o3 vs Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads o3 on the Artificial Analysis Intelligence Index, 45.4 to 20.2, and Qwen3.8 Max (0902) costs 1.3x less per output token ($6.00 vs $8.00 per million). Updated October 21, 2026; 65 benchmarks have a result for both.
o3 or Qwen3.8 Max (0902): which to pick
Only Qwen3.8 Max (0902) has a coding score, 62.4 on the Vibe Coding Index; o3 has none, so the two cannot be ranked on coding.
Pick o3 for a lower cost per solved task ($0.571 against $1.32) and work measured by LegalBench (Vals AI) or MortgageTax (Vals AI), where it leads.
- Shared results
- 65
- o3 only
- 37
- Qwen3.8 Max (0902) only
- 48
- 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 Qwen3.8 Max (0902) has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 45.4 against 20.2.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3.8 Max (0902) has a AA Agentic Index result, 56.0.
Directional only
Reasoning
GPQA Diamond
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 93.7% against 84.1%.
Same board, both measured
Math
AIME
No call
Only o3 has a AIME result, 85.3%.
Directional only
Knowledge
MMLU Pro
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 88.6% against 85.6%.
Same board, both measured
Web design
Design Arena: websites
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 1275 against 1036.
Same board, both measured
Long documents
Listed context window
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) takes 1M tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.8 Max (0902)
o3 $0.0060, Qwen3.8 Max (0902) $0.0050 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
o3
o3 $0.571, Qwen3.8 Max (0902) $1.32.
Published attempt cost and pass rate
At a glance
- Coding index
- o3 not benchmarked, Qwen3.8 Max (0902) 62.4 from 5 benchmarks.
- Widest category
- Web design, 29.9 points apart on average over 5 shared benchmarks.
- Widest single gap
- FrontierMath, tiers 1 to 3: o3 33.3% against Qwen3.8 Max (0902) 74.7%, 41.4 points apart on a 0 to 100 scale.
- Output price
- o3 $8.00 against Qwen3.8 Max (0902) $6.00 per million output tokens, 1.3x apart.
- Context window
- o3 takes 200K 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 | o3 | Bars | Qwen3.8 Max (0902) | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 2 | ||
| Reasoning | 0 | 12 | ||
| Math | 0 | 4 | ||
| Knowledge | 4 | 7 | ||
| Web design | 0 | 5 | ||
| General | 0 | 28 | ||
| All shared boards | 4 | 61 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | o3 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| Aider polyglot | 81.3% | Not measured | Only o3 measured |
| SWE-bench Verified | 58.4% | Not measured | Only o3 measured |
| SWE-bench Multimodal | 36.0% | Not measured | Only o3 measured |
| LiveBench coding | Not measured | 60.3% | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev | Not measured | 1674 | Only Qwen3.8 Max (0902) measured |
| AA Coding Index | Not measured | 76.2 | Only Qwen3.8 Max (0902) measured |
| LiveCodeBench (Vals AI) | 83.9% | 87.8% | Qwen3.8 Max (0902) |
| SWE-bench Verified (Vals AI) | Not measured | 85.6% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 34.3% | Only Qwen3.8 Max (0902) measured |
| Vibe Code Bench (Vals AI) | Not measured | 64.7% | Only Qwen3.8 Max (0902) measured |
| 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) | 80.8% | Not measured | Only o3 measured |
