Phi 4 Open vs 
GPT-3.5 Turbo 16k Paid
Phi 4 vs GPT-3.5 Turbo 16k compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.
GPT-3.5 Turbo 16k — full profile ›
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
$0.14 /M outputNo per-token fees if you self-host
$4 /M outputManaged API (no infra to run)
Phi 4 vs GPT-3.5 Turbo 16k specs
| Spec | Phi 4 | GPT-3.5 Turbo 16k | Winner |
|---|---|---|---|
| Maker | Microsoft | OpenAI | – |
| Type | Open-weight | Proprietary | |
| Context window | 16K tokens | 16K tokens | |
| Input price | $0.07/M · free self-host | $3/M | |
| Output price | $0.14/M · free self-host | $4/M | |
| Vision / multimodal | No | No | – |
| Tool / function calling | No | Yes | |
| Self-hostable | Yes | No (API only) | |
| License | MIT | Proprietary |
Price gap & when to choose each
Phi 4 is ~29× cheaper than GPT-3.5 Turbo 16k on output tokens ($0.14 vs $4 per M tokens).
- You want to self-host or run on your cloud
- You prioritize data privacy & control
- You want the lowest operating costs
- You are building open or reproducible AI
- You want frontier performance through a managed API
- You need the longer 16K context window
- You value reliability & ecosystem
- You don't want to manage infrastructure
Feature comparison
| Capability | Phi 4 | GPT-3.5 Turbo 16k |
|---|---|---|
| Open weights (downloadable) | ✓ | ✗ |
| Self-hostable | ✓ | ✗ |
| Runs fully offline | ✓ | ✗ |
| Vision / multimodal | ✗ | ✗ |
| Tool / function calling | ✗ | ✓ |
| 1M+ context window | ✗ | ✗ |
Benchmarks: Phi 4 vs GPT-3.5 Turbo 16k
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
How Phi 4 and GPT-3.5 Turbo 16k score
| Criterion | Phi 4 | GPT-3.5 Turbo 16k |
|---|---|---|
| Cost-efficiency | 5.0 | 4.0 |
| Context window | 2.0 | 2.0 |
| Openness | 5.0 | 1.5 |
| Self-hosting | 5.0 | 1.0 |
| Multimodality | 2.0 | 3.5 |
Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.
What each model is
Phi 4 Open
[Microsoft Research](/microsoft) Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses are needed. At 14 billion...
GPT-3.5 Turbo 16k Paid
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...
Frequently asked questions
Is Phi 4 as good as GPT-3.5 Turbo 16k?
Phi 4 is open-weight and competitive on many tasks, but GPT-3.5 Turbo 16k may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.
Can I run Phi 4 locally?
Yes. Phi 4 has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. GPT-3.5 Turbo 16k is API-only and cannot be self-hosted.
How much cheaper is Phi 4?
Phi 4 costs $0.14/M output vs $4/M for GPT-3.5 Turbo 16k — roughly 29x cheaper via API, and free if you self-host.
Phi 4 vs GPT-3.5 Turbo 16k — which should I pick in 2026?
Choose Phi 4 if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose GPT-3.5 Turbo 16k if you want frontier capability through a managed API with zero infrastructure to run.
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