ornith-ai/
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 #
Access #
Confirm how your client reaches this model.
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Provider
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Ornith
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API compatibility
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OpenAI-compatible chat completions
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Anthropic compatibility
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Anthropic-compatible Messages, POST /v1/messages
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Accepted input
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Text and images
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Availability
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Available
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Data retention
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
source & further reading
runinfra.ai — original article