Gemini 2.5 Flash vs Qwen3.5-27B
Qwen3.5-27B leads Gemini 2.5 Flash on the Artificial Analysis Intelligence Index, 22.9 to 15.5, and Qwen3.5-27B costs 1.6x less per output token ($1.56 vs $2.50 per million). Updated October 22, 2026; 48 benchmarks have a result for both.
Gemini 2.5 Flash or Qwen3.5-27B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Gemini 2.5 Flash for a larger context window (1.05M against 262K tokens) and work measured by Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.
- Shared results
- 48
- Gemini 2.5 Flash only
- 25
- Qwen3.5-27B only
- 5
- Like-for-like categories
- 7 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.5-27B
Qwen3.5-27B leads, 22.9 against 15.5.
Same board, both measured
Web design
Design Arena: websites
No call
Only Gemini 2.5 Flash has a Design Arena: websites result, 1074.
Directional only
Long documents
Listed context window
Gemini 2.5 Flash
Gemini 2.5 Flash takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5-27B
Gemini 2.5 Flash $0.0015, Qwen3.5-27B $0.0010 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 2.5 Flash has the number, $0.466.
Directional only
At a glance
- Coding index
- Gemini 2.5 Flash not benchmarked, Qwen3.5-27B not benchmarked.
- Widest category
- Agentic work, 32.2 points apart on average over 2 shared benchmarks.
- Widest single gap
- τ²-Bench Telecom: Gemini 2.5 Flash 31.6% against Qwen3.5-27B 93.9%, 62.3 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Flash $2.50 against Qwen3.5-27B $1.56 per million output tokens, 1.6x apart.
- Context window
- Gemini 2.5 Flash takes 1.05M tokens, Qwen3.5-27B 262K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Gemini 2.5 Flash | Bars | Qwen3.5-27B | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 1 | 1 | ||
| Reasoning | 1 | 6 | ||
| Math | 0 | 2 | ||
| Knowledge | 3 | 1 | ||
| General | 17 | 12 | ||
| All shared boards | 22 | 26 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Gemini 2.5 Flash | Qwen3.5-27B | Leader |
|---|---|---|---|
| SWE-bench Verified | 28.7% | Not measured | Only Gemini 2.5 Flash measured |
| LMArena WebDev | Not measured | 1358 | Only Qwen3.5-27B measured |
| LiveCodeBench (Artificial Analysis run) | 69.5% | Not measured | Only Gemini 2.5 Flash measured |
| Terminal-Bench Hard (Artificial Analysis run) | 13.6% | 32.6% | Qwen3.5-27B |
| Terminal-Bench | 17.1% | Not measured | Only Gemini 2.5 Flash measured |
| WeirdML | Not measured | 39.5% | Only Qwen3.5-27B measured |
| ALE-Bench | Not measured | 349.4 | Only Qwen3.5-27B measured |
| LMArena Text: coding | 1423 | 1427 | Qwen3.5-27B |
| LMArena Text: software and IT | 1425 | 1431 | Qwen3.5-27B |
| LMArena WebDev: React | Not measured | 1346 | Only Qwen3.5-27B measured |
| LMArena WebDev: HTML | Not measured | 1386 | Only Qwen3.5-27B measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Flash | Qwen3.5-27B | Leader |
|---|---|---|---|
| AA Intelligence Index | 15.5 | 22.9 | Qwen3.5-27B |
| Epoch Capabilities Index | 142.9 | Not measured | Only Gemini 2.5 Flash measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Gemini 2.5 Flash | Qwen3.5-27B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 31.6% | 93.9% | Qwen3.5-27B |
| BALROG | 33.5% | Not measured | Only Gemini 2.5 Flash measured |
| Vending-Bench 2 | $549 | $202 | Gemini 2.5 Flash |
| Berkeley Function Calling Leaderboard (BFCL) | 56.2% | Not measured | Only Gemini 2.5 Flash measured |
| BrowseComp-Plus | 39.9% | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index16
| Benchmark | Gemini 2.5 Flash | Qwen3.5-27B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 79.0% | 85.8% | Qwen3.5-27B |
| Humanity's Last Exam (Artificial Analysis run) | 12.1% | 23.9% | Qwen3.5-27B |
| ARC-AGI | 33.3% | Not measured | Only Gemini 2.5 Flash measured |
| ARC-AGI-2 | 2.5% | Not measured | Only Gemini 2.5 Flash measured |
| SimpleBench | 41.2% | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: hard prompts | 1422 | 1415 | Gemini 2.5 Flash |
| LMArena Text: expert | 1426 | 1427 | Qwen3.5-27B |
| LMArena Text: hard prompts in English | 1420 | 1429 | Qwen3.5-27B |
| LMArena Vision: diagrams | 1245 | 1249 | Qwen3.5-27B |
| LMArena Vision: homework | 1244 | 1256 | Qwen3.5-27B |
| Kagi LLM Benchmark | 56.8% | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 11 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Flash | Qwen3.5-27B | Leader |
|---|---|---|---|
| AA Math Index | 73.3 | Not measured | Only Gemini 2.5 Flash measured |
| AIME 2025 (Artificial Analysis run) | 73.3% | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: math | 1411 | 1429 | Qwen3.5-27B |
| LMArena Text: mathematical work | 1422 | 1429 | Qwen3.5-27B |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | Gemini 2.5 Flash | Qwen3.5-27B | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 40.4% | Not measured | Only Gemini 2.5 Flash measured |
