Model comparison
Gemini 2.5 Flash vs Qwen3.5-9B
Gemini 2.5 Flash is the stronger model overall, scoring 39.0 to 33.3 on the Noometry Index. Qwen3.5-9B costs 7.6× less per token, which makes it the better buy when Gemini 2.5 Flash's lead doesn't matter for your workload.
Last verified . 6 shared benchmarks.
Google
Alibaba (Qwen)Summary
- They share 6 benchmarks with published results for both. Gemini 2.5 Flash scores higher in 3 categories and Qwen3.5-9B in 2 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Gemini 2.5 Flash leads 30.6 to 14.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 73.1% for Gemini 2.5 Flash and 61.7% for Qwen3.5-9B.
- Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $0.30 / $2.50 for Gemini 2.5 Flash.
- Gemini 2.5 Flash accepts more context: 1.05M tokens versus 262K.
- Qwen3.5-9B has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Flash | Qwen3.5-9B | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 39.0 | 33.3 |
| Released | 2025-04-17 | 2026-02-23 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 66K | 66K |
| Input $ / M tokens | $0.30 | $0.10 |
| Output $ / M tokens | $2.50 | $0.15 |
| Results tracked | 54 | 10 |
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Category by category
Coding Too close to call
Gemini 2.5 Flash: 35.5 (#210), Qwen3.5-9B: 35.3 (#213)
| Benchmark | Gemini 2.5 Flash | Qwen3.5-9B |
|---|---|---|
| SWE-bench Verified (bash only) | 28.7% | — |
| Aider Polyglot | 55.1% | — |
| SciCode | — | 27.5% |
| WeirdML | 41.9% | — |
| LMArena Coding | 1424 | — |
| ALE-Bench | 661.88 | — |
Agentic & Tool Use Gemini 2.5 Flash leads
Gemini 2.5 Flash: 30.6 (#67), Qwen3.5-9B: 14.4 (#143)
| Benchmark | Gemini 2.5 Flash | Qwen3.5-9B |
|---|---|---|
| Terminal-Bench | 17.1% | 9.2% |
| Berkeley Function Calling Leaderboard | 56.2% | — |
| TheAgentCompany | 41.1% | — |
| BALROG | 33.5% | — |
| Vending-Bench 2 | 548.84 | — |
Reasoning Qwen3.5-9B leads
Gemini 2.5 Flash: 18.2 (#271), Qwen3.5-9B: 22.5 (#178)
| Benchmark | Gemini 2.5 Flash | Qwen3.5-9B |
|---|---|---|
| CritPt | 1.1% | 0.3% |
| DTBench | 76.5% | 71.2% |
| LMCA | 27.5% | 24.5% |
| Epoch Capabilities Index | 143.04 | 139.45 |
| ARC-AGI-2 | 2.5% | — |
| SimpleBench | 41.2% | — |
| Kagi LLM Benchmark | 56.8% | — |
| ARC-AGI-1 | 33.3% | — |
| Chess Puzzles | — | 12% |
| EnigmaEval | 2.7% | — |
| LMArena Hard Prompts | 1422 | — |
| ForecastBench | 60.6 | — |
Math Gemini 2.5 Flash leads
Gemini 2.5 Flash: 38.1 (#87), Qwen3.5-9B: 33.5 (#174)
| Benchmark | Gemini 2.5 Flash | Qwen3.5-9B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 73.1% | 61.7% |
| MathArena Final-Answer Competitions | — | 48.5% |
| Omni-MATH | 38.5% | — |
| LMArena Math | 1415 | — |
| FrontierMath (Feb 2025 set) | 4.8% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Qwen3.5-9B leads
Gemini 2.5 Flash: 36.1 (#162), Qwen3.5-9B: 46.0 (#77)
| Benchmark | Gemini 2.5 Flash | Qwen3.5-9B |
|---|---|---|
| GPQA Diamond | — | 79% |
| 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), Qwen3.5-9B: —
| Benchmark | Gemini 2.5 Flash | Qwen3.5-9B |
|---|---|---|
| LMArena Vision | 1254 | — |
| GeoBench | 76% | — |
| VPCT | 46.2% | — |
| SpatialViz-Bench | 36.9% | — |
Multilingual Not comparable
Gemini 2.5 Flash: 52.5 (#83), Qwen3.5-9B: —
| Benchmark | Gemini 2.5 Flash | Qwen3.5-9B |
|---|---|---|
| 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), Qwen3.5-9B: —
| Benchmark | Gemini 2.5 Flash | Qwen3.5-9B |
|---|---|---|
| IFEval | 89.8% | — |
| LMArena Instruction Following | 1405 | — |
Long Context Not comparable
Gemini 2.5 Flash: 47.5 (#16), Qwen3.5-9B: —
| Benchmark | Gemini 2.5 Flash | Qwen3.5-9B |
|---|---|---|
| Fiction.LiveBench | 77.8% | — |
| LMArena Longer Query | 1419 | — |
Writing & Preference Not comparable
Gemini 2.5 Flash: 54.0 (#153), Qwen3.5-9B: —
| Benchmark | Gemini 2.5 Flash | Qwen3.5-9B |
|---|---|---|
| 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 Qwen3.5-9B?
Gemini 2.5 Flash is the stronger model overall, scoring 39.0 to 33.3 on the Noometry Index. Qwen3.5-9B costs 7.6× less per token, which makes it the better buy when Gemini 2.5 Flash's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Flash or Qwen3.5-9B?
Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; Gemini 2.5 Flash lists at $0.30 and $2.50.
Is Gemini 2.5 Flash or Qwen3.5-9B better for coding?
They score almost the same on coding (35.5 vs 35.3); test both on your own repository before choosing.
Which has the bigger context window?
Gemini 2.5 Flash does, with 1.05M tokens against 262K.
How many benchmarks do Gemini 2.5 Flash and Qwen3.5-9B share?
6 benchmarks have published results for both models. Gemini 2.5 Flash has 54 scored results on Noometry and Qwen3.5-9B has 10.