Gemini 3.5 Flash vs Qwen3 32B
Gemini 3.5 Flash leads Qwen3 32B on the Artificial Analysis Intelligence Index, 33.6 to 7.3, and Qwen3 32B costs 22.5x less per output token ($0.40 vs $9.00 per million). Updated October 21, 2026; 36 benchmarks have a result for both.
vs boards won of 36 shared
Gemini 3.5 Flash or Qwen3 32B: which to pick
Only Gemini 3.5 Flash has a coding score, 39.8 on the Vibe Coding Index; Qwen3 32B has none, so the two cannot be ranked on coding.
Pick Qwen3 32B for output tokens 22.5x cheaper ($0.40 vs $9.00 per million).
Model AGemini 3.5 FlashGoogle39.8/1004 independent benchmarks$1.21 per solved taskModel BQwen3 32BQwenNot benchmarkedNo coding benchmarkNo cost per solved task
- Shared results
- 36
- Gemini 3.5 Flash only
- 76
- Qwen3 32B only
- 9
- 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
Only Gemini 3.5 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Gemini 3.5 Flash
Gemini 3.5 Flash leads, 33.6 against 7.3.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Gemini 3.5 Flash has a GPQA Diamond result, 92.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.5 Flash has a MMLU Pro result, 89.5%.
Directional only
Web design
Design Arena: websites
No call
Only Gemini 3.5 Flash has a Design Arena: websites result, 1268.
Directional only
Long documents
Listed context window
Gemini 3.5 Flash
Gemini 3.5 Flash takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 32B
Gemini 3.5 Flash $0.0060, Qwen3 32B $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 3.5 Flash has the number, $1.21.
Directional only
At a glance
- Coding index
- Gemini 3.5 Flash 39.8 from 4 benchmarks, Qwen3 32B not benchmarked.
- Widest category
- Agentic work, 65.8 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Gemini 3.5 Flash 74.3% against Qwen3 32B 0.0%, 74.3 points apart on a 0 to 100 scale.
- Output price
- Gemini 3.5 Flash $9.00 against Qwen3 32B $0.40 per million output tokens, 22.5x apart.
- Context window
- Gemini 3.5 Flash takes 1.05M tokens, Qwen3 32B 131K.
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 3.5 Flash | Bars | Qwen3 32B | Ties |
|---|---|---|---|---|
| Coding | 4 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 6 | 0 | ||
| Math | 3 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 16 | 0 | ||
| All shared boards | 36 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
| Benchmark | Gemini 3.5 Flash | Qwen3 32B | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 40.0% | Only Qwen3 32B measured |
| LMArena WebDev | 1499 | Not measured | Only Gemini 3.5 Flash measured |
| LiveCodeBench (Vals AI) | 87.6% | Not measured | Only Gemini 3.5 Flash measured |
| SWE-bench Verified (Vals AI) | 78.8% | Not measured | Only Gemini 3.5 Flash measured |
| Terminal-Bench 4 (Vals AI) | 6.1% | Not measured | Only Gemini 3.5 Flash measured |
| Vibe Code Bench (Vals AI) | 48.7% | Not measured | Only Gemini 3.5 Flash measured |
| Code migration (Vals AI) | 26.8% | Not measured | Only Gemini 3.5 Flash measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Gemini 3.5 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 74.2% | Not measured | Only Gemini 3.5 Flash measured |
| SkillsBench (Vals AI) | 52.7% | Not measured | Only Gemini 3.5 Flash measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 54.6% | Only Qwen3 32B measured |
| SciCode | 53.9% | 36.0% | Gemini 3.5 Flash |
| Terminal-Bench Hard (Artificial Analysis run) | 46.2% | 3.0% | Gemini 3.5 Flash |
| WeirdML | 62.6% | Not measured | Only Gemini 3.5 Flash measured |
| ALE-Bench | 911.0 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: coding | 1493 | 1357 | Gemini 3.5 Flash |
| LMArena Text: software and IT | 1494 | 1366 | Gemini 3.5 Flash |
| LMArena WebDev: React | 1495 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena WebDev: HTML | 1522 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena WebDev: from an image | 1504 | Not measured | Only Gemini 3.5 Flash measured |
| SciCode | 12.3% | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 3.5 Flash | Qwen3 32B | Leader |
|---|---|---|---|
| AA Intelligence Index | 33.6 | 7.3 | Gemini 3.5 Flash |
| Epoch Capabilities Index | 154.9 | 138.4 | Gemini 3.5 Flash |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemini 3.5 Flash | Qwen3 32B | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1202 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building full-stack apps | 1197 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building mobile apps | 1174 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building Android apps | 1184 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building Godot games | 1098 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building games | 1180 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: HTML slides | 1142 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: PowerPoint slides | 1179 | Not measured | Only Gemini 3.5 Flash measured |
