Model comparison
phi-3-medium 14B vs Qwen3-Next 80B-A3B Instruct
Qwen3-Next 80B-A3B Instruct is the stronger model overall, scoring 43.0 to 29.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
Microsoft
Alibaba (Qwen)Summary
- The widest gap is in knowledge, where Qwen3-Next 80B-A3B Instruct leads 41.8 to 9.1.
Side by side
| phi-3-medium 14B | Qwen3-Next 80B-A3B Instruct | |
|---|---|---|
| Provider | Microsoft | Alibaba (Qwen) |
| Noometry Index | 29.7 | 43.0 |
| Released | 2024-04-23 | 2025-09 |
| Weights | Open | Open |
| Context window | — | 131K |
| Max output | — | 33K |
| Input $ / M tokens | — | $0.50 |
| Output $ / M tokens | — | $2 |
| Results tracked | 13 | 25 |
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Category by category
Coding Qwen3-Next 80B-A3B Instruct leads
phi-3-medium 14B: 36.8 (#201), Qwen3-Next 80B-A3B Instruct: 42.5 (#98)
| Benchmark | phi-3-medium 14B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| BigCodeBench Instruct | 37.6% | — |
| LMArena Coding | — | 1440 |
| BigCodeBench Complete | 48.7% | — |
Reasoning Not comparable
phi-3-medium 14B: —, Qwen3-Next 80B-A3B Instruct: 31.1 (#81)
| Benchmark | phi-3-medium 14B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Kagi LLM Benchmark | — | 66.7% |
| LMArena Hard Prompts | — | 1428 |
| Adversarial NLI | 55.8% | — |
| BIG-Bench Hard | 81.4% | — |
| Epoch Capabilities Index | 121.23 | — |
| HellaSwag | 82.4% | — |
| WinoGrande | 81.5% | — |
Math Qwen3-Next 80B-A3B Instruct leads
phi-3-medium 14B: 27.3 (#250), Qwen3-Next 80B-A3B Instruct: 38.8 (#126)
| Benchmark | phi-3-medium 14B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Omni-MATH | — | 46.7% |
| LMArena Math | — | 1440 |
| MATH Level 5 | 17.6% | — |
Knowledge Qwen3-Next 80B-A3B Instruct leads
phi-3-medium 14B: 9.1 (#306), Qwen3-Next 80B-A3B Instruct: 41.8 (#106)
| Benchmark | phi-3-medium 14B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| GPQA Diamond | 27.6% | — |
| MMLU-Pro | — | 78.6% |
| Vectara Hallucination Rate | — | 9.3% |
| GPQA (HELM) | — | 63% |
| LMArena Expert | — | 1417 |
| ARC (AI2) Challenge | 91.6% | — |
| MMLU | 78% | — |
| OpenBookQA | 87.4% | — |
| TriviaQA | 73.9% | — |
Multilingual Not comparable
phi-3-medium 14B: —, Qwen3-Next 80B-A3B Instruct: 52.1 (#93)
| Benchmark | phi-3-medium 14B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Non-English | — | 1407 |
| LMArena Chinese | — | 1460 |
| LMArena French | — | 1413 |
| LMArena German | — | 1417 |
| LMArena Japanese | — | 1395 |
| LMArena Korean | — | 1364 |
| LMArena Russian | — | 1404 |
| LMArena Spanish | — | 1435 |
Instruction Following Not comparable
phi-3-medium 14B: —, Qwen3-Next 80B-A3B Instruct: 70.8 (#159)
| Benchmark | phi-3-medium 14B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| IFEval | — | 81% |
| LMArena Instruction Following | — | 1389 |
Long Context Not comparable
phi-3-medium 14B: —, Qwen3-Next 80B-A3B Instruct: 37.0 (#223)
| Benchmark | phi-3-medium 14B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Fiction.LiveBench | — | 55.6% |
| LMArena Longer Query | — | 1403 |
Writing & Preference Not comparable
phi-3-medium 14B: —, Qwen3-Next 80B-A3B Instruct: 58.0 (#121)
| Benchmark | phi-3-medium 14B | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Text | — | 1417 |
| LMArena Creative Writing | — | 1334 |
| WildBench | — | 80.7% |
| LMArena Multi-Turn | — | 1416 |
Frequently asked questions
Is phi-3-medium 14B better than Qwen3-Next 80B-A3B Instruct?
Qwen3-Next 80B-A3B Instruct is the stronger model overall, scoring 43.0 to 29.7 on the Noometry Index.
Is phi-3-medium 14B or Qwen3-Next 80B-A3B Instruct better for coding?
Qwen3-Next 80B-A3B Instruct scores higher on coding benchmarks: 42.5 versus 36.8 in the Noometry coding category.
How many benchmarks do phi-3-medium 14B and Qwen3-Next 80B-A3B Instruct share?
0 benchmarks have published results for both models. phi-3-medium 14B has 13 scored results on Noometry and Qwen3-Next 80B-A3B Instruct has 25.