| MMLU Pro (Artificial Analysis run) | 83.2% | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: science | 1433 | 1437 | Qwen3.5-27B |
| LMArena Text: medicine and healthcare | 1428 | 1425 | Gemini 2.5 Flash |
| LMArena Text: legal and government | 1430 | 1405 | Gemini 2.5 Flash |
| LMArena Text: business and finance | 1404 | 1399 | Gemini 2.5 Flash |
| FACTS Benchmark Suite | 47.2% | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Gemini 2.5 Flash | Qwen3.5-27B | Leader |
|---|---|---|---|
| Design Arena: websites | 1074 | Not measured | Only Gemini 2.5 Flash measured |
| Design Arena: UI components | 1002 | Not measured | Only Gemini 2.5 Flash measured |
| Design Arena: game dev | 1004 | Not measured | Only Gemini 2.5 Flash measured |
| Design Arena: data viz | 1060 | Not measured | Only Gemini 2.5 Flash measured |
| Design Arena: 3D | 1020 | Not measured | Only Gemini 2.5 Flash measured |
| Design Arena: all code categories | 1059 | Not measured | Only Gemini 2.5 Flash measured |
| Design Arena: SVG | 1020 | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index1712
| Benchmark | Gemini 2.5 Flash | Qwen3.5-27B | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 44.8% | Not measured | Only Gemini 2.5 Flash measured |
| MedScribe (Vals AI) | 83.0% | Not measured | Only Gemini 2.5 Flash measured |
| IFBench | 50.3% | 75.6% | Qwen3.5-27B |
| Long context reasoning (AA-LCR) | 65.3% | 77.7% | Qwen3.5-27B |
| DTBench | 76.5% | 82.4% | Qwen3.5-27B |
| LMCA | 27.5% | 34.0% | Qwen3.5-27B |
| LMArena Text | 1417 | 1409 | Gemini 2.5 Flash |
| LMArena Text: instruction following | 1405 | 1393 | Gemini 2.5 Flash |
| LMArena Text: creative writing | 1400 | 1362 | Gemini 2.5 Flash |
| LMArena Vision | 1235 | 1241 | Qwen3.5-27B |
| LMArena Text: English | 1418 | 1425 | Qwen3.5-27B |
| LMArena Text: non-English | 1409 | 1390 | Gemini 2.5 Flash |
| LMArena Text: Chinese | 1449 | 1478 | Qwen3.5-27B |
| LMArena Text: German | 1417 | 1392 | Gemini 2.5 Flash |
| LMArena Text: Japanese | 1396 | 1346 | Gemini 2.5 Flash |
| LMArena Text: Korean | 1385 | 1359 | Gemini 2.5 Flash |
| LMArena Text: French | 1432 | 1410 | Gemini 2.5 Flash |
| LMArena Text: Spanish | 1422 | 1407 | Gemini 2.5 Flash |
| LMArena Text: Russian | 1415 | 1390 | Gemini 2.5 Flash |
| LMArena Text: Polish | 1413 | 1375 | Gemini 2.5 Flash |
| LMArena Text: multi-turn | 1408 | 1410 | Qwen3.5-27B |
| LMArena Text: longer queries | 1419 | 1413 | Gemini 2.5 Flash |
| LMArena Text: writing and language | 1405 | 1380 | Gemini 2.5 Flash |
| LMArena Text: entertainment and media | 1393 | 1363 | Gemini 2.5 Flash |
| LMArena Vision: English | 1239 | 1246 | Qwen3.5-27B |
| LMArena Vision: Chinese | 1284 | 1301 | Qwen3.5-27B |
| LMArena Vision: reading text | 1237 | 1246 | Qwen3.5-27B |
| LMArena Vision: humor | 1225 | 1227 | Qwen3.5-27B |
| LMArena Vision: captioning | 1277 | 1170 | Gemini 2.5 Flash |
| LMArena Vision: recognizing things | 1252 | 1210 | Gemini 2.5 Flash |
| LMArena Vision: creative writing | 1241 | 1224 | Gemini 2.5 Flash |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Flash | Qwen3.5-27B | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Qwen3.5-27B costs less
Repository review
50K input + 3K output tokens
Qwen3.5-27B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-27B costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Google Gemini 2.5 Flash | Qwen3.5-27B |
|---|---|---|
| Maker | Qwen | |
| Weights | No public weights listed | Open weights |
| Released | June 17, 2025 | February 25, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $0.30 | $0.195 |
| Output $/Mtok | $2.50 | $1.56 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | $0.466 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Flash better than Qwen3.5-27B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemini 2.5 Flash for a larger context window (1.05M against 262K tokens) and work measured by Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.
Which is cheaper, Gemini 2.5 Flash or Qwen3.5-27B?
Gemini 2.5 Flash costs $0.30 per million input tokens and $2.50 per million output tokens; Qwen3.5-27B costs $0.195 and $1.56. Cost per solved task is known for Gemini 2.5 Flash only.
Which has the bigger context window, Gemini 2.5 Flash or Qwen3.5-27B?
Gemini 2.5 Flash, with 1.05M tokens against 262K.
How many benchmarks is the Gemini 2.5 Flash vs Qwen3.5-27B comparison based on?
48 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Flash's coding index rests on 0 independent benchmarks and Qwen3.5-27B's on 1. Where only one model has a result, the page says so instead of naming a winner.