Model comparison
Phi-4 Mini vs Qwen3 14B
Qwen3 14B is the stronger model overall, scoring 35.5 to 30.9 on the Noometry Index. Phi-4 Mini costs 4.7× less per token, which makes it the better buy when Qwen3 14B's lead doesn't matter for your workload.
Last verified . 3 shared benchmarks.
Microsoft
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. Phi-4 Mini scores higher in 1 category and Qwen3 14B in 2 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3 14B leads 39.3 to 25.3.
- The biggest single-benchmark swing is SciCode: 10.8% for Phi-4 Mini and 31.6% for Qwen3 14B.
- Phi-4 Mini is cheaper at $0.075 / $0.30 per million input/output tokens, against $0.35 / $1.40 for Qwen3 14B.
- Qwen3 14B accepts more context: 131K tokens versus 128K.
Side by side
| Phi-4 Mini | Qwen3 14B | |
|---|---|---|
| Provider | Microsoft | Alibaba (Qwen) |
| Noometry Index | 30.9 | 35.5 |
| Released | 2024-12-11 | 2025-04 |
| Weights | Open | Open |
| Context window | 128K | 131K |
| Max output | 4K | 8K |
| Input $ / M tokens | $0.075 | $0.35 |
| Output $ / M tokens | $0.30 | $1.40 |
| Results tracked | 3 | 12 |
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Category by category
Coding Qwen3 14B leads
Phi-4 Mini: 28.1 (#317), Qwen3 14B: 37.3 (#195)
| Benchmark | Phi-4 Mini | Qwen3 14B |
|---|---|---|
| SciCode | 10.8% | 31.6% |
Agentic & Tool Use Not comparable
Phi-4 Mini: —, Qwen3 14B: 29.6 (#83)
| Benchmark | Phi-4 Mini | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41% |
Reasoning Phi-4 Mini leads
Phi-4 Mini: 22.4 (#195), Qwen3 14B: 18.5 (#280)
| Benchmark | Phi-4 Mini | Qwen3 14B |
|---|---|---|
| CritPt | 0% | 0% |
| Kagi LLM Benchmark | — | 49.1% |
| Chess Puzzles | — | 4% |
| DTBench | — | 64% |
| LMCA | — | 18.2% |
| Epoch Capabilities Index | — | 138.23 |
Math Not comparable
Phi-4 Mini: —, Qwen3 14B: 38.6 (#133)
| Benchmark | Phi-4 Mini | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 66.4% |
Knowledge Qwen3 14B leads
Phi-4 Mini: 25.3 (#262), Qwen3 14B: 39.3 (#134)
| Benchmark | Phi-4 Mini | Qwen3 14B |
|---|---|---|
| Vectara Hallucination Rate | 23.5% | 5.4% |
| GPQA Diamond | — | 63.8% |
Long Context Not comparable
Phi-4 Mini: —, Qwen3 14B: 38.1 (#204)
| Benchmark | Phi-4 Mini | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
Frequently asked questions
Is Phi-4 Mini better than Qwen3 14B?
Qwen3 14B is the stronger model overall, scoring 35.5 to 30.9 on the Noometry Index. Phi-4 Mini costs 4.7× less per token, which makes it the better buy when Qwen3 14B's lead doesn't matter for your workload.
Which is cheaper, Phi-4 Mini or Qwen3 14B?
Phi-4 Mini is cheaper. It lists at $0.075 per million input tokens and $0.30 per million output tokens; Qwen3 14B lists at $0.35 and $1.40.
Is Phi-4 Mini or Qwen3 14B better for coding?
Qwen3 14B scores higher on coding benchmarks: 37.3 versus 28.1 in the Noometry coding category.
Which has the bigger context window?
Qwen3 14B does, with 131K tokens against 128K.
How many benchmarks do Phi-4 Mini and Qwen3 14B share?
3 benchmarks have published results for both models. Phi-4 Mini has 3 scored results on Noometry and Qwen3 14B has 12.