Gemini 2.5 Pro vs Qwen3.8 Max (0902)
Updated October 21, 2026. 66 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
vs boards won of 66 shared
Decision reading
Pick Qwen3.8 Max (0902) for coding: it scores 63.5 on the Vibe Coding Index against 37.0 for Gemini 2.5 Pro.
Pick Gemini 2.5 Pro when a solved task costs $0.64 against $1.32, or when the context window is larger, 1.05M against 1M tokens.
Model AGemini 2.5 ProGoogle37.0/1002 independent benchmarks$0.64 per solved taskModel BQwen3.8 Max (0902)Qwen63.5/1002 independent benchmarks$1.32 per solved task
- Shared results
- 66
- Gemini 2.5 Pro only
- 21
- Qwen3.8 Max (0902) only
- 47
- Like-for-like categories
- 8 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) scores 63.5 against 37.0.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 45.4 against 16.1.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 56.0 against 1.6.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Qwen3.8 Max (0902) has a GPQA Diamond result, 93.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.8 Max (0902) has a MMLU Pro result, 88.6%.
Directional only
Web design
Design Arena: websites
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 1275 against 1167.
Same board, both measured
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
Qwen3.8 Max (0902)
Gemini 2.5 Pro $0.0063, Qwen3.8 Max (0902) $0.0050 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Gemini 2.5 Pro
Gemini 2.5 Pro $0.64, Qwen3.8 Max (0902) $1.32.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 2.5 Pro 37.0 from 2 benchmarks, Qwen3.8 Max (0902) 63.5 from 2 benchmarks.
- Widest category
- Agentic work, 54.4 points apart on average over 1 shared benchmark.
- Widest single gap
- Vibe Code Bench (Vals AI): Gemini 2.5 Pro 0.4% against Qwen3.8 Max (0902) 64.7%, 64.3 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Pro $10.00 against Qwen3.8 Max (0902) $6.00 per million output tokens, 1.7x apart.
- Context window
- Gemini 2.5 Pro takes 1.05M tokens, Qwen3.8 Max (0902) 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 | Qwen3.8 Max (0902) | Ties |
|---|---|---|---|---|
| Coding | 0 | 9 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 8 | ||
| Math | 0 | 5 | ||
| Knowledge | 2 | 5 | ||
| Web design | 0 | 6 | ||
| General | 2 | 26 | ||
| All shared boards | 4 | 62 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index09
| Benchmark | Gemini 2.5 Pro | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| SWE-bench Verified | 53.6% | Not measured | Only Gemini 2.5 Pro measured |
| LiveBench coding | Not measured | 60.3% | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev | 1226 | 1674 | Qwen3.8 Max (0902) |
| AA Coding Index | 33.3 | 76.2 | Qwen3.8 Max (0902) |
| LiveCodeBench (Vals AI) | Not measured | 87.8% | Only Qwen3.8 Max (0902) measured |
| SWE-bench Verified (Vals AI) | 54.4% | 85.6% | Qwen3.8 Max (0902) |
| Terminal-Bench 4 (Vals AI) | Not measured | 34.3% | Only Qwen3.8 Max (0902) measured |
| Vibe Code Bench (Vals AI) | 0.4% | 64.7% | Qwen3.8 Max (0902) |
| Code migration (Vals AI) | Not measured | 24.0% | Only Qwen3.8 Max (0902) measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Qwen3.8 Max (0902) measured |
| IOI (Vals AI) | Not measured | 68.9% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 67.4% | Only Qwen3.8 Max (0902) measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 42.5% | Only Qwen3.8 Max (0902) measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 12.8% | Only Qwen3.8 Max (0902) measured |
