
GPT-3.5 Turbo 16K vs GPT-4 32K compares provider, context window, token pricing, benchmark performance, and release timeline in one side-by-side view. Use this page to quickly identify which model is a better fit for your production constraints, quality targets, and estimated cost per request.
GPT-3.5 Turbo 16K has lower listed token pricing, while GPT-4 32K can still be preferable if benchmark results better match your workload.
Author: Mirai Minds Research Team
Last updated:
GPT-3.5 Turbo 16K | GPT-4 32K | |
|---|---|---|
Provider The entity that provides this model. | OpenAI | OpenAI |
Input Context Window The number of tokens supported by the input context window. | 16.4K tokens | 32.8K tokens |
Maximum Output Tokens The number of tokens that can be generated by the model in a single request. | 16.4K tokens | Not specified. |
Release Date When the model was first released. | Jun 13, 2023 over 1 yearago 2023-06-13 | Mar 14, 2023 over 1 year 2023-03-14 |
GPT-3.5 Turbo 16K | GPT-4 32K | |
|---|---|---|
Rank | Unknown | Unknown |
Arena Elo | Not specified. | Not specified. |
95% CI | Not specified. | Not specified. |
Votes | Not specified. | Not specified. |
License | Not specified. | Not specified. |
Knowledge Cutoff | Unknown | Unknown |
GPT-3.5 Turbo 16K | GPT-4 32K | |
|---|---|---|
Input Cost of input data provided to the model. | $3.00 per million tokens | $60.00 per million tokens |
Output Cost of output tokens generated by the model. | $4.00 per million tokens | $120.00 per million tokens |
GPT-3.5 Turbo 16K | GPT-4 32K | |
|---|---|---|
MMLU Evaluating LLM knowledge acquisition in zero-shot and few-shot settings. | Benchmark not available. | Benchmark not available. |
MMMU A wide ranging multi-discipline and multimodal benchmark. | Benchmark not available. | Benchmark not available. |
HellaSwag A challenging sentence completion benchmark. | Benchmark not available. | Benchmark not available. |
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sneh[at]miraiminds.coMirai Minds