Model comparison
Gemini 2.5 Pro vs Qwen2.5-VL 72B Instruct
Gemini 2.5 Pro is the stronger model overall, scoring 45.0 to 29.9 on the Noometry Index.
Last verified . 4 shared benchmarks.
Google
Alibaba (Qwen)Summary
- They share 4 benchmarks with published results for both. Gemini 2.5 Pro scores higher in 3 categories and Qwen2.5-VL 72B Instruct in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in multimodal, where Gemini 2.5 Pro leads 45.2 to 33.5.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 70.3% for Gemini 2.5 Pro and 36% for Qwen2.5-VL 72B Instruct.
- Gemini 2.5 Pro is cheaper at $1.25 / $10 per million input/output tokens, against $2.80 / $8.40 for Qwen2.5-VL 72B Instruct.
- Gemini 2.5 Pro accepts more context: 1.05M tokens versus 131K.
- Qwen2.5-VL 72B Instruct has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Pro | Qwen2.5-VL 72B Instruct | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 45.0 | 29.9 |
| Released | 2025-03-25 | 2024-09 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 131K |
| Max output | 66K | 8K |
| Input $ / M tokens | $1.25 | $2.80 |
| Output $ / M tokens | $10 | $8.40 |
| Results tracked | 78 | 6 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Not comparable
Gemini 2.5 Pro: 42.4 (#101), Qwen2.5-VL 72B Instruct: —
| Benchmark | Gemini 2.5 Pro | Qwen2.5-VL 72B Instruct |
|---|---|---|
| SWE-bench Verified | 57.6% | — |
| SWE-bench Verified (bash only) | 53.6% | — |
| Aider Polyglot | 83.1% | — |
| LMArena WebDev | 1227 | — |
| SciCode | 42.8% | — |
| GSO | 3.9% | — |
| WeirdML | 54% | — |
| LiveBench Coding | 85.9% | — |
| LMArena Coding | 1452 | — |
| CadEval | 64% | — |
| ALE-Bench | 785.52 | — |
| AlgoTune | 1.51 | — |
Agentic & Tool Use Gemini 2.5 Pro leads
Gemini 2.5 Pro: 29.2 (#88), Qwen2.5-VL 72B Instruct: 18.6 (#144)
| Benchmark | Gemini 2.5 Pro | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Terminal-Bench | 32.6% | — |
| GDPval | 23.3% | — |
| Remote Labor Index | 0.8% | — |
| TheAgentCompany | 30.3% | — |
| τ²-bench Banking | 13.7% | — |
| DeepResearch Bench | 42.8% | — |
| OSWorld | — | 5% |
| BALROG | 43.3% | — |
| LMArena Search | 1142 | — |
| METR Time Horizons | 55.4% | — |
| Vending-Bench 2 | 573.64 | — |
Reasoning Gemini 2.5 Pro leads
Gemini 2.5 Pro: 28.8 (#99), Qwen2.5-VL 72B Instruct: 20.7 (#233)
| Benchmark | Gemini 2.5 Pro | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 70.3% | 36% |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 62.4% | — |
| ARC-AGI-1 | 41% | — |
| CritPt | 2% | — |
| Chess Puzzles | 20% | — |
| EnigmaEval | 5.6% | — |
| LiveBench Reasoning | 89.8% | — |
| LMArena Hard Prompts | 1455 | — |
| DTBench | 82.4% | — |
| LiveBench Data Analysis | 79.9% | — |
| LMCA | 34.8% | — |
| Epoch Capabilities Index | 145.32 | — |
| ForecastBench | 61.3 | — |
| LiveBench | 82.3% | — |
Math Not comparable
Gemini 2.5 Pro: 32.5 (#213), Qwen2.5-VL 72B Instruct: —
| Benchmark | Gemini 2.5 Pro | Qwen2.5-VL 72B Instruct |
|---|---|---|
| FrontierMath (Tiers 1-3) | 24.6% | — |