| SkillsBench (Vals AI) | Not measured | 42.0% | Only Qwen3.8 Max (0902) measured |
| CyberBench (Vals AI) | Not measured | 28.6% | Only Qwen3.8 Max (0902) measured |
| LiveCodeBench (Artificial Analysis run) | 80.1% | Not measured | Only Gemini 2.5 Pro measured |
| SciCode | 46.3% | 53.2% | Qwen3.8 Max (0902) |
| 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 |
| FrontierSWE | Not measured | 17.8% | Only Qwen3.8 Max (0902) measured |
| GSO-Bench | 3.9% | Not measured | Only Gemini 2.5 Pro measured |
| WeirdML | 54.0% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: coding | 1452 | 1502 | Qwen3.8 Max (0902) |
| LMArena Text: software and IT | 1459 | 1498 | Qwen3.8 Max (0902) |
| LMArena WebDev: React | Not measured | 1692 | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev: HTML | 1235 | 1649 | Qwen3.8 Max (0902) |
| LMArena WebDev: from an image | 1285 | 1637 | Qwen3.8 Max (0902) |
| Neither model has a result on the other 10 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Pro | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.1 | 45.4 | Qwen3.8 Max (0902) |
| Epoch Capabilities Index | 145.1 | 157.4 | Qwen3.8 Max (0902) |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Pro | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | 56.0 | Qwen3.8 Max (0902) |
| Design Arena: agents building web apps | Not measured | 1301 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building full-stack apps | Not measured | 1305 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building mobile apps | Not measured | 1223 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building Android apps | Not measured | 1207 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building Godot games | Not measured | 1234 | Only Qwen3.8 Max (0902) measured |
| Design Arena: PowerPoint slides | Not measured | 1257 | Only Qwen3.8 Max (0902) measured |
| Design Arena: spreadsheets | Not measured | 868 | Only Qwen3.8 Max (0902) measured |
| LiveBench research | Not measured | 69.9% | Only Qwen3.8 Max (0902) measured |
| LiveBench browser | Not measured | 32.0% | Only Qwen3.8 Max (0902) measured |
| LiveBench long agentic | Not measured | 42.3% | Only Qwen3.8 Max (0902) measured |
| Finance Agent (Vals AI) | Not measured | 50.6% | Only Qwen3.8 Max (0902) measured |
| Tax Agent Bench (Vals AI) | Not measured | 32.1% | Only Qwen3.8 Max (0902) measured |
| Legal Research Bench (Vals AI) | Not measured | 47.6% | Only Qwen3.8 Max (0902) measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 60.1% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 12.9% | Only Qwen3.8 Max (0902) measured |
| τ²-Bench Telecom | 54.1% | Not measured | Only Gemini 2.5 Pro measured |
| APEX-Agents | Not measured | 63.3% | Only Qwen3.8 Max (0902) 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 |
| LMArena Search | Not measured | 1261 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 17 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | Gemini 2.5 Pro | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 93.7% | Only Qwen3.8 Max (0902) measured |
| LiveBench reasoning | Not measured | 88.2% | Only Qwen3.8 Max (0902) measured |
| MysteryMechanism (Vals AI) | Not measured | 23.9% | Only Qwen3.8 Max (0902) measured |
| MMMU Pro (Vals AI) | Not measured | 88.0% | Only Qwen3.8 Max (0902) measured |
| GPQA Diamond (Artificial Analysis run) | 84.4% | 92.8% | Qwen3.8 Max (0902) |
| Humanity's Last Exam (Artificial Analysis run) | 22.5% | 43.1% | Qwen3.8 Max (0902) |
| GPQA Diamond (Epoch AI run) | 85.3% | 92.7% | Qwen3.8 Max (0902) |
