Model comparison
Gemini 2.5 Flash vs Qwen3.5 122B-A10B
Qwen3.5 122B-A10B is the stronger model overall, scoring 42.1 to 39.3 on the Noometry Index.
Last verified . 22 shared benchmarks.
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Alibaba (Qwen)Summary
- They share 22 benchmarks with published results for both. Gemini 2.5 Flash scores higher in 5 categories and Qwen3.5 122B-A10B in 4 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.5 122B-A10B leads 27.2 to 18.1.
- The biggest single-benchmark swing is DTBench: 76.5% for Gemini 2.5 Flash and 84.3% for Qwen3.5 122B-A10B.
- Gemini 2.5 Flash is cheaper at $0.30 / $2.50 per million input/output tokens, against $0.40 / $3.20 for Qwen3.5 122B-A10B.
- Gemini 2.5 Flash accepts more context: 1.05M tokens versus 262K.
- Qwen3.5 122B-A10B has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Flash | Qwen3.5 122B-A10B | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 39.3 | 42.1 |
| Released | 2025-04-17 | 2026-02-23 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 66K | 66K |
| Input $ / M tokens | $0.30 | $0.40 |
| Output $ / M tokens | $2.50 | $3.20 |
| Results tracked | 54 | 27 |
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Category by category
Coding Qwen3.5 122B-A10B leads
Gemini 2.5 Flash: 35.8 (#220), Qwen3.5 122B-A10B: 39.1 (#162)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Coding | 1424 | 1436 |
| SWE-bench Verified (bash only) | 28.7% | — |
| Aider Polyglot | 55.1% | — |
| LMArena WebDev | — | 1360 |
| SciCode | — | 35.6% |
| WeirdML | 41.9% | — |
| ALE-Bench | 661.88 | — |
Agentic & Tool Use Not comparable
Gemini 2.5 Flash: 30.8 (#74), Qwen3.5 122B-A10B: —
| Benchmark | Gemini 2.5 Flash | Qwen3.5 122B-A10B |
|---|---|---|
| Terminal-Bench | 17.1% | — |
| Berkeley Function Calling Leaderboard | 56.2% | — |
| TheAgentCompany | 41.1% | — |
| BALROG | 33.5% | — |
| Vending-Bench 2 | 548.84 | — |
Reasoning Qwen3.5 122B-A10B leads
Gemini 2.5 Flash: 18.1 (#286), Qwen3.5 122B-A10B: 27.2 (#123)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 122B-A10B |
|---|---|---|
| CritPt | 1.1% | 0.9% |
| LMArena Hard Prompts | 1422 | 1421 |
| DTBench | 76.5% | 84.3% |
| LMCA | 27.5% | 32.2% |
| ARC-AGI-2 | 2.5% | — |
| SimpleBench | 41.2% | — |
| Kagi LLM Benchmark | 56.8% | — |
| NYT Connections (extended) | — | 51.7% |
| ARC-AGI-1 | 33.3% | — |
| EnigmaEval | 2.7% | — |
| Thematic Generalization | — | 51.2% |
| Mystery Game Puzzles | — | 17% |
| Epoch Capabilities Index | 143.03 | — |
| ForecastBench | 60.6 | — |
Math Too close to call
Gemini 2.5 Flash: 39.9 (#98), Qwen3.5 122B-A10B: 39.1 (#112)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Math | 1415 | 1432 |
| OTIS Mock AIME 2024-2025 | 73.1% | — |
| Omni-MATH | 38.5% | — |
| FrontierMath (Feb 2025 set) | 4.8% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Qwen3.5 122B-A10B leads
Gemini 2.5 Flash: 36.4 (#168), Qwen3.5 122B-A10B: 38.8 (#142)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 122B-A10B |
|---|---|---|
| Vectara Hallucination Rate | 7.8% | 11.2% |
| LMArena Expert | 1426 | 1432 |
| Humanity's Last Exam | 12.1% | — |
| MMLU-Pro | 63.9% | — |
| Confabulations | 16.8% | — |
| GPQA (HELM) | 39% | — |
Multimodal Gemini 2.5 Flash leads
Gemini 2.5 Flash: 41.8 (#32), Qwen3.5 122B-A10B: 39.6 (#57)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Vision | 1253 | 1245 |
| GeoBench | 76% | — |
| VPCT | 46.2% | — |
| SpatialViz-Bench | 36.9% | — |
Multilingual Too close to call
Gemini 2.5 Flash: 52.3 (#88), Qwen3.5 122B-A10B: 51.6 (#107)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Non-English | 1409 | 1400 |
| LMArena Chinese | 1450 | 1462 |
| LMArena French | 1433 | 1442 |
| LMArena German | 1418 | 1426 |
| LMArena Japanese | 1405 | 1367 |
| LMArena Korean | 1385 | 1352 |
| LMArena Russian | 1415 | 1400 |
| LMArena Spanish | 1421 | 1424 |
Instruction Following Gemini 2.5 Flash leads
Gemini 2.5 Flash: 75.7 (#54), Qwen3.5 122B-A10B: 73.8 (#115)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Instruction Following | 1405 | 1399 |
| IFEval | 89.8% | — |
Long Context Gemini 2.5 Flash leads
Gemini 2.5 Flash: 47.5 (#17), Qwen3.5 122B-A10B: 43.0 (#109)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Longer Query | 1419 | 1410 |
| Fiction.LiveBench | 77.8% | — |
Writing & Preference Qwen3.5 122B-A10B leads
Gemini 2.5 Flash: 53.8 (#157), Qwen3.5 122B-A10B: 60.0 (#105)
| Benchmark | Gemini 2.5 Flash | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Text | 1417 | 1417 |
| LMArena Creative Writing | 1400 | 1368 |
| LMArena Multi-Turn | 1408 | 1416 |
| Short-Story Creative Writing | 76.5% | — |
| EQ-Bench Creative Writing | 1137 | — |
| WildBench | 81.7% | — |
Frequently asked questions
Is Gemini 2.5 Flash better than Qwen3.5 122B-A10B?
Qwen3.5 122B-A10B is the stronger model overall, scoring 42.1 to 39.3 on the Noometry Index.
Which is cheaper, Gemini 2.5 Flash or Qwen3.5 122B-A10B?
Gemini 2.5 Flash is cheaper. It lists at $0.30 per million input tokens and $2.50 per million output tokens; Qwen3.5 122B-A10B lists at $0.40 and $3.20.
Is Gemini 2.5 Flash or Qwen3.5 122B-A10B better for coding?
Qwen3.5 122B-A10B scores higher on coding benchmarks: 39.1 versus 35.8 in the Noometry coding category.
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 122B-A10B share?
22 benchmarks have published results for both models. Gemini 2.5 Flash has 54 scored results on Noometry and Qwen3.5 122B-A10B has 27.