| SciCode | Not measured | 53.2% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench Hard (Artificial Analysis run) | 37.1% | Not measured | Only o3 measured |
| FrontierSWE | Not measured | 17.8% | Only Qwen3.8 Max (0902) measured |
| GSO-Bench | 8.8% | Not measured | Only o3 measured |
| WeirdML | 52.4% | Not measured | Only o3 measured |
| ALE-Bench | 933.5 | Not measured | Only o3 measured |
| LMArena Text: coding | 1407 | 1502 | Qwen3.8 Max (0902) |
| LMArena Text: software and IT | 1415 | 1498 | Qwen3.8 Max (0902) |
| LMArena WebDev: React | Not measured | 1692 | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev: HTML | Not measured | 1649 | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev: from an image | Not measured | 1637 | Only Qwen3.8 Max (0902) measured |
| SciCode | 9.2% | Not measured | Only o3 measured |
| Neither model has a result on the other 8 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | o3 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.2 | 45.4 | Qwen3.8 Max (0902) |
| Epoch Capabilities Index | 146.7 | 157.4 | Qwen3.8 Max (0902) |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index25 boards, none shared
| Benchmark | o3 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 56.0 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building web apps | Not measured | 1300 | 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 | 1224 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building Android apps | Not measured | 1202 | 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 | 1258 | Only Qwen3.8 Max (0902) measured |
| Design Arena: spreadsheets | Not measured | 937 | 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 | 80.7% | Not measured | Only o3 measured |
| APEX-Agents | Not measured | 63.3% | Only Qwen3.8 Max (0902) measured |
| METR time horizons | 65.4% | Not measured | Only o3 measured |
| GDPval | 30.8% | Not measured | Only o3 measured |
| DeepResearch Bench | 45.2% | Not measured | Only o3 measured |
| OSWorld | 23.0% | Not measured | Only o3 measured |
| LMArena Search | Not measured | 1261 | Only Qwen3.8 Max (0902) measured |
| Berkeley Function Calling Leaderboard (BFCL) | 63.0% | Not measured | Only o3 measured |
| BrowseComp-Plus | 65.9% | Not measured | Only o3 measured |
| Neither model has a result on the other 16 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index012
| Benchmark | o3 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| GPQA Diamond | 84.1% | 93.7% | Qwen3.8 Max (0902) |
| 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) | 80.4% | 88.0% | Qwen3.8 Max (0902) |
| GPQA Diamond (Artificial Analysis run) | 82.7% | 92.8% | Qwen3.8 Max (0902) |
| Humanity's Last Exam (Artificial Analysis run) | 20.1% | 43.1% | Qwen3.8 Max (0902) |
| GPQA Diamond (Epoch AI run) | 81.8% | 92.7% | Qwen3.8 Max (0902) |
| ARC-AGI | 60.8% | Not measured | Only o3 measured |
| ARC-AGI-2 | 6.5% | Not measured | Only o3 measured |
| SimpleBench | 53.1% | Not measured | Only o3 measured |
| Chess puzzles | 37.0% | 46.0% | Qwen3.8 Max (0902) |
| Mystery game puzzles | 29.0% | 38.0% | Qwen3.8 Max (0902) |
| VPCT | 52.0% | Not measured | Only o3 measured |
| LMArena Text: hard prompts | 1402 | 1496 | Qwen3.8 Max (0902) |
| LMArena Text: expert | 1402 | 1507 | Qwen3.8 Max (0902) |
| LMArena Text: hard prompts in English | 1411 | 1503 | Qwen3.8 Max (0902) |
| LMArena Vision: diagrams | 1220 | 1323 | Qwen3.8 Max (0902) |
