Model comparison
GPT-4.5 vs Qwen2.5 7B Instruct
GPT-4.5 is the stronger model overall, scoring 37.2 to 29.0 on the Noometry Index.
Last verified . 3 shared benchmarks.
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. GPT-4.5 scores higher in 6 categories and Qwen2.5 7B Instruct in 1 category; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-4.5 leads 32.6 to 12.6.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 37.8% for GPT-4.5 and 2.5% for Qwen2.5 7B Instruct.
- Qwen2.5 7B Instruct has downloadable open weights; the other is API-only.
Side by side
| GPT-4.5 | Qwen2.5 7B Instruct | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 37.2 | 29.0 |
| Released | 2025-02-27 | 2024-09 |
| Weights | Proprietary | Open |
| Context window | — | 131K |
| Max output | — | 8K |
| Input $ / M tokens | — | $0.17 |
| Output $ / M tokens | — | $0.70 |
| Results tracked | 42 | 15 |
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Category by category
Coding GPT-4.5 leads
GPT-4.5: 42.2 (#109), Qwen2.5 7B Instruct: 36.5 (#208)
| Benchmark | GPT-4.5 | Qwen2.5 7B Instruct |
|---|---|---|
| Aider Polyglot | 44.9% | — |
| WeirdML | 39.4% | — |
| BigCodeBench Instruct | — | 37.6% |
| LiveBench Coding | 75.2% | — |
| LMArena Coding | 1396 | — |
| BigCodeBench Complete | — | 46.1% |
Agentic & Tool Use GPT-4.5 leads
GPT-4.5: 27.9 (#97), Qwen2.5 7B Instruct: 23.8 (#124)
Reasoning Too close to call
GPT-4.5: 13.9 (#330), Qwen2.5 7B Instruct: 14.8 (#322)
| Benchmark | GPT-4.5 | Qwen2.5 7B Instruct |
|---|---|---|
| Epoch Capabilities Index | 136.74 | 118.51 |
| ARC-AGI-2 | 0.8% | — |
| SimpleBench | 34.5% | — |
| ARC-AGI-1 | 10.3% | — |
| Chess Puzzles | — | 0% |
| EnigmaEval | 3.2% | — |
| LiveBench Reasoning | 71.1% | — |
| LMArena Hard Prompts | 1403 | — |
| DTBench | — | 47.7% |
| LiveBench Data Analysis | 64.3% | — |
| LMCA | — | 6.4% |
| ForecastBench | 61.7 | — |
| LiveBench | 69% | — |
Math GPT-4.5 leads
GPT-4.5: 32.6 (#211), Qwen2.5 7B Instruct: 12.6 (#306)
| Benchmark | GPT-4.5 | Qwen2.5 7B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 37.8% | 2.5% |
| Omni-MATH | — | 29.4% |
| LiveBench Math | 69.3% | — |
| LMArena Math | 1412 | — |
| MATH Level 5 | 78.6% | — |
Knowledge GPT-4.5 leads
GPT-4.5: 32.5 (#211), Qwen2.5 7B Instruct: 17.0 (#286)
| Benchmark | GPT-4.5 | Qwen2.5 7B Instruct |
|---|---|---|
| GPQA Diamond | 68.7% | 35.5% |
| Humanity's Last Exam | 5.4% | — |
| MMLU-Pro | — | 53.9% |
| Confabulations | 13.6% | — |
| GPQA (HELM) | — | 34.1% |
| LMArena Expert | 1394 | — |
| MMLU | — | 72.9% |
Multimodal Not comparable
GPT-4.5: 37.6 (#71), Qwen2.5 7B Instruct: —
| Benchmark | GPT-4.5 | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Vision | 1195 | — |
| VPCT | 45% | — |
Multilingual Not comparable
GPT-4.5: 52.5 (#83), Qwen2.5 7B Instruct: —
| Benchmark | GPT-4.5 | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Non-English | 1413 | — |
| LMArena Chinese | 1421 | — |
| LMArena French | 1418 | — |
| LMArena German | 1457 | — |
| LMArena Japanese | 1416 | — |
| LMArena Korean | 1392 | — |
| LMArena Russian | 1419 | — |
Instruction Following GPT-4.5 leads
GPT-4.5: 72.6 (#134), Qwen2.5 7B Instruct: 63.2 (#231)
| Benchmark | GPT-4.5 | Qwen2.5 7B Instruct |
|---|---|---|
| LiveBench Instruction Following | 72.3% | — |
| IFEval | — | 74.1% |
| LMArena Instruction Following | 1404 | — |
Long Context Not comparable
GPT-4.5: 40.4 (#155), Qwen2.5 7B Instruct: —
| Benchmark | GPT-4.5 | Qwen2.5 7B Instruct |
|---|---|---|
| Fiction.LiveBench | 63.9% | — |
| LMArena Longer Query | 1406 | — |
Writing & Preference GPT-4.5 leads
GPT-4.5: 56.9 (#134), Qwen2.5 7B Instruct: 48.8 (#195)
| Benchmark | GPT-4.5 | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Text | 1417 | — |
| LMArena Creative Writing | 1394 | — |
| Short-Story Creative Writing | 75.6% | — |
| EQ-Bench Creative Writing | 1258 | — |
| WildBench | — | 73.1% |
| LMArena Multi-Turn | 1444 | — |
| LiveBench Language | 61.5% | — |
Frequently asked questions
Is GPT-4.5 better than Qwen2.5 7B Instruct?
GPT-4.5 is the stronger model overall, scoring 37.2 to 29.0 on the Noometry Index.
Is GPT-4.5 or Qwen2.5 7B Instruct better for coding?
GPT-4.5 scores higher on coding benchmarks: 42.2 versus 36.5 in the Noometry coding category.
How many benchmarks do GPT-4.5 and Qwen2.5 7B Instruct share?
3 benchmarks have published results for both models. GPT-4.5 has 42 scored results on Noometry and Qwen2.5 7B Instruct has 15.