Model comparison
Gemini 2.5 Flash vs Qwen2.5 32B Instruct
Gemini 2.5 Flash is the stronger model overall, scoring 39.0 to 29.7 on the Noometry Index.
Last verified . 2 shared benchmarks.
Google
Alibaba (Qwen)Summary
- They share 2 benchmarks with published results for both. Gemini 2.5 Flash scores higher in 2 categories and Qwen2.5 32B Instruct in 2 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where Gemini 2.5 Flash leads 38.1 to 15.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 73.1% for Gemini 2.5 Flash and 7.4% for Qwen2.5 32B Instruct.
- Gemini 2.5 Flash is cheaper at $0.30 / $2.50 per million input/output tokens, against $0.70 / $2.80 for Qwen2.5 32B Instruct.
- Gemini 2.5 Flash accepts more context: 1.05M tokens versus 131K.
- Qwen2.5 32B Instruct has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Flash | Qwen2.5 32B Instruct | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 39.0 | 29.7 |
| Released | 2025-04-17 | 2024-09 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 131K |
| Max output | 66K | 8K |
| Input $ / M tokens | $0.30 | $0.70 |
| Output $ / M tokens | $2.50 | $2.80 |
| Results tracked | 54 | 7 |
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Category by category
Coding Qwen2.5 32B Instruct leads
Gemini 2.5 Flash: 35.5 (#210), Qwen2.5 32B Instruct: 38.1 (#165)
| Benchmark | Gemini 2.5 Flash | Qwen2.5 32B Instruct |
|---|---|---|
| SWE-bench Verified (bash only) | 28.7% | — |
| Aider Polyglot | 55.1% | — |
| WeirdML | 41.9% | — |
| BigCodeBench Instruct | — | 45% |
| LMArena Coding | 1424 | — |
| BigCodeBench Complete | — | 52.3% |
| ALE-Bench | 661.88 | — |
Agentic & Tool Use Not comparable
Gemini 2.5 Flash: 30.6 (#67), Qwen2.5 32B Instruct: —
| Benchmark | Gemini 2.5 Flash | Qwen2.5 32B Instruct |
|---|---|---|
| Terminal-Bench | 17.1% | — |
| Berkeley Function Calling Leaderboard | 56.2% | — |
| TheAgentCompany | 41.1% | — |
| BALROG | 33.5% | — |
| Vending-Bench 2 | 548.84 | — |
Reasoning Too close to call
Gemini 2.5 Flash: 18.2 (#271), Qwen2.5 32B Instruct: 18.5 (#262)
| Benchmark | Gemini 2.5 Flash | Qwen2.5 32B Instruct |
|---|---|---|
| Epoch Capabilities Index | 143.04 | 128.52 |
| ARC-AGI-2 | 2.5% | — |
| SimpleBench | 41.2% | — |
| Kagi LLM Benchmark | 56.8% | — |
| ARC-AGI-1 | 33.3% | — |
| CritPt | 1.1% | — |
| Chess Puzzles | — | 0% |
| EnigmaEval | 2.7% | — |
| LMArena Hard Prompts | 1422 | — |
| DTBench | 76.5% | — |
| LMCA | 27.5% | — |
| ForecastBench | 60.6 | — |
Math Gemini 2.5 Flash leads
Gemini 2.5 Flash: 38.1 (#87), Qwen2.5 32B Instruct: 15.3 (#289)
| Benchmark | Gemini 2.5 Flash | Qwen2.5 32B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 73.1% | 7.4% |
| Omni-MATH | 38.5% | — |
| LMArena Math | 1415 | — |
| MATH Level 5 | — | 56.1% |
| FrontierMath (Feb 2025 set) | 4.8% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Gemini 2.5 Flash leads
Gemini 2.5 Flash: 36.1 (#162), Qwen2.5 32B Instruct: 24.9 (#259)
| Benchmark | Gemini 2.5 Flash | Qwen2.5 32B Instruct |
|---|---|---|
| GPQA Diamond | — | 46.1% |
| Humanity's Last Exam | 12.1% | — |
| MMLU-Pro | 63.9% | — |
| Confabulations | 16.8% | — |
| Vectara Hallucination Rate | 7.8% | — |
| GPQA (HELM) | 39% | — |
| LMArena Expert | 1426 | — |
Multimodal Not comparable
Gemini 2.5 Flash: 41.2 (#31), Qwen2.5 32B Instruct: —
| Benchmark | Gemini 2.5 Flash | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Vision | 1254 | — |
| GeoBench | 76% | — |
| VPCT | 46.2% | — |
| SpatialViz-Bench | 36.9% | — |
Multilingual Not comparable
Gemini 2.5 Flash: 52.5 (#83), Qwen2.5 32B Instruct: —
| Benchmark | Gemini 2.5 Flash | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Non-English | 1410 | — |
| LMArena Chinese | 1450 | — |
| LMArena French | 1433 | — |
| LMArena German | 1419 | — |
| LMArena Japanese | 1403 | — |
| LMArena Korean | 1385 | — |
| LMArena Russian | 1415 | — |
| LMArena Spanish | 1421 | — |
Instruction Following Not comparable
Gemini 2.5 Flash: 75.9 (#50), Qwen2.5 32B Instruct: —
| Benchmark | Gemini 2.5 Flash | Qwen2.5 32B Instruct |
|---|---|---|
| IFEval | 89.8% | — |
| LMArena Instruction Following | 1405 | — |
Long Context Not comparable
Gemini 2.5 Flash: 47.5 (#16), Qwen2.5 32B Instruct: —
| Benchmark | Gemini 2.5 Flash | Qwen2.5 32B Instruct |
|---|---|---|
| Fiction.LiveBench | 77.8% | — |
| LMArena Longer Query | 1419 | — |
Writing & Preference Not comparable
Gemini 2.5 Flash: 54.0 (#153), Qwen2.5 32B Instruct: —
| Benchmark | Gemini 2.5 Flash | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Text | 1417 | — |
| LMArena Creative Writing | 1400 | — |
| Short-Story Creative Writing | 76.5% | — |
| EQ-Bench Creative Writing | 1137 | — |
| WildBench | 81.7% | — |
| LMArena Multi-Turn | 1408 | — |
Frequently asked questions
Is Gemini 2.5 Flash better than Qwen2.5 32B Instruct?
Gemini 2.5 Flash is the stronger model overall, scoring 39.0 to 29.7 on the Noometry Index.
Which is cheaper, Gemini 2.5 Flash or Qwen2.5 32B Instruct?
Gemini 2.5 Flash is cheaper. It lists at $0.30 per million input tokens and $2.50 per million output tokens; Qwen2.5 32B Instruct lists at $0.70 and $2.80.
Is Gemini 2.5 Flash or Qwen2.5 32B Instruct better for coding?
Qwen2.5 32B Instruct scores higher on coding benchmarks: 38.1 versus 35.5 in the Noometry coding category.
Which has the bigger context window?
Gemini 2.5 Flash does, with 1.05M tokens against 131K.
How many benchmarks do Gemini 2.5 Flash and Qwen2.5 32B Instruct share?
2 benchmarks have published results for both models. Gemini 2.5 Flash has 54 scored results on Noometry and Qwen2.5 32B Instruct has 7.