Intelligence
N/A
44
General reasoning and benchmark headroom.
SituationalOpenAI: GPT-3.5 Turbo 16k is a mid-range text-first model from openai with a heavy runtime profile, compact context posture, and the clearest fit around reasoning / coding.
Benchmark blend
Dev workflow signal
Compact
Mid-range tier
OpenAI: GPT-3.5 Turbo 16k currently reads as a mid-range text-first option with compact context and a heavy runtime profile.
Decision Strip
Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.
General reasoning and benchmark headroom.
SituationalLatency data is partial.
SituationalHow much prompt and task state can stay in view.
Limited$4.00 output / 1M
CompetitiveEditorial Profile
Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.
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 to Sep 2021.
openai text-first profile
Reasoning / Coding with compact context and heavy runtime.
Balanced spend profile. Easier to justify in mixed production and exploration workloads.
The available source data suggests a balanced profile rather than one dominant edge.
Costs look manageable, but still deserve attention in always-on agents or batch jobs.
Latency profile is better for deliberate runs than rapid back-and-forth chat.
Current metadata points to a text-first profile rather than a broad multimodal one.
Context window is more comfortable for focused tasks than extremely long sessions.
Focused chat, retrieval-augmented flows, and narrower production tasks.
Benchmarks
Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.
Specs & Pricing
Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.
This model sits in a balanced spend range. It is easier to justify across both production and exploratory workflows.
Metadata
Verification details remain available, but the page no longer forces them ahead of the editorial read.