Accepted input\n- Text and images\n- Availability\n- Available\n- Data retention\n- [Zero data retention by default. Never used for training.](https://runinfra.ai/docs/security/data-retention)\n\n## Capacity\n\nCheck the limits your workload must fit.\n\n- Context window\n- 262,144 tokens\n- Maximum request size\n- 3.5 MB per request\n- Maximum generated output\n- 262,144 tokens\n\n## Capabilities\n\nSee which request modes the API supports.\n\n- Tool calling\n- Supported\n- JSON mode\n- Supported\n- Streaming\n- Supported\n- Precision\n- BF16, unquantized\n\n## View full spec\n\n- Gateway compatibility\n- OpenAI- and Anthropic-compatible APIs for compatible clients, tools, and gateways\n- Prefix caching\n- 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.\n- Cache retention\n- Prefix cache is held on the serving GPU and evicted under memory pressure. Retention is best effort.\n- Upstream model\n- [View model](https://huggingface.co/ornith-ai/Ornith-1.5-122B)", "url": "https://wpnews.pro/news/ornith-1-5-122b-at-302tps", "canonical_source": "https://runinfra.ai/inference-api/ornith-1-5-122b", "published_at": "2026-10-20 21:37:48+00:00", "updated_at": "2026-10-20 21:46:46.088307+00:00", "lang": "en", "topics": ["large-language-models", "ai-infrastructure", "ai-products", "ai-tools"], "entities": ["Ornith 1.5 122B", "RunInfra", "Ornith", "Hugging Face"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/ornith-1-5-122b-at-302tps", "markdown": "https://wpnews.pro/news/ornith-1-5-122b-at-302tps.md", "text": "https://wpnews.pro/news/ornith-1-5-122b-at-302tps.txt", "jsonld": "https://wpnews.pro/news/ornith-1-5-122b-at-302tps.jsonld"}}