| 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 | 46.0% | Only Qwen3.8 Max (0902) measured |
| Mystery game puzzles | Not measured | 38.0% | Only Qwen3.8 Max (0902) measured |
| LMArena Text: hard prompts | 1455 | 1496 | Qwen3.8 Max (0902) |
| LMArena Text: expert | 1452 | 1507 | Qwen3.8 Max (0902) |
| LMArena Text: hard prompts in English | 1453 | 1503 | Qwen3.8 Max (0902) |
| LMArena Vision: diagrams | 1274 | 1323 | Qwen3.8 Max (0902) |
| LMArena Vision: homework | 1281 | 1336 | Qwen3.8 Max (0902) |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Gemini 2.5 Pro | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| 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% | 100.0% | Qwen3.8 Max (0902) |
| FrontierMath, tiers 1 to 3 | 24.6% | 74.7% | Qwen3.8 Max (0902) |
| FrontierMath, tier 4 | 0.0% | 46.3% | Qwen3.8 Max (0902) |
| ProofBench | Not measured | 58.0% | Only Qwen3.8 Max (0902) measured |
| LMArena Text: math | 1450 | 1501 | Qwen3.8 Max (0902) |
| LMArena Text: mathematical work | 1454 | 1491 | Qwen3.8 Max (0902) |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index25
| Benchmark | Gemini 2.5 Pro | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 88.6% | Only Qwen3.8 Max (0902) measured |
| LegalBench (Vals AI) | Not measured | 83.6% | Only Qwen3.8 Max (0902) measured |
| CaseLaw (Vals AI) | 63.9% | Not measured | Only Gemini 2.5 Pro measured |
| CorpFin (Vals AI) | 60.8% | 65.8% | Qwen3.8 Max (0902) |
| TaxEval (Vals AI) | Not measured | 75.5% | Only Qwen3.8 Max (0902) measured |
| MortgageTax (Vals AI) | 68.9% | 64.0% | Gemini 2.5 Pro |
| MedCode (Vals AI) | 50.6% | 40.7% | Gemini 2.5 Pro |
| MMLU Pro (Artificial Analysis run) | 86.2% | Not measured | Only Gemini 2.5 Pro measured |
| SimpleQA Verified | Not measured | 47.3% | Only Qwen3.8 Max (0902) measured |
| LMArena Text: science | 1480 | 1512 | Qwen3.8 Max (0902) |
| LMArena Text: medicine and healthcare | 1476 | 1503 | Qwen3.8 Max (0902) |
| LMArena Text: legal and government | 1480 | 1492 | Qwen3.8 Max (0902) |
| LMArena Text: business and finance | 1439 | 1480 | Qwen3.8 Max (0902) |
| Neither model has a result on the other 4 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Gemini 2.5 Pro | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| Design Arena: websites | 1167 | 1275 | Qwen3.8 Max (0902) |
| Design Arena: UI components | 1139 | 1340 | Qwen3.8 Max (0902) |
| Design Arena: game dev | 1112 | 1313 | Qwen3.8 Max (0902) |
| Design Arena: data viz | 1222 | 1281 | Qwen3.8 Max (0902) |
| Design Arena: 3D | 1080 | 1337 | Qwen3.8 Max (0902) |
| Design Arena: all code categories | 1152 | 1293 | Qwen3.8 Max (0902) |
| Design Arena: ASCII art | Not measured | 1201 | Only Qwen3.8 Max (0902) measured |
| LiveBench design | Not measured | 78.6% | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index226
| Benchmark | Gemini 2.5 Pro | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 78.4% | Only Qwen3.8 Max (0902) measured |
| Public Benefits Bench (Vals AI) | Not measured | 67.1% | Only Qwen3.8 Max (0902) measured |
| SAGE (Vals AI) | 41.9% | 51.2% | Qwen3.8 Max (0902) |
| MedScribe (Vals AI) | 73.5% | 85.0% | Qwen3.8 Max (0902) |
| Vals Multimodal Index | Not measured | 65.4% | Only Qwen3.8 Max (0902) measured |
| IFBench | 48.7% | Not measured | Only Gemini 2.5 Pro measured |
| Long context reasoning (AA-LCR) | 69.0% | 80.3% | Qwen3.8 Max (0902) |
| DTBench | 82.4% | 92.0% | Qwen3.8 Max (0902) |
| LMCA | 34.8% | 46.2% | Qwen3.8 Max (0902) |
| Creative writing (Lech Mazur) | 83.8% | Not measured | Only Gemini 2.5 Pro measured |
