GPT-4 vs Qwen3.8 Max (0902)
Updated October 21, 2026. 34 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 34 shared
Decision reading
Pick Qwen3.8 Max (0902) for coding: it scores 63.5 on the Vibe Coding Index against 22.4 for GPT-4.
GPT-4 is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
Model AGPT-4OpenAI22.4/1001 independent benchmarkNo cost per solved taskModel BQwen3.8 Max (0902)Qwen63.5/1002 independent benchmarks$1.32 per solved task
- Shared results
- 34
- GPT-4 only
- 11
- Qwen3.8 Max (0902) only
- 79
- Like-for-like categories
- 6 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 22.4.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 45.4 against 6.7.
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
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
No call
Only Qwen3.8 Max (0902) has a Design Arena: websites result, 1275.
Directional only
Long documents
Listed context window
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) takes 1M tokens against 8K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.8 Max (0902)
GPT-4 $0.060, Qwen3.8 Max (0902) $0.0050 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.8 Max (0902) has the number, $1.32.
Directional only
At a glance
- Coding index
- GPT-4 22.4 from 1 benchmark, Qwen3.8 Max (0902) 63.5 from 2 benchmarks.
- Widest category
- Knowledge, 55.4 points apart on average over 4 shared benchmarks.
- Widest single gap
- AA Coding Index: GPT-4 13.1 against Qwen3.8 Max (0902) 76.2, 63.1 points apart on a 0 to 100 scale.
- Output price
- GPT-4 $60.00 against Qwen3.8 Max (0902) $6.00 per million output tokens, 10.0x apart.
- Context window
- GPT-4 takes 8K 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 | GPT-4 | Bars | Qwen3.8 Max (0902) | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 2 | ||
| Reasoning | 0 | 4 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 19 | ||
| All shared boards | 0 | 34 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index03
| Benchmark | GPT-4 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| SWE-bench Verified | 22.4% | Not measured | Only GPT-4 measured |
| SWE-bench Lite | 39.7% | Not measured | Only GPT-4 measured |
| SWE-bench (full test set) | 12.5% | Not measured | Only GPT-4 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 | 13.1 | 76.2 | Qwen3.8 Max (0902) |
| LiveCodeBench (Vals AI) | Not measured | 87.8% | Only Qwen3.8 Max (0902) measured |
| 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 |
| SciCode | Not measured | 53.2% | Only Qwen3.8 Max (0902) measured |
| FrontierSWE | Not measured | 17.8% | Only Qwen3.8 Max (0902) measured |
| LMArena Text: coding | 1209 | 1502 | Qwen3.8 Max (0902) |
| LMArena Text: software and IT | 1195 | 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 |
| Neither model has a result on the other 13 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.7 | 45.4 | Qwen3.8 Max (0902) |
| Epoch Capabilities Index | 125.7 | 157.4 | Qwen3.8 Max (0902) |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
| Benchmark | GPT-4 | 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 | 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 |
| APEX-Agents | Not measured | 63.3% | Only Qwen3.8 Max (0902) measured |
| LMArena Search | Not measured | 1261 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-4 | 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) | 34.9% | 92.8% | Qwen3.8 Max (0902) |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 43.1% | Only Qwen3.8 Max (0902) measured |
| GPQA Diamond (Epoch AI run) | Not measured | 92.7% | Only Qwen3.8 Max (0902) 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 |
| BIG-Bench Hard | 75.1% | Not measured | Only GPT-4 measured |
| LMArena Text: hard prompts | 1200 | 1496 | Qwen3.8 Max (0902) |
| LMArena Text: expert | 1149 | 1507 | Qwen3.8 Max (0902) |
| LMArena Text: hard prompts in English | 1209 | 1503 | Qwen3.8 Max (0902) |
| LMArena Vision: diagrams | Not measured | 1323 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: homework | Not measured | 1336 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 100.0% | Only Qwen3.8 Max (0902) measured |
| FrontierMath, tiers 1 to 3 | Not measured | 74.7% | Only Qwen3.8 Max (0902) measured |
| FrontierMath, tier 4 | Not measured | 46.3% | Only Qwen3.8 Max (0902) measured |
| ProofBench | Not measured | 58.0% | Only Qwen3.8 Max (0902) measured |
| GSM8K | 92.0% | Not measured | Only GPT-4 measured |
| LMArena Text: math | 1230 | 1501 | Qwen3.8 Max (0902) |
| LMArena Text: mathematical work | 1228 | 1491 | Qwen3.8 Max (0902) |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-4 | 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 |
| CorpFin (Vals AI) | Not measured | 65.8% | Only Qwen3.8 Max (0902) measured |
| TaxEval (Vals AI) | Not measured | 75.5% | Only Qwen3.8 Max (0902) measured |
| MortgageTax (Vals AI) | Not measured | 64.0% | Only Qwen3.8 Max (0902) measured |
| MedCode (Vals AI) | Not measured | 40.7% | Only Qwen3.8 Max (0902) measured |
| MMLU Pro (Artificial Analysis run) | 56.2% | Not measured | Only GPT-4 measured |
