AI model comparison
Qwen3 14B vs Phi 4
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
Qwen
Qwen3 14B
Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue.
- Input / 1M
- $0.12
- Output / 1M
- $0.24
- Context
- 41K
Microsoft
Phi 4
[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.
- Input / 1M
- $0.07
- Output / 1M
- $0.14
- Context
- 16K
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
Phi 4
1.7x cheaper for a typical chat
Higher intelligence score
Qwen3 14B
6.7 vs 5.9 on Artificial Analysis
Larger context window
Qwen3 14B
41K vs 16K tokens
Newer release
Qwen3 14B
Released April 28, 2025
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Qwen3 14B6.7Coding index
Qwen3 14BNot availableAgentic index
Qwen3 14BNot availablePricing
Qwen3 14B vs Phi 4 API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Qwen3 14B | |
|---|---|---|
| Input tokensPer 1M tokens | $0.12 | $0.07 |
| Output tokensPer 1M tokens | $0.24 | $0.14 |
| Cached input (read)Per 1M tokens | Not available | Not available |
| Cache writePer 1M tokens | Not available | Not available |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Qwen3 14B$0.36Coding task
30K in, 4K out
Qwen3 14B$4.56Long document summary
150K in, 2K out
Qwen3 14B$18.48Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | Qwen3 14B | |
|---|---|---|
| Context window | 41K tokens | 16K tokens |
| Max output | 16K tokens | 15K tokens |
| Input types | Text | Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | April 28, 2025 | January 10, 2025 |
Features
Supported features
API features available for each model.
| Metric | Qwen3 14B | |
|---|---|---|
| Tool calling | Supported | Not supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Not supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Not supported | Not supported |
Keep exploring
More on these models
Other head-to-heads, the full model page, and the alternatives list for each model.
Qwen3 14BView full model details- Qwen3 14B vs Qwen3.7 Flash
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- Qwen3 14B vs Qwen3 Coder 30B A3B Instruct
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- Qwen3 14B vs Nemotron 3 Nano 30B A3B
- Qwen3 14B vs Qwen3 VL 30B A3B Instruct
- Qwen3 14B vs Qwen2.5 72B Instruct
- Qwen3 14B vs Qwen3 30B A3B
- Qwen3 14B vs Qwen3 32B
- Qwen3 14B vs Mistral Small 3
- Qwen3 14B vs Nova Lite 1.0
- Qwen3 14B vs Reka Flash 3
- Qwen3 14B vs Ministral 3 14B 2512
Our take
Phi 4 is 1.7x cheaper for a typical chat. Qwen3 14B scores higher on the Artificial Analysis Intelligence Index (6.7 vs 5.9). Qwen3 14B has the larger context window (41K vs 16K tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is Qwen3 14B or Phi 4 cheaper?
Phi 4 is cheaper for a typical chat (2K input tokens and 500 output tokens). Phi 4 costs $0.07 per 1M input tokens and $0.14 per 1M output tokens, while Qwen3 14B costs $0.12 per 1M input tokens and $0.24 per 1M output tokens.
Which has a bigger context window, Qwen3 14B or Phi 4?
Qwen3 14B supports up to 41K tokens of context, compared with 16K for Phi 4.
Is Qwen3 14B smarter than Phi 4?
On the Artificial Analysis Intelligence Index, Qwen3 14B scores 6.7 and Phi 4 scores 5.9, putting Qwen3 14B ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use Qwen3 14B and Phi 4 at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Qwen3 14B and Phi 4 answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Qwen3 14B and Phi 4 at the same time. Compare the answers side by side and keep the best one.