Gemini 2.5 Pro vs Qwen3.5-Flash
Qwen3.5-Flash leads Gemini 2.5 Pro on coding, 41.1 to 19.1 on the Vibe Coding Index, and Qwen3.5-Flash costs 38.5x less per output token ($0.26 vs $10.00 per million). Updated October 22, 2026; 43 benchmarks have a result for both.
Gemini 2.5 Pro or Qwen3.5-Flash: which to pick
Pick Qwen3.5-Flash for coding: it scores 41.1 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro, though on 2 benchmarks against 3.
Pick Gemini 2.5 Pro for a larger context window (1.05M against 1M tokens) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
- Shared results
- 43
- Gemini 2.5 Pro only
- 47
- Qwen3.5-Flash only
- 12
- Like-for-like categories
- 6 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
Qwen3.5-Flash
Qwen3.5-Flash scores 41.1 against 19.1.
3 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only Gemini 2.5 Pro has a AA Intelligence Index result, 16.1.
Directional only
Agentic work
AA Agentic Index
No call
Only Gemini 2.5 Pro has a AA Agentic Index result, 1.6.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.5-Flash has a GPQA Diamond result, 82.8%.
Directional only
Math
AIME
No call
Only Qwen3.5-Flash has a AIME result, 92.5%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.5-Flash has a MMLU Pro result, 84.1%.
Directional only
Web design
Design Arena: websites
No call
Only Gemini 2.5 Pro has a Design Arena: websites result, 1167.
Directional only
Long documents
Listed context window
Gemini 2.5 Pro
Gemini 2.5 Pro takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5-Flash
Gemini 2.5 Pro $0.0063, Qwen3.5-Flash $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Qwen3.5-Flash
Gemini 2.5 Pro $0.64, Qwen3.5-Flash $0.40.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 2.5 Pro 19.1 from 3 benchmarks, Qwen3.5-Flash 41.1 from 2 benchmarks.
- Widest category
- General, 10.9 points apart on average over 21 shared benchmarks.
- Widest single gap
- LMArena Text: creative writing: Gemini 2.5 Pro 1454 against Qwen3.5-Flash 1343, 18.4 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Pro $10.00 against Qwen3.5-Flash $0.26 per million output tokens, 38.5x apart.
- Context window
- Gemini 2.5 Pro takes 1.05M tokens, Qwen3.5-Flash 1M.
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 Pro | Bars | Qwen3.5-Flash | Ties |
|---|---|---|---|---|
| Coding | 2 | 3 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 4 | 0 | ||
| Math | 4 | 0 | ||
| Knowledge | 7 | 1 | ||
| General | 19 | 2 | ||
| All shared boards | 37 | 6 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index23
| Benchmark | Gemini 2.5 Pro | Qwen3.5-Flash | Leader |
|---|---|---|---|
| SWE-bench Verified | 53.6% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena WebDev | 1226 | 1244 | Qwen3.5-Flash |
| AA Coding Index | 33.3 | Not measured | Only Gemini 2.5 Pro measured |
| LiveCodeBench (Vals AI) | Not measured | 83.3% | Only Qwen3.5-Flash measured |
| SWE-bench Verified (Vals AI) | 54.4% | 64.4% | Qwen3.5-Flash |
| Vibe Code Bench (Vals AI) | 0.4% | Not measured | Only Gemini 2.5 Pro measured |
| LiveCodeBench (Artificial Analysis run) | 80.1% | Not measured | Only Gemini 2.5 Pro measured |
| SciCode | 46.3% | Not measured | Only Gemini 2.5 Pro measured |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | Not measured | Only Gemini 2.5 Pro measured |
| Terminal-Bench | 32.6% | Not measured | Only Gemini 2.5 Pro measured |
| GSO-Bench | 3.9% | Not measured | Only Gemini 2.5 Pro measured |
| WeirdML | 54.0% | Not measured | Only Gemini 2.5 Pro measured |
| ALE-Bench | Not measured | 265.9 | Only Qwen3.5-Flash measured |
| LMArena Text: coding | 1452 | 1412 | Gemini 2.5 Pro |
| LMArena Text: software and IT | 1459 | 1416 | Gemini 2.5 Pro |
| LMArena WebDev: React | Not measured | 1229 | Only Qwen3.5-Flash measured |
| LMArena WebDev: HTML | 1235 | 1291 | Qwen3.5-Flash |