| Finance Agent (Vals AI) | 57.9% | Not measured | Only Gemini 3.5 Flash measured |
| Tax Agent Bench (Vals AI) | 21.6% | Not measured | Only Gemini 3.5 Flash measured |
| Legal Research Bench (Vals AI) | 30.8% | Not measured | Only Gemini 3.5 Flash measured |
| Excel Modeling Benchmark (Vals AI) | 63.5% | Not measured | Only Gemini 3.5 Flash measured |
| Terminal-Bench-Science (Vals AI) | 5.7% | Not measured | Only Gemini 3.5 Flash measured |
| τ²-Bench Telecom | 95.6% | 29.8% | Gemini 3.5 Flash |
| APEX-Agents | 27.5% | Not measured | Only Gemini 3.5 Flash measured |
| Vending-Bench 2 | $5,396 | Not measured | Only Gemini 3.5 Flash measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 48.7% | Only Qwen3 32B measured |
| BrowseComp-Plus | Not measured | 10.7% | Only Qwen3 32B measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Gemini 3.5 Flash | Qwen3 32B | Leader |
|---|---|---|---|
| GPQA Diamond | 92.7% | Not measured | Only Gemini 3.5 Flash measured |
| MMMU Pro (Vals AI) | 88.3% | Not measured | Only Gemini 3.5 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 92.2% | 66.8% | Gemini 3.5 Flash |
| Humanity's Last Exam (Artificial Analysis run) | 42.7% | 7.4% | Gemini 3.5 Flash |
| GPQA Diamond (Epoch AI run) | 92.8% | 65.7% | Gemini 3.5 Flash |
| ARC-AGI | 92.5% | Not measured | Only Gemini 3.5 Flash measured |
| ARC-AGI-2 | 72.1% | Not measured | Only Gemini 3.5 Flash measured |
| SimpleBench | 76.7% | Not measured | Only Gemini 3.5 Flash measured |
| Chess puzzles | 45.0% | Not measured | Only Gemini 3.5 Flash measured |
| Mystery game puzzles | 32.0% | Not measured | Only Gemini 3.5 Flash measured |
| EBR-bench | 4.8% | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: hard prompts | 1488 | 1334 | Gemini 3.5 Flash |
| LMArena Text: expert | 1495 | 1362 | Gemini 3.5 Flash |
| LMArena Text: hard prompts in English | 1483 | 1350 | Gemini 3.5 Flash |
| LMArena Vision: diagrams | 1323 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: homework | 1330 | Not measured | Only Gemini 3.5 Flash measured |
| Kagi LLM Benchmark | Not measured | 48.7% | Only Qwen3 32B measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Gemini 3.5 Flash | Qwen3 32B | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 73.0 | Only Qwen3 32B measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 73.0% | Only Qwen3 32B measured |
| OTIS Mock AIME | 95.6% | 66.9% | Gemini 3.5 Flash |
| FrontierMath, tiers 1 to 3 | 62.8% | Not measured | Only Gemini 3.5 Flash measured |
| FrontierMath, tier 4 | 26.8% | Not measured | Only Gemini 3.5 Flash measured |
| ProofBench | 31.0% | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: math | 1504 | 1399 | Gemini 3.5 Flash |
| LMArena Text: mathematical work | 1495 | 1420 | Gemini 3.5 Flash |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemini 3.5 Flash | Qwen3 32B | Leader |
|---|---|---|---|
| MMLU Pro | 89.5% | Not measured | Only Gemini 3.5 Flash measured |
| LegalBench (Vals AI) | 83.6% | Not measured | Only Gemini 3.5 Flash measured |
| CorpFin (Vals AI) | 64.7% | Not measured | Only Gemini 3.5 Flash measured |
| TaxEval (Vals AI) | 74.4% | Not measured | Only Gemini 3.5 Flash measured |
| MortgageTax (Vals AI) | 68.1% | Not measured | Only Gemini 3.5 Flash measured |
| MedCode (Vals AI) | 55.8% | Not measured | Only Gemini 3.5 Flash measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 79.8% | Only Qwen3 32B measured |
| SimpleQA Verified | 66.2% | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: science | 1495 | 1372 | Gemini 3.5 Flash |
| LMArena Text: medicine and healthcare | 1483 | 1368 | Gemini 3.5 Flash |
| LMArena Text: legal and government | 1488 | 1324 | Gemini 3.5 Flash |
| LMArena Text: business and finance | 1467 | 1318 | Gemini 3.5 Flash |
| FACTS Benchmark Suite | 63.1% | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Gemini 3.5 Flash | Qwen3 32B | Leader |
|---|---|---|---|
