Model comparison
Gemini 2.5 Pro vs Qwen2.5 7B Instruct
Gemini 2.5 Pro is the stronger model overall, scoring 45.0 to 29.0 on the Noometry Index. Qwen2.5 7B Instruct costs 11× less per token, which makes it the better buy when Gemini 2.5 Pro's lead doesn't matter for your workload.
Last verified . 12 shared benchmarks.
Google
Alibaba (Qwen)Summary
- They share 12 benchmarks with published results for both. Gemini 2.5 Pro scores higher in 7 categories and Qwen2.5 7B Instruct in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Gemini 2.5 Pro leads 56.0 to 17.0.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 84.7% for Gemini 2.5 Pro and 2.5% for Qwen2.5 7B Instruct.
- Qwen2.5 7B Instruct is cheaper at $0.17 / $0.70 per million input/output tokens, against $1.25 / $10 for Gemini 2.5 Pro.
- Gemini 2.5 Pro accepts more context: 1.05M tokens versus 131K.
- Qwen2.5 7B Instruct has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Pro | Qwen2.5 7B Instruct | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 45.0 | 29.0 |
| Released | 2025-03-25 | 2024-09 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 131K |
| Max output | 66K | 8K |
| Input $ / M tokens | $1.25 | $0.17 |
| Output $ / M tokens | $10 | $0.70 |
| Results tracked | 78 | 15 |
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Category by category
Coding Gemini 2.5 Pro leads
Gemini 2.5 Pro: 42.4 (#101), Qwen2.5 7B Instruct: 36.5 (#208)
| Benchmark | Gemini 2.5 Pro | Qwen2.5 7B 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% | — |
| BigCodeBench Instruct | — | 37.6% |
| LiveBench Coding | 85.9% | — |
| LMArena Coding | 1452 | — |
| BigCodeBench Complete | — | 46.1% |
| 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 7B Instruct: 23.8 (#124)
| Benchmark | Gemini 2.5 Pro | Qwen2.5 7B Instruct |
|---|---|---|
| BALROG | 43.3% | 7.8% |
| Terminal-Bench | 32.6% | — |
| GDPval | 23.3% | — |
| Remote Labor Index | 0.8% | — |
| TheAgentCompany | 30.3% | — |
| τ²-bench Banking | 13.7% | — |
| DeepResearch Bench | 42.8% | — |
| 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 7B Instruct: 14.8 (#322)
| Benchmark | Gemini 2.5 Pro | Qwen2.5 7B Instruct |
|---|---|---|
| Chess Puzzles | 20% | 0% |
| DTBench | 82.4% | 47.7% |
| LMCA | 34.8% | 6.4% |
| Epoch Capabilities Index | 145.32 | 118.51 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 62.4% | — |
| Kagi LLM Benchmark | 70.3% | — |
| ARC-AGI-1 | 41% | — |
| CritPt | 2% | — |
| EnigmaEval | 5.6% | — |
| LiveBench Reasoning | 89.8% | — |
| LMArena Hard Prompts | 1455 | — |
| LiveBench Data Analysis | 79.9% | — |
| ForecastBench | 61.3 | — |
| LiveBench | 82.3% | — |
Math Gemini 2.5 Pro leads
Gemini 2.5 Pro: 32.5 (#213), Qwen2.5 7B Instruct: 12.6 (#306)
| Benchmark | Gemini 2.5 Pro | Qwen2.5 7B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 84.7% | 2.5% |
| Omni-MATH | 41.6% | 29.4% |
| FrontierMath (Tiers 1-3) | 24.6% | — |
| FrontierMath Tier 4 | 0% | — |
| 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 Gemini 2.5 Pro leads
Gemini 2.5 Pro: 56.0 (#46), Qwen2.5 7B Instruct: 17.0 (#286)
| Benchmark | Gemini 2.5 Pro | Qwen2.5 7B Instruct |
|---|---|---|
| GPQA Diamond | 85.3% | 35.5% |
| MMLU-Pro | 86.3% | 53.9% |
| GPQA (HELM) | 74.9% | 34.1% |
| Humanity's Last Exam | 21.6% | — |
| Confabulations | 10.6% | — |
| Vectara Hallucination Rate | 7% | — |
| LMArena Expert | 1452 | — |
| MMLU | — | 72.9% |
Multimodal Not comparable
Gemini 2.5 Pro: 45.2 (#18), Qwen2.5 7B Instruct: —
| Benchmark | Gemini 2.5 Pro | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Vision | 1263 | — |
| GeoBench | 86% | — |
| VPCT | 48% | — |
| LMArena Document | 1421 | — |
| SpatialViz-Bench | 44.7% | — |
Multilingual Not comparable
Gemini 2.5 Pro: 55.3 (#31), Qwen2.5 7B Instruct: —
| Benchmark | Gemini 2.5 Pro | Qwen2.5 7B 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 Gemini 2.5 Pro leads
Gemini 2.5 Pro: 75.0 (#75), Qwen2.5 7B Instruct: 63.2 (#231)
| Benchmark | Gemini 2.5 Pro | Qwen2.5 7B Instruct |
|---|---|---|
| IFEval | 84% | 74.1% |
| LiveBench Instruction Following | 80.6% | — |
| LMArena Instruction Following | 1437 | — |
Long Context Not comparable
Gemini 2.5 Pro: 59.8 (#5), Qwen2.5 7B Instruct: —
| Benchmark | Gemini 2.5 Pro | Qwen2.5 7B Instruct |
|---|---|---|
| Fiction.LiveBench | 91.7% | — |
| LMArena Longer Query | 1449 | — |
Writing & Preference Gemini 2.5 Pro leads
Gemini 2.5 Pro: 63.7 (#62), Qwen2.5 7B Instruct: 48.8 (#195)
| Benchmark | Gemini 2.5 Pro | Qwen2.5 7B Instruct |
|---|---|---|
| WildBench | 85.7% | 73.1% |
| LMArena Text | 1458 | — |
| LMArena Creative Writing | 1454 | — |
| Short-Story Creative Writing | 83.8% | — |
| EQ-Bench Creative Writing | 1421 | — |
| LMArena Multi-Turn | 1453 | — |
| LiveBench Language | 67.8% | — |
Frequently asked questions
Is Gemini 2.5 Pro better than Qwen2.5 7B Instruct?
Gemini 2.5 Pro is the stronger model overall, scoring 45.0 to 29.0 on the Noometry Index. Qwen2.5 7B Instruct costs 11× less per token, which makes it the better buy when Gemini 2.5 Pro's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Pro or Qwen2.5 7B Instruct?
Qwen2.5 7B Instruct is cheaper. It lists at $0.17 per million input tokens and $0.70 per million output tokens; Gemini 2.5 Pro lists at $1.25 and $10.
Is Gemini 2.5 Pro or Qwen2.5 7B Instruct better for coding?
Gemini 2.5 Pro scores higher on coding benchmarks: 42.4 versus 36.5 in the Noometry coding category.
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 7B Instruct share?
12 benchmarks have published results for both models. Gemini 2.5 Pro has 78 scored results on Noometry and Qwen2.5 7B Instruct has 15.