| SimpleQA Verified | Not measured | 47.3% | Only Qwen3.8 Max (0902) measured |
| MMLU | 86.4% | Not measured | Only GPT-4 measured |
| AI2 Reasoning Challenge | 96.3% | Not measured | Only GPT-4 measured |
| LMArena Text: science | 1177 | 1512 | Qwen3.8 Max (0902) |
| LMArena Text: medicine and healthcare | 1145 | 1503 | Qwen3.8 Max (0902) |
| LMArena Text: legal and government | 1191 | 1492 | Qwen3.8 Max (0902) |
| LMArena Text: business and finance | 1145 | 1480 | Qwen3.8 Max (0902) |
| Neither model has a result on the other 3 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-4 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1275 | Only Qwen3.8 Max (0902) measured |
| Design Arena: UI components | Not measured | 1340 | Only Qwen3.8 Max (0902) measured |
| Design Arena: game dev | Not measured | 1313 | Only Qwen3.8 Max (0902) measured |
| Design Arena: data viz | Not measured | 1281 | Only Qwen3.8 Max (0902) measured |
| Design Arena: 3D | Not measured | 1337 | Only Qwen3.8 Max (0902) measured |
| Design Arena: all code categories | Not measured | 1293 | Only Qwen3.8 Max (0902) measured |
| 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 index019
| Benchmark | GPT-4 | 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) | Not measured | 51.2% | Only Qwen3.8 Max (0902) measured |
| MedScribe (Vals AI) | Not measured | 85.0% | Only Qwen3.8 Max (0902) measured |
| Vals Multimodal Index | Not measured | 65.4% | Only Qwen3.8 Max (0902) measured |
| IFBench | 33.2% | Not measured | Only GPT-4 measured |
| Long context reasoning (AA-LCR) | Not measured | 80.3% | Only Qwen3.8 Max (0902) measured |
| DTBench | 62.7% | 92.0% | Qwen3.8 Max (0902) |
| LMCA | 17.1% | 46.2% | Qwen3.8 Max (0902) |
| Furniture assembly | Not measured | 20.0% | Only Qwen3.8 Max (0902) measured |
| HellaSwag | 95.3% | Not measured | Only GPT-4 measured |
| WinoGrande | 87.5% | Not measured | Only GPT-4 measured |
| LMArena Text | 1206 | 1483 | Qwen3.8 Max (0902) |
| LMArena Text: instruction following | 1201 | 1481 | Qwen3.8 Max (0902) |
| LMArena Text: creative writing | 1191 | 1477 | Qwen3.8 Max (0902) |
| LMArena Vision | Not measured | 1313 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: English | 1220 | 1491 | Qwen3.8 Max (0902) |
| LMArena Text: non-English | 1194 | 1473 | Qwen3.8 Max (0902) |
| LMArena Text: Chinese | 1184 | 1539 | Qwen3.8 Max (0902) |
| LMArena Text: German | 1198 | 1478 | Qwen3.8 Max (0902) |
| LMArena Text: Japanese | 1137 | 1473 | Qwen3.8 Max (0902) |
| LMArena Text: Korean | 1087 | 1460 | Qwen3.8 Max (0902) |
| LMArena Text: French | 1220 | 1498 | Qwen3.8 Max (0902) |
| LMArena Text: Spanish | 1197 | 1489 | Qwen3.8 Max (0902) |
| LMArena Text: Russian | 1195 | 1482 | Qwen3.8 Max (0902) |
| LMArena Text: Polish | 1265 | 1471 | Qwen3.8 Max (0902) |
| LMArena Text: multi-turn | 1206 | 1489 | Qwen3.8 Max (0902) |
| LMArena Text: longer queries | 1190 | 1488 | Qwen3.8 Max (0902) |
| LMArena Text: writing and language | 1219 | 1477 | Qwen3.8 Max (0902) |
| LMArena Text: entertainment and media | 1184 | 1464 | Qwen3.8 Max (0902) |
| LMArena Vision: English | Not measured | 1311 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: Chinese | Not measured | 1358 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: reading text | Not measured | 1322 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: humor | Not measured | 1304 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: creative writing | Not measured | 1312 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4 | 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
GPT-4$0.060Fits 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
GPT-4$1.68Exceeds the context window
Qwen3.8 Max (0902)$0.118Fits in one request
Qwen3.8 Max (0902) costs less
Agent loop
200K input + 10K output tokens
GPT-4$6.60Exceeds the context window
Qwen3.8 Max (0902)$0.460Fits in one request
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 GPT-4 | Qwen3.8 Max (0902) |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | May 28, 2023 | September 3, 2026 |
| Context window | 8K | 1M |
| Input $/Mtok | $30.00 | $2.00 |
| Output $/Mtok | $60.00 | $6.00 |
| Coding index | 22.4 | 63.5 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | Not computable | $1.32 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4 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 22.4 for GPT-4. GPT-4 is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
Which is cheaper, GPT-4 or Qwen3.8 Max (0902)?
GPT-4 costs $30.00 per million input tokens and $60.00 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Cost per solved task is known for Qwen3.8 Max (0902) only.
Which has the bigger context window, GPT-4 or Qwen3.8 Max (0902)?
Qwen3.8 Max (0902), with 1M tokens against 8K.
How many benchmarks is the GPT-4 vs Qwen3.8 Max (0902) comparison based on?
34 benchmarks have a result for both models as of October 21, 2026. GPT-4's coding index rests on 1 independent benchmark and Qwen3.8 Max (0902)'s on 2. Where only one model has a result, the page says so instead of naming a winner.