| Design Arena: websites | 1268 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: UI components | 1273 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: game dev | 1263 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: data viz | 1236 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: 3D | 1244 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: all code categories | 1266 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: SVG | 1254 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: ASCII art | 1254 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index160
| Benchmark | Gemini 3.5 Flash | Qwen3 32B | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 59.5% | Not measured | Only Gemini 3.5 Flash measured |
| SAGE (Vals AI) | 49.9% | Not measured | Only Gemini 3.5 Flash measured |
| MedScribe (Vals AI) | 76.6% | Not measured | Only Gemini 3.5 Flash measured |
| Vals Multimodal Index | 62.9% | Not measured | Only Gemini 3.5 Flash measured |
| IFBench | 76.3% | 36.3% | Gemini 3.5 Flash |
| Long context reasoning (AA-LCR) | 74.3% | 0.0% | Gemini 3.5 Flash |
| DTBench | 94.7% | 67.5% | Gemini 3.5 Flash |
| LMCA | 47.1% | 17.3% | Gemini 3.5 Flash |
| Fiction.LiveBench | Not measured | 74.2% | Only Qwen3 32B measured |
| Surface Evolver Bench | 58.1% | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text | 1482 | 1340 | Gemini 3.5 Flash |
| LMArena Text: instruction following | 1467 | 1305 | Gemini 3.5 Flash |
| LMArena Text: creative writing | 1470 | 1297 | Gemini 3.5 Flash |
| LMArena Vision | 1308 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: English | 1481 | 1359 | Gemini 3.5 Flash |
| LMArena Text: non-English | 1475 | 1317 | Gemini 3.5 Flash |
| LMArena Text: Chinese | 1527 | 1357 | Gemini 3.5 Flash |
| LMArena Text: German | 1494 | 1341 | Gemini 3.5 Flash |
| LMArena Text: Japanese | 1486 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: Korean | 1448 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: French | 1490 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: Spanish | 1480 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: Russian | 1493 | 1311 | Gemini 3.5 Flash |
| LMArena Text: Polish | 1516 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: multi-turn | 1481 | 1331 | Gemini 3.5 Flash |
| LMArena Text: longer queries | 1483 | 1327 | Gemini 3.5 Flash |
| LMArena Text: writing and language | 1478 | 1298 | Gemini 3.5 Flash |
| LMArena Text: entertainment and media | 1459 | 1279 | Gemini 3.5 Flash |
| LMArena Vision: English | 1305 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: Chinese | 1377 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: reading text | 1317 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: humor | 1321 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: creative writing | 1301 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Document | 1463 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.5 Flash | Qwen3 32B | 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
Gemini 3.5 Flash$0.0060Fits in one request
Qwen3 32B$0.0003Fits in one request
Qwen3 32B costs less
Repository review
50K input + 3K output tokens
Gemini 3.5 Flash$0.102Fits in one request
Qwen3 32B$0.0082Fits in one request
Qwen3 32B costs less
Agent loop
200K input + 10K output tokens
Gemini 3.5 Flash$0.390Fits in one request
Qwen3 32B$0.032Exceeds the context window
Qwen3 32B 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 3.5 Flash | Qwen3 32B |
|---|---|---|
| Maker | Qwen | |
| Weights | No public weights listed | Open weights |
| Released | May 19, 2026 | April 28, 2025 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $1.50 | $0.14 |
| Output $/Mtok | $9.00 | $0.40 |
| Coding index | 39.8 | Not benchmarked |
| Independent measurements behind it | 4 | 0 |
| Cost per solved task | $1.21 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.5 Flash better than Qwen3 32B for coding?
Only Gemini 3.5 Flash has a coding score, 39.8 on the Vibe Coding Index; Qwen3 32B has none, so the two cannot be ranked on coding. Pick Qwen3 32B for output tokens 22.5x cheaper ($0.40 vs $9.00 per million).
Which is cheaper, Gemini 3.5 Flash or Qwen3 32B?
Gemini 3.5 Flash costs $1.50 per million input tokens and $9.00 per million output tokens; Qwen3 32B costs $0.14 and $0.40. Cost per solved task is known for Gemini 3.5 Flash only.
Which has the bigger context window, Gemini 3.5 Flash or Qwen3 32B?
Gemini 3.5 Flash, with 1.05M tokens against 131K.
How many benchmarks is the Gemini 3.5 Flash vs Qwen3 32B comparison based on?
36 benchmarks have a result for both models as of October 21, 2026. Gemini 3.5 Flash's coding index rests on 4 independent benchmarks and Qwen3 32B's on 0. Where only one model has a result, the page says so instead of naming a winner.