| LMArena Vision: homework | 1234 | 1336 | Qwen3.8 Max (0902) |
| Kagi LLM Benchmark | 67.6% | Not measured | Only o3 measured |
| Neither model has a result on the other 3 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | o3 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AIME | 85.3% | Not measured | Only o3 measured |
| MATH 500 (Vals AI) | 94.6% | Not measured | Only o3 measured |
| MGSM (Vals AI) | 91.8% | Not measured | Only o3 measured |
| AA Math Index | 88.3 | Not measured | Only o3 measured |
| AIME 2025 (Artificial Analysis run) | 88.3% | Not measured | Only o3 measured |
| OTIS Mock AIME | 84.4% | 100.0% | Qwen3.8 Max (0902) |
| FrontierMath, tiers 1 to 3 | 33.3% | 74.7% | Qwen3.8 Max (0902) |
| FrontierMath, tier 4 | Not measured | 46.3% | Only Qwen3.8 Max (0902) measured |
| ProofBench | Not measured | 58.0% | Only Qwen3.8 Max (0902) measured |
| MATH level 5 | 97.8% | Not measured | Only o3 measured |
| LMArena Text: math | 1426 | 1501 | Qwen3.8 Max (0902) |
| LMArena Text: mathematical work | 1423 | 1491 | Qwen3.8 Max (0902) |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index47
| Benchmark | o3 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| MMLU Pro | 85.6% | 88.6% | Qwen3.8 Max (0902) |
| LegalBench (Vals AI) | 83.8% | 83.6% | o3 |
| CorpFin (Vals AI) | 59.7% | 65.8% | Qwen3.8 Max (0902) |
| TaxEval (Vals AI) | 74.6% | 75.5% | Qwen3.8 Max (0902) |
| MortgageTax (Vals AI) | 65.7% | 64.0% | o3 |
| MedQA (Vals AI) | 96.1% | Not measured | Only o3 measured |
| MedCode (Vals AI) | 47.3% | 40.7% | o3 |
| MMLU Pro (Artificial Analysis run) | 85.3% | Not measured | Only o3 measured |
| SimpleQA Verified | 49.4% | 47.3% | o3 |
| GeoBench | 74.0% | Not measured | Only o3 measured |
| LMArena Text: science | 1429 | 1512 | Qwen3.8 Max (0902) |
| LMArena Text: medicine and healthcare | 1448 | 1503 | Qwen3.8 Max (0902) |
| LMArena Text: legal and government | 1428 | 1492 | Qwen3.8 Max (0902) |
| LMArena Text: business and finance | 1393 | 1480 | Qwen3.8 Max (0902) |
| FACTS Benchmark Suite | 44.4% | Not measured | Only o3 measured |
| Neither model has a result on the other 3 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | o3 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| Design Arena: websites | 1036 | 1275 | Qwen3.8 Max (0902) |
| Design Arena: UI components | 1017 | 1340 | Qwen3.8 Max (0902) |
| Design Arena: game dev | 1034 | 1313 | Qwen3.8 Max (0902) |
| Design Arena: data viz | 1200 | 1282 | Qwen3.8 Max (0902) |
| Design Arena: 3D | Not measured | 1337 | Only Qwen3.8 Max (0902) measured |
| Design Arena: all code categories | 1020 | 1293 | Qwen3.8 Max (0902) |
| Design Arena: ASCII art | Not measured | 1200 | 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 index028
| Benchmark | o3 | 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) | 41.8% | 51.2% | Qwen3.8 Max (0902) |
| MedScribe (Vals AI) | 76.7% | 85.0% | Qwen3.8 Max (0902) |
| Vals Multimodal Index | Not measured | 65.4% | Only Qwen3.8 Max (0902) measured |
| IFBench | 71.4% | Not measured | Only o3 measured |
| Long context reasoning (AA-LCR) | 74.7% | 80.3% | Qwen3.8 Max (0902) |
| DTBench | 84.8% | 92.0% | Qwen3.8 Max (0902) |
| LMCA | 39.7% | 46.2% | Qwen3.8 Max (0902) |
| Fiction.LiveBench | 88.9% | Not measured | Only o3 measured |
| Creative writing (Lech Mazur) | 83.9% | Not measured | Only o3 measured |
| CL-bench | 17.8% | Not measured | Only o3 measured |