| FrontierMath Tier 4 | 0% | — |
| OTIS Mock AIME 2024-2025 | 84.7% | — |
| Omni-MATH | 41.6% | — |
| LiveBench Math | 90.2% | — |
| LMArena Math | 1450 | — |
| MATH Level 5 | 95.9% | — |
| FrontierMath (Feb 2025 set) | 14.1% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Not comparable
Gemini 2.5 Pro: 56.0 (#46), Qwen2.5-VL 72B Instruct: —
| Benchmark | Gemini 2.5 Pro | Qwen2.5-VL 72B Instruct |
|---|---|---|
| GPQA Diamond | 85.3% | — |
| Humanity's Last Exam | 21.6% | — |
| MMLU-Pro | 86.3% | — |
| Confabulations | 10.6% | — |
| Vectara Hallucination Rate | 7% | — |
| GPQA (HELM) | 74.9% | — |
| LMArena Expert | 1452 | — |
Multimodal Gemini 2.5 Pro leads
Gemini 2.5 Pro: 45.2 (#18), Qwen2.5-VL 72B Instruct: 33.5 (#97)
| Benchmark | Gemini 2.5 Pro | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Vision | 1263 | 1107 |
| GeoBench | 86% | 62% |
| SpatialViz-Bench | 44.7% | 33.3% |
| Video-MME | — | 73.5% |
| VPCT | 48% | — |
| LMArena Document | 1421 | — |
Multilingual Not comparable
Gemini 2.5 Pro: 55.3 (#31), Qwen2.5-VL 72B Instruct: —
| Benchmark | Gemini 2.5 Pro | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Non-English | 1451 | — |
| LMArena Chinese | 1507 | — |
| LMArena French | 1472 | — |
| LMArena German | 1487 | — |
| LMArena Japanese | 1461 | — |
| LMArena Korean | 1434 | — |
| LMArena Russian | 1461 | — |
| LMArena Spanish | 1473 | — |
Instruction Following Not comparable
Gemini 2.5 Pro: 75.0 (#75), Qwen2.5-VL 72B Instruct: —
| Benchmark | Gemini 2.5 Pro | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LiveBench Instruction Following | 80.6% | — |
| IFEval | 84% | — |
| LMArena Instruction Following | 1437 | — |
Long Context Not comparable
Gemini 2.5 Pro: 59.8 (#5), Qwen2.5-VL 72B Instruct: —
| Benchmark | Gemini 2.5 Pro | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Fiction.LiveBench | 91.7% | — |
| LMArena Longer Query | 1449 | — |
Writing & Preference Not comparable
Gemini 2.5 Pro: 63.7 (#62), Qwen2.5-VL 72B Instruct: —
| Benchmark | Gemini 2.5 Pro | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Text | 1458 | — |
| LMArena Creative Writing | 1454 | — |
| Short-Story Creative Writing | 83.8% | — |
| EQ-Bench Creative Writing | 1421 | — |
| WildBench | 85.7% | — |
| LMArena Multi-Turn | 1453 | — |
| LiveBench Language | 67.8% | — |
Frequently asked questions
Is Gemini 2.5 Pro better than Qwen2.5-VL 72B Instruct?
Gemini 2.5 Pro is the stronger model overall, scoring 45.0 to 29.9 on the Noometry Index.
Which is cheaper, Gemini 2.5 Pro or Qwen2.5-VL 72B Instruct?
Gemini 2.5 Pro is cheaper. It lists at $1.25 per million input tokens and $10 per million output tokens; Qwen2.5-VL 72B Instruct lists at $2.80 and $8.40.
Which has the bigger context window?
Gemini 2.5 Pro does, with 1.05M tokens against 131K.
How many benchmarks do Gemini 2.5 Pro and Qwen2.5-VL 72B Instruct share?
4 benchmarks have published results for both models. Gemini 2.5 Pro has 78 scored results on Noometry and Qwen2.5-VL 72B Instruct has 6.