Model comparison
Phi-4 vs Qwen3-Next 80B-A3B Instruct
Qwen3-Next 80B-A3B Instruct is the stronger model overall, scoring 43.0 to 31.2 on the Noometry Index. Phi-4 costs 10.0× less per token, which makes it the better buy when Qwen3-Next 80B-A3B Instruct's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
Microsoft
Alibaba (Qwen)Summary
- They share 18 benchmarks with published results for both. Phi-4 scores higher in 0 categories and Qwen3-Next 80B-A3B Instruct in 8 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3-Next 80B-A3B Instruct leads 38.8 to 20.8.
- The biggest single-benchmark swing is Vectara Hallucination Rate: 3.7% for Phi-4 and 9.3% for Qwen3-Next 80B-A3B Instruct.
- Phi-4 is cheaper at $0.07 / $0.14 per million input/output tokens, against $0.50 / $2 for Qwen3-Next 80B-A3B Instruct.
- Qwen3-Next 80B-A3B Instruct accepts more context: 131K tokens versus 128K.
Side by side
| Phi-4 | Qwen3-Next 80B-A3B Instruct | |
|---|---|---|
| Provider | Microsoft | Alibaba (Qwen) |
| Noometry Index | 31.2 | 43.0 |
| Released | 2024-12-11 | 2025-09 |
| Weights | Open | Open |
| Context window | 128K | 131K |
| Max output | 4K | 33K |
| Input $ / M tokens | $0.07 | $0.50 |
| Output $ / M tokens | $0.14 | $2 |
| Results tracked | 37 | 25 |
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Category by category
Coding Qwen3-Next 80B-A3B Instruct leads
Phi-4: 34.4 (#239), Qwen3-Next 80B-A3B Instruct: 42.5 (#98)
| Benchmark | Phi-4 | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Coding | 1231 | 1440 |
| BigCodeBench Instruct | 45.5% | — |
| LiveBench Coding | 30.7% | — |
| BigCodeBench Complete | 55.4% | — |
Agentic & Tool Use Not comparable
Phi-4: 22.8 (#128), Qwen3-Next 80B-A3B Instruct: —
| Benchmark | Phi-4 | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | 28.8% | — |
| BALROG | 11.6% | — |
Reasoning Qwen3-Next 80B-A3B Instruct leads
Phi-4: 17.7 (#291), Qwen3-Next 80B-A3B Instruct: 31.1 (#81)
| Benchmark | Phi-4 | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1220 | 1428 |
| Kagi LLM Benchmark | — | 66.7% |
| Chess Puzzles | 1% | — |
| LiveBench Reasoning | 47.8% | — |
| LiveBench Data Analysis | 45.2% | — |
| Epoch Capabilities Index | 130.42 | — |
| LiveBench | 41.6% | — |
Math Qwen3-Next 80B-A3B Instruct leads
Phi-4: 20.8 (#285), Qwen3-Next 80B-A3B Instruct: 38.8 (#126)
| Benchmark | Phi-4 | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Math | 1246 | 1440 |
| OTIS Mock AIME 2024-2025 | 13.8% | — |
| Omni-MATH | — | 46.7% |
| LiveBench Math | 42% | — |
| MATH Level 5 | 64.9% | — |
Knowledge Qwen3-Next 80B-A3B Instruct leads
Phi-4: 32.6 (#209), Qwen3-Next 80B-A3B Instruct: 41.8 (#106)
| Benchmark | Phi-4 | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Vectara Hallucination Rate | 3.7% | 9.3% |
| LMArena Expert | 1203 | 1417 |
| GPQA Diamond | 56.1% | — |
| MMLU-Pro | — | 78.6% |
| Confabulations | 29.4% | — |
| GPQA (HELM) | — | 63% |
| MMLU | 84.8% | — |
Multilingual Qwen3-Next 80B-A3B Instruct leads
Phi-4: 37.2 (#237), Qwen3-Next 80B-A3B Instruct: 52.1 (#93)
| Benchmark | Phi-4 | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Non-English | 1197 | 1407 |
| LMArena Chinese | 1212 | 1460 |
| LMArena French | 1224 | 1413 |
| LMArena German | 1222 | 1417 |
| LMArena Japanese | 1158 | 1395 |
| LMArena Korean | 1151 | 1364 |
| LMArena Russian | 1209 | 1404 |
| LMArena Spanish | 1234 | 1435 |
Instruction Following Qwen3-Next 80B-A3B Instruct leads
Phi-4: 60.4 (#251), Qwen3-Next 80B-A3B Instruct: 70.8 (#159)
| Benchmark | Phi-4 | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Instruction Following | 1201 | 1389 |
| LiveBench Instruction Following | 58.4% | — |
| IFEval | — | 81% |
Long Context Too close to call
Phi-4: 36.9 (#226), Qwen3-Next 80B-A3B Instruct: 37.0 (#223)
| Benchmark | Phi-4 | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Longer Query | 1217 | 1403 |
| Fiction.LiveBench | — | 55.6% |
Writing & Preference Qwen3-Next 80B-A3B Instruct leads
Phi-4: 40.5 (#244), Qwen3-Next 80B-A3B Instruct: 58.0 (#121)
| Benchmark | Phi-4 | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Text | 1217 | 1417 |
| LMArena Creative Writing | 1182 | 1334 |
| LMArena Multi-Turn | 1206 | 1416 |
| Short-Story Creative Writing | 62.6% | — |
| WildBench | — | 80.7% |
| LiveBench Language | 25.6% | — |
Frequently asked questions
Is Phi-4 better than Qwen3-Next 80B-A3B Instruct?
Qwen3-Next 80B-A3B Instruct is the stronger model overall, scoring 43.0 to 31.2 on the Noometry Index. Phi-4 costs 10.0× less per token, which makes it the better buy when Qwen3-Next 80B-A3B Instruct's lead doesn't matter for your workload.
Which is cheaper, Phi-4 or Qwen3-Next 80B-A3B Instruct?
Phi-4 is cheaper. It lists at $0.07 per million input tokens and $0.14 per million output tokens; Qwen3-Next 80B-A3B Instruct lists at $0.50 and $2.
Is Phi-4 or Qwen3-Next 80B-A3B Instruct better for coding?
Qwen3-Next 80B-A3B Instruct scores higher on coding benchmarks: 42.5 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
Qwen3-Next 80B-A3B Instruct does, with 131K tokens against 128K.
How many benchmarks do Phi-4 and Qwen3-Next 80B-A3B Instruct share?
18 benchmarks have published results for both models. Phi-4 has 37 scored results on Noometry and Qwen3-Next 80B-A3B Instruct has 25.