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OpenAI
openai/gpt-3.5-turbo-16kCatalogue: Indexed in the reference catalogue; nothing on this deployment answers as this model yet.
Published by the vendor; the platform bills at the target's declared price.
OpenAI openai/gpt-3.5-turbo-16k
This model offers four times the context length of gpt-3.5-turbo, allowing it to support approximately 20 pages of text in a single request at a higher cost. Training data: up...
GPT-3.5 Turbo 16k earns a request when it needs tool calls; a short, general request would go to Nemotron 3.5 Super VL (free) instead - free per million input tokens against $3.00 here; and the hardest requests, where the quality floor rules it out, to Claude Opus 5.5 (batch). Your rules decide the floor; the trace shows the comparison for every request.
Lower input price and an intelligence index within 5 points (this model has no published index).
Nothing on this deployment answers as this model yet. Connect your own provider under Model providers, or add a target to your catalogue - the router picks it up without retraining.
# targets.yaml - declare a target that runs GPT-3.5 Turbo 16k
targets:
- id: gpt-3-5-turbo-16k
kind: llm
name: GPT-3.5 Turbo 16k
metadata:
model: openai/gpt-3.5-turbo-16k # links the target to this catalogue entry
capabilities:
domains: [general]
supports_tools: true
context_window: 16385
cost:
usd_per_1k_tokens: 0.003500Input list price per million tokens; GPT-3.5 Turbo 16k is the most expensive of 13 listed.
Photo: RDNE Stock project
A higher intelligence index, best first, with the price it comes at.
Other models by the same vendor in the catalogue.
The catalogue prints input and output prices and what three typical monthly workloads cost on each.