| Furniture assembly | Not measured | 20.0% | Only Qwen3.8 Max (0902) measured |
| LMArena Text | 1458 | 1483 | Qwen3.8 Max (0902) |
| LMArena Text: instruction following | 1437 | 1481 | Qwen3.8 Max (0902) |
| LMArena Text: creative writing | 1454 | 1477 | Qwen3.8 Max (0902) |
| LMArena Vision | 1263 | 1313 | Qwen3.8 Max (0902) |
| LMArena Text: English | 1458 | 1491 | Qwen3.8 Max (0902) |
| LMArena Text: non-English | 1452 | 1473 | Qwen3.8 Max (0902) |
| LMArena Text: Chinese | 1507 | 1539 | Qwen3.8 Max (0902) |
| LMArena Text: German | 1487 | 1478 | Gemini 2.5 Pro |
| LMArena Text: Japanese | 1461 | 1473 | Qwen3.8 Max (0902) |
| LMArena Text: Korean | 1434 | 1460 | Qwen3.8 Max (0902) |
| LMArena Text: French | 1473 | 1498 | Qwen3.8 Max (0902) |
| LMArena Text: Spanish | 1474 | 1489 | Qwen3.8 Max (0902) |
| LMArena Text: Russian | 1461 | 1482 | Qwen3.8 Max (0902) |
| LMArena Text: Polish | 1479 | 1471 | Gemini 2.5 Pro |
| LMArena Text: multi-turn | 1453 | 1489 | Qwen3.8 Max (0902) |
| LMArena Text: longer queries | 1449 | 1488 | Qwen3.8 Max (0902) |
| LMArena Text: writing and language | 1454 | 1477 | Qwen3.8 Max (0902) |
| LMArena Text: entertainment and media | 1441 | 1464 | Qwen3.8 Max (0902) |
| LMArena Vision: English | 1261 | 1311 | Qwen3.8 Max (0902) |
| LMArena Vision: Chinese | 1300 | 1358 | Qwen3.8 Max (0902) |
| LMArena Vision: reading text | 1270 | 1322 | Qwen3.8 Max (0902) |
| LMArena Vision: humor | 1262 | 1304 | Qwen3.8 Max (0902) |
| 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 | 1312 | Qwen3.8 Max (0902) |
| LMArena Document | 1421 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 9 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro | Qwen3.8 Max (0902) | 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 2.5 Pro$0.0063Fits in one request
Qwen3.8 Max (0902)$0.0050Fits in one request
Qwen3.8 Max (0902) costs less
Repository review
50K input + 3K output tokens
Gemini 2.5 Pro$0.092Fits in one request
Qwen3.8 Max (0902)$0.118Fits in one request
Gemini 2.5 Pro costs less
Agent loop
200K input + 10K output tokens
Gemini 2.5 Pro$0.350Fits in one request
Qwen3.8 Max (0902)$0.460Fits in one request
Gemini 2.5 Pro 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 | Qwen3.8 Max (0902) |
|---|---|---|
| Maker | Qwen | |
| Weights | No public weights listed | No public weights listed |
| Released | June 17, 2025 | September 3, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $1.25 | $2.00 |
| Output $/Mtok | $10.00 | $6.00 |
| Coding index | 37.0 | 63.5 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $0.64 | $1.32 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro better than Qwen3.8 Max (0902) for coding?
Pick Qwen3.8 Max (0902) for coding: it scores 63.5 on the Vibe Coding Index against 37.0 for Gemini 2.5 Pro. Pick Gemini 2.5 Pro when a solved task costs $0.64 against $1.32, or when the context window is larger, 1.05M against 1M tokens.
Which is cheaper, Gemini 2.5 Pro or Qwen3.8 Max (0902)?
Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Per solved SWE-bench Verified task, Gemini 2.5 Pro costs $0.64 and Qwen3.8 Max (0902) $1.32.
Which has the bigger context window, Gemini 2.5 Pro or Qwen3.8 Max (0902)?
Gemini 2.5 Pro, with 1.05M tokens against 1M.
How many benchmarks is the Gemini 2.5 Pro vs Qwen3.8 Max (0902) comparison based on?
66 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Pro's coding index rests on 2 independent benchmarks and Qwen3.8 Max (0902)'s on 2. Where only one model has a result, the page says so instead of naming a winner.