Model comparison
GPT-6 Sol vs phi-3-medium 14B
GPT-6 Sol is the stronger model overall, scoring 61.8 to 29.7 on the Noometry Index.
Last verified . 2 shared benchmarks.
MicrosoftSummary
- They share 2 benchmarks with published results for both. GPT-6 Sol scores higher in 3 categories and phi-3-medium 14B in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Sol leads 87.2 to 27.3.
- The biggest single-benchmark swing is GPQA Diamond: 94.3% for GPT-6 Sol and 27.6% for phi-3-medium 14B.
- phi-3-medium 14B has downloadable open weights; the other is API-only.
Side by side
| GPT-6 Sol | phi-3-medium 14B | |
|---|---|---|
| Provider | OpenAI | Microsoft |
| Noometry Index | 61.8 | 29.7 |
| Released | 2026-09-22 | 2024-04-23 |
| Weights | Proprietary | Open |
| Context window | 1.05M | — |
| Max output | 128K | — |
| Input $ / M tokens | $2 | — |
| Output $ / M tokens | $10 | — |
| Results tracked | 45 | 13 |
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Category by category
Coding GPT-6 Sol leads
GPT-6 Sol: 60.1 (#11), phi-3-medium 14B: 36.8 (#201)
| Benchmark | GPT-6 Sol | phi-3-medium 14B |
|---|---|---|
| DeepSWE | 68.8% | — |
| FrontierCode | 49.3% | — |
| LMArena WebDev | 1688 | — |
| SciCode | 57.6% | — |
| BigCodeBench Instruct | — | 37.6% |
| LMArena Coding | 1447 | — |
| BigCodeBench Complete | — | 48.7% |
| ALE-Bench | 2,462 | — |
Agentic & Tool Use Not comparable
GPT-6 Sol: 37.2 (#36), phi-3-medium 14B: —
| Benchmark | GPT-6 Sol | phi-3-medium 14B |
|---|---|---|
| APEX-Agents | 54.3% | — |
| GDP.pdf | 26.4% | — |
| Vending-Bench 2 | 14,428 | — |
Reasoning Not comparable
GPT-6 Sol: 74.0 (#9), phi-3-medium 14B: —
| Benchmark | GPT-6 Sol | phi-3-medium 14B |
|---|---|---|
| Epoch Capabilities Index | 162.72 | 121.23 |
| ARC-AGI-2 | 89.6% | — |
| NYT Connections (extended) | 90.1% | — |
| ARC-AGI-1 | 95.5% | — |
| CritPt | 30.9% | — |
| EBR-Bench | 53.3% | — |
| LMArena Hard Prompts | 1418 | — |
| Mystery Game Puzzles | 56% | — |
| DTBench | 97.3% | — |
| LMCA | 59.1% | — |
| Adversarial NLI | — | 55.8% |
| BIG-Bench Hard | — | 81.4% |
| HellaSwag | — | 82.4% |
| WinoGrande | — | 81.5% |
Math GPT-6 Sol leads
GPT-6 Sol: 87.2 (#7), phi-3-medium 14B: 27.3 (#250)
| Benchmark | GPT-6 Sol | phi-3-medium 14B |
|---|---|---|
| FrontierMath (Tiers 1-3) | 89.8% | — |
| FrontierMath Tier 4 | 90% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 83% | — |
| LMArena Math | 1402 | — |
| MATH Level 5 | — | 17.6% |
Knowledge GPT-6 Sol leads
GPT-6 Sol: 64.8 (#15), phi-3-medium 14B: 9.1 (#306)
| Benchmark | GPT-6 Sol | phi-3-medium 14B |
|---|---|---|
| GPQA Diamond | 94.3% | 27.6% |
| SimpleQA Verified | 60.7% | — |
| Vectara Hallucination Rate | 6.5% | — |
| LMArena Expert | 1439 | — |
| ARC (AI2) Challenge | — | 91.6% |
| MMLU | — | 78% |
| OpenBookQA | — | 87.4% |
| TriviaQA | — | 73.9% |
Multimodal Not comparable
GPT-6 Sol: 47.6 (#10), phi-3-medium 14B: —
| Benchmark | GPT-6 Sol | phi-3-medium 14B |
|---|---|---|
| LMArena Vision | 1245 | — |
| Blueprint-Bench 2 | 36.9% | — |
| Furniture Assembly | 58.3% | — |
Multilingual Not comparable
GPT-6 Sol: 50.5 (#118), phi-3-medium 14B: —
| Benchmark | GPT-6 Sol | phi-3-medium 14B |
|---|---|---|
| LMArena Non-English | 1385 | — |
| LMArena Chinese | 1405 | — |
| LMArena French | 1410 | — |
| LMArena German | 1390 | — |
| LMArena Japanese | 1385 | — |
| LMArena Korean | 1341 | — |
| LMArena Russian | 1401 | — |
| LMArena Spanish | 1384 | — |
Instruction Following Not comparable
GPT-6 Sol: 74.5 (#94), phi-3-medium 14B: —
| Benchmark | GPT-6 Sol | phi-3-medium 14B |
|---|---|---|
| LMArena Instruction Following | 1412 | — |
Long Context Not comparable
GPT-6 Sol: 43.1 (#108), phi-3-medium 14B: —
| Benchmark | GPT-6 Sol | phi-3-medium 14B |
|---|---|---|
| LMArena Longer Query | 1411 | — |
Writing & Preference Not comparable
GPT-6 Sol: 71.9 (#18), phi-3-medium 14B: —
| Benchmark | GPT-6 Sol | phi-3-medium 14B |
|---|---|---|
| LMArena Text | 1395 | — |
| LMArena Creative Writing | 1378 | — |
| EQ-Bench Creative Writing | 2125 | — |
| LMArena Multi-Turn | 1412 | — |
Frequently asked questions
Is GPT-6 Sol better than phi-3-medium 14B?
GPT-6 Sol is the stronger model overall, scoring 61.8 to 29.7 on the Noometry Index.
Is GPT-6 Sol or phi-3-medium 14B better for coding?
GPT-6 Sol scores higher on coding benchmarks: 60.1 versus 36.8 in the Noometry coding category.
How many benchmarks do GPT-6 Sol and phi-3-medium 14B share?
2 benchmarks have published results for both models. GPT-6 Sol has 45 scored results on Noometry and phi-3-medium 14B has 13.