16K context window handles medium-length documents and multi-turn conversations
Fast inference with low latency compared to flagship models
Well-documented and widely supported across third-party tooling and frameworks
Lower cost than GPT-4 class models for simple, high-volume tasks
Weaknesses
Significantly weaker reasoning and instruction-following than GPT-4o, Claude Sonnet 4, or Gemini 1.5 Pro — all available at similar or lower prices
At $3/$4 per million tokens, it offers poor value: GPT-4o mini outperforms it at a fraction of the cost
16K context is now considered small; competitors offer 128K–1M+ token windows as standard
Monthly cost estimate
See what OpenAI: GPT-3.5 Turbo 16k actually costs at your usage level
Input tokens / month1M
10k50M
Output tokens / month500k
10k25M
Input cost
$3.00
Output cost
$2.00
Total / month
$5.00
Based on OpenAI: GPT-3.5 Turbo 16k API pricing: $3/1M input · $4/1M output. Real costs vary by provider discounts and caching. Check the provider for exact current rates.
Price History
OpenAI: GPT-3.5 Turbo 16k pricing over time
→0% since Mar 27
2 data points · tracked daily since Mar 27, 2026
Ready to try it?
Start using OpenAI: GPT-3.5 Turbo 16k
Legacy integrations or applications that need slightly longer documents processed without upgrading to a modern model.. Start free — no card required.
Recommendations are made independently based on real-world use and public benchmarks. See our disclosures for details.
Compare alternatives
Similar models worth checking before you commit.
OpenAIBudget
OpenAI: GPT-4.1 Mini
GPT-4.1 Mini is OpenAI's cost-optimized small model from the GPT-4.1 family, designed to deliver strong instruction-following and coding performance at a fraction of flagship pricing. It targets high-volume, latency-sensitive applications where cost efficiency matters more than peak capability.
Verdict
The go-to budget workhorse for high-volume OpenAI API users who need GPT-4.1 quality at GPT-3.5 prices.
Quality score
65%
Pricing
$0.40/1M in
$1.60/1M out
Speed
Very fast
Best for high-volume production workloads that need reliable gpt-4-class instruction following without flagship pricing.
Context
1.0M tokens
Pricing shown is $0.40 input / $1.60 output per 1M tokens. Cached input tokens are significantly cheaper. The 1M token context window is a standout feature at this price tier — few competitors match it. Supersedes GPT-4o as the recommended default for cost-conscious applications.
BudgetFastLong ContextOpenAIProduction
Best for
High-volume production workloads that need reliable GPT-4-class instruction following without flagship pricing.
GPT-4.1 Nano is OpenAI's smallest and most cost-efficient model in the GPT-4.1 family, designed for high-throughput, latency-sensitive tasks at near-commodity pricing. It offers a 1M token context window at just $0.10/1M input tokens, making it one of the cheapest large-context models available.
Verdict
The best pick for budget-conscious, high-volume workloads that don't demand frontier intelligence.
Quality score
54%
Pricing
$0.10/1M in
$0.40/1M out
Speed
Very fast
Best for high-volume production workloads like classification, extraction, summarization, and simple q&a where cost and speed matter more than frontier reasoning.
Context
1.0M tokens
Pricing is $0.10/1M input and $0.40/1M output tokens. Officially supersedes GPT-4o in OpenAI's lineup for lightweight use cases. Context window of ~1.047M tokens is one of the largest available at this price tier.
BudgetFastLong ContextHigh VolumeOpenAI
Best for
High-volume production workloads like classification, extraction, summarization, and simple Q&A where cost and speed matter more than frontier reasoning.
GPT-5 Mini is OpenAI's budget-tier distillation of GPT-5, designed for high-volume, cost-sensitive tasks that don't require full flagship reasoning depth. It supersedes GPT-4o with improved instruction following and a massively expanded 400K context window at a fraction of the cost.
Verdict
The new budget default for OpenAI API users: faster, cheaper, and smarter than GPT-4o with a context window that punches well above its price tier.
Quality score
66%
Pricing
$0.25/1M in
$2.00/1M out
Speed
Very fast
Best for high-volume production workloads — chatbots, summarization pipelines, and document q&a — where cost efficiency matters more than peak reasoning.
Context
400k tokens
Output cost of $2/1M tokens is higher than some competing budget models (Gemini Flash at ~$0.60/1M output). At scale, output-heavy tasks may erode cost advantages — monitor token ratios carefully. Supersedes GPT-4o, which may be deprecated on a rolling basis.
BudgetFastLong ContextHigh VolumeOpenAI
Best for
High-volume production workloads — chatbots, summarization pipelines, and document Q&A — where cost efficiency matters more than peak reasoning.
Pricing moves, ranking shifts, and capability updates.
New ModelMar 27, 2026
OpenAI: GPT-3.5 Turbo 16k — added to UseRightAI
OpenAI: GPT-3.5 Turbo 16k (OpenAI) is now indexed. An outdated model that's been lapped by cheaper, more capable competitors on every meaningful dimension.
OpenAI: GPT-3.5 Turbo 16k is best for legacy integrations or applications that need slightly longer documents processed without upgrading to a modern model.. It is a strong fit when that workflow matters more than the tradeoffs around balanced pricing and fast speed.
When should I avoid OpenAI: GPT-3.5 Turbo 16k?
You're starting a new project — cheaper, faster, and smarter alternatives like GPT-4o mini or Claude Haiku 3.5 make this model obsolete.
What is a cheaper alternative to OpenAI: GPT-3.5 Turbo 16k?
Meta: Llama 3.1 8B Instruct is the lower-cost option to compare first when you want a similar workflow fit with less token spend.
What is a faster alternative to OpenAI: GPT-3.5 Turbo 16k?
OpenAI: GPT-4.1 Mini is the better pick when response time matters more than maximum depth or premium quality.
Newsletter
Get notified when OpenAI: GPT-3.5 Turbo 16k pricing changes
We track pricing daily. When this model drops or spikes, you'll know first.
No spam. Useful updates only. Affiliate disclosures always clearly labeled.
