Model comparison
Gemini 2.5 Flash-Lite vs Qwen3.5 27B
Qwen3.5 27B is the stronger model overall, scoring 41.9 to 37.0 on the Noometry Index. Gemini 2.5 Flash-Lite costs 4.7× less per token, which makes it the better buy when Qwen3.5 27B's lead doesn't matter for your workload.
Last verified . 23 shared benchmarks.
Google
Alibaba (Qwen)Summary
- They share 23 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 0 categories and Qwen3.5 27B in 9 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in multimodal, where Qwen3.5 27B leads 39.4 to 29.1.
- The biggest single-benchmark swing is DTBench: 62.8% for Gemini 2.5 Flash-Lite and 82.4% for Qwen3.5 27B.
- Gemini 2.5 Flash-Lite is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.30 / $2.40 for Qwen3.5 27B.
- Gemini 2.5 Flash-Lite accepts more context: 1.05M tokens versus 262K.
- Qwen3.5 27B has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Flash-Lite | Qwen3.5 27B | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 37.0 | 41.9 |
| Released | 2025-06-17 | 2026-02-23 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 66K | 66K |
| Input $ / M tokens | $0.10 | $0.30 |
| Output $ / M tokens | $0.40 | $2.40 |
| Results tracked | 33 | 28 |
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Category by category
Coding Too close to call
Gemini 2.5 Flash-Lite: 38.5 (#173), Qwen3.5 27B: 38.9 (#168)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.5 27B |
|---|---|---|
| WeirdML | 35.2% | 39.5% |
| LMArena Coding | 1373 | 1427 |
| ALE-Bench | 325.9 | 349.45 |
| LMArena WebDev | — | 1358 |
Agentic & Tool Use Not comparable
Gemini 2.5 Flash-Lite: 28.0 (#96), Qwen3.5 27B: —
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.5 27B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 36.9% | — |
| Vending-Bench 2 | — | 201.98 |
Reasoning Qwen3.5 27B leads
Gemini 2.5 Flash-Lite: 22.2 (#205), Qwen3.5 27B: 27.5 (#117)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.5 27B |
|---|---|---|
| LMArena Hard Prompts | 1377 | 1414 |
| DTBench | 62.8% | 82.4% |
| LMCA | 18.1% | 34% |
| Kagi LLM Benchmark | 40.5% | — |
| NYT Connections (extended) | — | 47.9% |
| Thematic Generalization | — | 45.5% |
| Epoch Capabilities Index | 133.94 | — |
Math Too close to call
Gemini 2.5 Flash-Lite: 38.0 (#144), Qwen3.5 27B: 38.8 (#127)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.5 27B |
|---|---|---|
| LMArena Math | 1373 | 1429 |
| MathArena Final-Answer Competitions | — | 56.7% |
| Omni-MATH | 48% | — |
Knowledge Qwen3.5 27B leads
Gemini 2.5 Flash-Lite: 32.5 (#210), Qwen3.5 27B: 38.0 (#150)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.5 27B |
|---|---|---|
| Vectara Hallucination Rate | 3.3% | 12.1% |
| LMArena Expert | 1373 | 1428 |
| MMLU-Pro | 53.7% | — |
| GPQA (HELM) | 30.9% | — |
Multimodal Qwen3.5 27B leads
Gemini 2.5 Flash-Lite: 29.1 (#114), Qwen3.5 27B: 39.4 (#59)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.5 27B |
|---|---|---|
| LMArena Vision | 1198 | 1241 |
| VPCT | 30% | — |
Multilingual Qwen3.5 27B leads
Gemini 2.5 Flash-Lite: 49.3 (#134), Qwen3.5 27B: 50.8 (#115)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.5 27B |
|---|---|---|
| LMArena Non-English | 1369 | 1390 |
| LMArena Chinese | 1404 | 1478 |
| LMArena French | 1388 | 1410 |
| LMArena German | 1389 | 1393 |
| LMArena Japanese | 1359 | 1345 |
| LMArena Korean | 1360 | 1358 |
| LMArena Russian | 1373 | 1390 |
| LMArena Spanish | 1396 | 1407 |
Instruction Following Qwen3.5 27B leads
Gemini 2.5 Flash-Lite: 70.0 (#168), Qwen3.5 27B: 73.5 (#119)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.5 27B |
|---|---|---|
| LMArena Instruction Following | 1367 | 1393 |
| IFEval | 81% | — |
Long Context Qwen3.5 27B leads
Gemini 2.5 Flash-Lite: 33.3 (#262), Qwen3.5 27B: 43.1 (#106)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.5 27B |
|---|---|---|
| LMArena Longer Query | 1373 | 1413 |
| Fiction.LiveBench | 47.2% | — |
Writing & Preference Qwen3.5 27B leads
Gemini 2.5 Flash-Lite: 56.8 (#135), Qwen3.5 27B: 59.3 (#111)
| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.5 27B |
|---|---|---|
| LMArena Text | 1379 | 1409 |
| LMArena Creative Writing | 1367 | 1362 |
| LMArena Multi-Turn | 1366 | 1410 |
| WildBench | 81.8% | — |
Frequently asked questions
Is Gemini 2.5 Flash-Lite better than Qwen3.5 27B?
Qwen3.5 27B is the stronger model overall, scoring 41.9 to 37.0 on the Noometry Index. Gemini 2.5 Flash-Lite costs 4.7× less per token, which makes it the better buy when Qwen3.5 27B's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Flash-Lite or Qwen3.5 27B?
Gemini 2.5 Flash-Lite is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Qwen3.5 27B lists at $0.30 and $2.40.
Is Gemini 2.5 Flash-Lite or Qwen3.5 27B better for coding?
They score almost the same on coding (38.5 vs 38.9); test both on your own repository before choosing.
Which has the bigger context window?
Gemini 2.5 Flash-Lite does, with 1.05M tokens against 262K.
How many benchmarks do Gemini 2.5 Flash-Lite and Qwen3.5 27B share?
23 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and Qwen3.5 27B has 28.