
Gpt-3.5-turbo vs GPT-4 Turbo 1106 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 has lower listed token pricing, while GPT-4 Turbo 1106 can still be preferable if benchmark results better match your workload.
Author: Mirai Minds Research Team
Last updated:
Gpt-3.5-turbo | GPT-4 Turbo 1106 | |
|---|---|---|
Provider The entity that provides this model. | OpenAI | OpenAI |
Input Context Window The number of tokens supported by the input context window. | 4096 tokens | 128K tokens |
Maximum Output Tokens The number of tokens that can be generated by the model in a single request. | 4096 tokens | 4,096 tokens |
Release Date When the model was first released. | Nov 28, 2022 over 1 yearago 2022-11-28 | Nov 06, 2023 over 1 year 2023-11-06 |
Gpt-3.5-turbo | GPT-4 Turbo 1106 | |
|---|---|---|
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 | GPT-4 Turbo 1106 | |
|---|---|---|
Input Cost of input data provided to the model. | $0.50 per million tokens | $10.00 per million tokens |
Output Cost of output tokens generated by the model. | $1.50 per million tokens | $30.00 per million tokens |
Gpt-3.5-turbo | GPT-4 Turbo 1106 | |
|---|---|---|
MMLU Evaluating LLM knowledge acquisition in zero-shot and few-shot settings. | 70.0 (5-shot) | Benchmark not available. |
MMMU A wide ranging multi-discipline and multimodal benchmark. | Benchmark not available. | Benchmark not available. |
HellaSwag A challenging sentence completion benchmark. | 85.5 (10-shot) | Benchmark not available. |
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sneh[at]miraiminds.coMirai Minds