| Furniture assembly | Not measured | 20.0% | Only Qwen3.8 Max (0902) measured |
| LMArena Text | 1410 | 1483 | Qwen3.8 Max (0902) |
| LMArena Text: instruction following | 1368 | 1481 | Qwen3.8 Max (0902) |
| LMArena Text: creative writing | 1359 | 1477 | Qwen3.8 Max (0902) |
| LMArena Vision | 1214 | 1313 | Qwen3.8 Max (0902) |
| LMArena Text: English | 1417 | 1491 | Qwen3.8 Max (0902) |
| LMArena Text: non-English | 1401 | 1473 | Qwen3.8 Max (0902) |
| LMArena Text: Chinese | 1437 | 1539 | Qwen3.8 Max (0902) |
| LMArena Text: German | 1420 | 1478 | Qwen3.8 Max (0902) |
| LMArena Text: Japanese | 1403 | 1473 | Qwen3.8 Max (0902) |
| LMArena Text: Korean | 1370 | 1460 | Qwen3.8 Max (0902) |
| LMArena Text: French | 1430 | 1498 | Qwen3.8 Max (0902) |
| LMArena Text: Spanish | 1395 | 1489 | Qwen3.8 Max (0902) |
| LMArena Text: Russian | 1406 | 1482 | Qwen3.8 Max (0902) |
| LMArena Text: Polish | 1438 | 1471 | Qwen3.8 Max (0902) |
| LMArena Text: multi-turn | 1405 | 1489 | Qwen3.8 Max (0902) |
| LMArena Text: longer queries | 1372 | 1488 | Qwen3.8 Max (0902) |
| LMArena Text: writing and language | 1372 | 1477 | Qwen3.8 Max (0902) |
| LMArena Text: entertainment and media | 1373 | 1464 | Qwen3.8 Max (0902) |
| LMArena Vision: English | 1221 | 1311 | Qwen3.8 Max (0902) |
| LMArena Vision: Chinese | 1237 | 1358 | Qwen3.8 Max (0902) |
| LMArena Vision: reading text | 1218 | 1322 | Qwen3.8 Max (0902) |
| LMArena Vision: humor | 1222 | 1304 | Qwen3.8 Max (0902) |
| LMArena Vision: captioning | 1210 | Not measured | Only o3 measured |
| LMArena Vision: recognizing things | 1234 | Not measured | Only o3 measured |
| LMArena Vision: creative writing | 1201 | 1312 | Qwen3.8 Max (0902) |
| Neither model has a result on the other 8 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | o3 | 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
Qwen3.8 Max (0902) costs less
Repository review
50K input + 3K output tokens
Qwen3.8 Max (0902) costs less
Agent loop
200K input + 10K output tokens
Qwen3.8 Max (0902) 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 | OpenAI o3 | Qwen3.8 Max (0902) |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | April 16, 2025 | September 3, 2026 |
| Context window | 200K | 1M |
| Input $/Mtok | $2.00 | $2.00 |
| Output $/Mtok | $8.00 | $6.00 |
| Coding index | Not benchmarked | 62.4 |
| Independent measurements behind it | 0 | 5 |
| Cost per solved task | $0.571 | $1.32 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is o3 better than Qwen3.8 Max (0902) for coding?
Only Qwen3.8 Max (0902) has a coding score, 62.4 on the Vibe Coding Index; o3 has none, so the two cannot be ranked on coding. Pick o3 for a lower cost per solved task ($0.571 against $1.32) and work measured by LegalBench (Vals AI) or MortgageTax (Vals AI), where it leads.
Which is cheaper, o3 or Qwen3.8 Max (0902)?
o3 costs $2.00 per million input tokens and $8.00 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Per solved SWE-bench Verified task, o3 costs $0.571 and Qwen3.8 Max (0902) $1.32.
Which has the bigger context window, o3 or Qwen3.8 Max (0902)?
Qwen3.8 Max (0902), with 1M tokens against 200K.
How many benchmarks is the o3 vs Qwen3.8 Max (0902) comparison based on?
65 benchmarks have a result for both models as of October 21, 2026. o3's coding index rests on 0 independent benchmarks and Qwen3.8 Max (0902)'s on 5. Where only one model has a result, the page says so instead of naming a winner.