| LMArena WebDev: from an image | 1285 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemini 2.5 Pro | Qwen3.5-Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.1 | Not measured | Only Gemini 2.5 Pro measured |
| Epoch Capabilities Index | 145.1 | 143.5 | Gemini 2.5 Pro |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemini 2.5 Pro | Qwen3.5-Flash | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | Not measured | Only Gemini 2.5 Pro measured |
| τ²-Bench Telecom | 54.1% | Not measured | Only Gemini 2.5 Pro measured |
| GDPval | 23.3% | Not measured | Only Gemini 2.5 Pro measured |
| DeepResearch Bench | 41.5% | Not measured | Only Gemini 2.5 Pro measured |
| Vending-Bench 2 | $574 | Not measured | Only Gemini 2.5 Pro measured |
| BrowseComp-Plus | 29.5% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemini 2.5 Pro | Qwen3.5-Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 82.8% | Only Qwen3.5-Flash measured |
| MMMU Pro (Vals AI) | Not measured | 81.9% | Only Qwen3.5-Flash measured |
| GPQA Diamond (Artificial Analysis run) | 84.4% | Not measured | Only Gemini 2.5 Pro measured |
| Humanity's Last Exam (Artificial Analysis run) | 22.5% | Not measured | Only Gemini 2.5 Pro measured |
| GPQA Diamond (Epoch AI run) | 85.3% | 82.3% | Gemini 2.5 Pro |
| ARC-AGI | 41.0% | Not measured | Only Gemini 2.5 Pro measured |
| ARC-AGI-2 | 4.9% | Not measured | Only Gemini 2.5 Pro measured |
| Chess puzzles | Not measured | 14.0% | Only Qwen3.5-Flash measured |
| Mystery game puzzles | Not measured | 20.0% | Only Qwen3.5-Flash measured |
| LMArena Text: hard prompts | 1455 | 1403 | Gemini 2.5 Pro |
| LMArena Text: expert | 1452 | 1407 | Gemini 2.5 Pro |
| LMArena Text: hard prompts in English | 1453 | 1409 | Gemini 2.5 Pro |
| LMArena Vision: diagrams | 1274 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: homework | 1281 | Not measured | Only Gemini 2.5 Pro measured |
| Kagi LLM Benchmark | 70.3% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemini 2.5 Pro | Qwen3.5-Flash | Leader |
|---|---|---|---|
| AIME | Not measured | 92.5% | Only Qwen3.5-Flash measured |
| AA Math Index | 87.7 | Not measured | Only Gemini 2.5 Pro measured |
| AIME 2025 (Artificial Analysis run) | 87.7% | Not measured | Only Gemini 2.5 Pro measured |
| OTIS Mock AIME | 84.7% | 84.4% | Gemini 2.5 Pro |
| FrontierMath, tiers 1 to 3 | 24.6% | 18.2% | Gemini 2.5 Pro |
| FrontierMath, tier 4 | 0.0% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: math | 1450 | 1407 | Gemini 2.5 Pro |
| LMArena Text: mathematical work | 1454 | 1413 | Gemini 2.5 Pro |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index71
| Benchmark | Gemini 2.5 Pro | Qwen3.5-Flash | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 84.1% | Only Qwen3.5-Flash measured |
| LegalBench (Vals AI) | Not measured | 84.3% | Only Qwen3.5-Flash measured |
| CaseLaw (Vals AI) | 63.9% | 56.0% | Gemini 2.5 Pro |
| CorpFin (Vals AI) | 60.8% | 63.6% | Qwen3.5-Flash |
| TaxEval (Vals AI) | Not measured | 72.2% | Only Qwen3.5-Flash measured |
| MortgageTax (Vals AI) | 68.9% | 67.4% | Gemini 2.5 Pro |
| MedCode (Vals AI) | 50.6% | 33.0% | Gemini 2.5 Pro |
| MMLU Pro (Artificial Analysis run) | 86.2% | Not measured | Only Gemini 2.5 Pro measured |
| SimpleQA Verified | Not measured | 20.3% | Only Qwen3.5-Flash measured |
| LMArena Text: science | 1480 | 1415 | Gemini 2.5 Pro |
| LMArena Text: medicine and healthcare | 1476 | 1407 | Gemini 2.5 Pro |
| LMArena Text: legal and government | 1480 | 1398 | Gemini 2.5 Pro |
| LMArena Text: business and finance | 1439 | 1394 | Gemini 2.5 Pro |
| FACTS Benchmark Suite | 61.5% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemini 2.5 Pro | Qwen3.5-Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1167 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: UI components | 1137 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: game dev | 1111 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: data viz | 1222 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: 3D | 1080 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: all code categories | 1152 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index192
| Benchmark | Gemini 2.5 Pro | Qwen3.5-Flash | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 41.9% | 42.5% | Qwen3.5-Flash |
| MedScribe (Vals AI) | 73.5% | 70.6% | Gemini 2.5 Pro |
| IFBench | 48.7% | Not measured | Only Gemini 2.5 Pro measured |
| Long context reasoning (AA-LCR) | 69.0% | Not measured | Only Gemini 2.5 Pro measured |
| DTBench | 82.4% | 82.9% | Qwen3.5-Flash |
| LMCA | 34.8% | 29.1% | Gemini 2.5 Pro |
| Creative writing (Lech Mazur) | 83.8% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text | 1458 | 1397 | Gemini 2.5 Pro |
| LMArena Text: instruction following | 1437 | 1374 | Gemini 2.5 Pro |
| LMArena Text: creative writing | 1454 | 1343 | Gemini 2.5 Pro |
| LMArena Vision | 1263 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: English | 1458 | 1404 | Gemini 2.5 Pro |
| LMArena Text: non-English | 1452 | 1385 | Gemini 2.5 Pro |
| LMArena Text: Chinese | 1507 | 1445 | Gemini 2.5 Pro |
| LMArena Text: German | 1487 | 1390 | Gemini 2.5 Pro |
| LMArena Text: Japanese | 1461 | 1369 | Gemini 2.5 Pro |
| LMArena Text: Korean | 1434 | 1344 | Gemini 2.5 Pro |
| LMArena Text: French | 1473 | 1413 | Gemini 2.5 Pro |
| LMArena Text: Spanish | 1474 | 1400 | Gemini 2.5 Pro |
| LMArena Text: Russian | 1461 | 1380 | Gemini 2.5 Pro |
| LMArena Text: Polish | 1479 | 1376 | Gemini 2.5 Pro |
| LMArena Text: multi-turn | 1453 | 1393 | Gemini 2.5 Pro |
| LMArena Text: longer queries | 1449 | 1392 | Gemini 2.5 Pro |
| LMArena Text: writing and language | 1454 | 1369 | Gemini 2.5 Pro |
| LMArena Text: entertainment and media | 1441 | 1347 | Gemini 2.5 Pro |
| LMArena Vision: English | 1261 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: Chinese | 1300 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: reading text | 1270 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: humor | 1262 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: captioning | 1304 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: recognizing things | 1283 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: creative writing | 1265 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Document | 1421 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro | Qwen3.5-Flash | 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-Flash costs less
Repository review
50K input + 3K output tokens
Qwen3.5-Flash costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-Flash 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 Pro | Qwen3.5-Flash |
|---|---|---|
| Maker | Qwen | |
| Weights | No public weights listed | No public weights listed |
| Released | June 17, 2025 | February 25, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $1.25 | $0.065 |
| Output $/Mtok | $10.00 | $0.26 |
| Coding index | 19.1 | 41.1 |
| Independent measurements behind it | 3 | 2 |
| Cost per solved task | $0.64 | $0.40 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro better than Qwen3.5-Flash for coding?
Pick Qwen3.5-Flash for coding: it scores 41.1 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro, though on 2 benchmarks against 3. Pick Gemini 2.5 Pro for a larger context window (1.05M against 1M tokens) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, Gemini 2.5 Pro or Qwen3.5-Flash?
Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; Qwen3.5-Flash costs $0.065 and $0.26. Per solved SWE-bench Verified task, Gemini 2.5 Pro costs $0.64 and Qwen3.5-Flash $0.40.
Which has the bigger context window, Gemini 2.5 Pro or Qwen3.5-Flash?
Gemini 2.5 Pro, with 1.05M tokens against 1M.
How many benchmarks is the Gemini 2.5 Pro vs Qwen3.5-Flash comparison based on?
43 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Pro's coding index rests on 3 independent benchmarks and Qwen3.5-Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.