Grok 4.3 vs Qwen3.7 Max
Updated October 21, 2026. 55 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Qwen3.7 Max for coding: it scores 45.1 on the Vibe Coding Index against 22.5 for Grok 4.3.
Pick Grok 4.3 when output tokens cost 1.8x less, or when a solved task costs $0.31 against $4.69.
- Shared results
- 55
- Grok 4.3 only
- 49
- Qwen3.7 Max only
- 4
- 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
Qwen3.7 Max
Qwen3.7 Max scores 45.1 against 22.5.
One benchmark behind each score
Intelligence
AA Intelligence Index
Qwen3.7 Max
Qwen3.7 Max leads, 29.5 against 24.9.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.7 Max
Qwen3.7 Max leads, 22.5 against 15.5.
Same board, both measured
Reasoning
GPQA Diamond
Grok 4.3
Grok 4.3 leads, 91.4% against 90.2%.
Same board, both measured
Knowledge
MMLU Pro
Qwen3.7 Max
Qwen3.7 Max leads, 89.3% against 85.8%.
Same board, both measured
Web design
Design Arena: websites
Qwen3.7 Max
Qwen3.7 Max leads, 1274 against 1196.
Same board, both measured
Long documents
Listed context window
No call
Both take 1M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Grok 4.3
Grok 4.3 $0.0025, Qwen3.7 Max $0.0037 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Grok 4.3
Grok 4.3 $0.31, Qwen3.7 Max $4.69.
Published attempt cost and pass rate
At a glance
- Coding index
- Grok 4.3 22.5 from 1 benchmark, Qwen3.7 Max 45.1 from 1 benchmark.
- Widest category
- Agentic work, 17.4 points apart on average over 14 shared benchmarks.
- Widest single gap
- Excel Modeling Benchmark (Vals AI): Grok 4.3 18.4% against Qwen3.7 Max 57.0%, 38.6 points apart on a 0 to 100 scale.
- Output price
- Grok 4.3 $2.50 against Qwen3.7 Max $4.425 per million output tokens, 1.8x apart.
- Context window
- Both take 1M tokens.
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 | Grok 4.3 | Bars | Qwen3.7 Max | Ties |
|---|---|---|---|---|
| Coding | 1 | 11 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 1 | 13 | ||
| Reasoning | 1 | 4 | ||
| Math | 0 | 4 | ||
| Knowledge | 1 | 5 | ||
| Web design | 0 | 8 | ||
| General | 1 | 4 | ||
| All shared boards | 5 | 50 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index111
| Benchmark | Grok 4.3 | Qwen3.7 Max | Leader |
|---|---|---|---|
| LMArena WebDev | 1358 | 1515 | Qwen3.7 Max |
| AA Coding Index | 42.2 | 66.0 | Qwen3.7 Max |
| LiveCodeBench (Vals AI) | 84.5% | 87.1% | Qwen3.7 Max |
| SWE-bench Verified (Vals AI) | 71.4% | 68.8% | Grok 4.3 |
| Vibe Code Bench (Vals AI) | 19.4% | 47.7% | Qwen3.7 Max |
| Code migration (Vals AI) | 6.8% | 13.1% | Qwen3.7 Max |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Grok 4.3 measured |
| Terminal-Bench 2.1 (Vals AI) | 42.0% | 61.0% | Qwen3.7 Max |
| SkillsBench (Vals AI) | 40.6% | Not measured | Only Grok 4.3 measured |
| SciCode | 48.3% | 49.5% | Qwen3.7 Max |
| Terminal-Bench Hard (Artificial Analysis run) | 37.9% | 50.8% | Qwen3.7 Max |
| WeirdML | 49.9% | Not measured | Only Grok 4.3 measured |
| ALE-Bench | 944.2 | 1189.4 | Qwen3.7 Max |
| LMArena Text: coding | 1415 | Not measured | Only Grok 4.3 measured |
| LMArena Text: software and IT | 1416 | Not measured | Only Grok 4.3 measured |
| LMArena WebDev: React | 1353 | 1514 | Qwen3.7 Max |
| LMArena WebDev: HTML | 1367 | 1512 | Qwen3.7 Max |
| LMArena WebDev: from an image | 1375 | Not measured | Only Grok 4.3 measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Grok 4.3 | Qwen3.7 Max | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.9 | 29.5 | Qwen3.7 Max |
| Epoch Capabilities Index | Not measured | 154.0 | Only Qwen3.7 Max measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index113
| Benchmark | Grok 4.3 | Qwen3.7 Max | Leader |
|---|---|---|---|
| AA Agentic Index | 15.5 | 22.5 | Qwen3.7 Max |
| Design Arena: agents building web apps | 1126 | 1208 | Qwen3.7 Max |
| Design Arena: agents building full-stack apps | 1006 | 1191 | Qwen3.7 Max |
| Design Arena: agents building mobile apps | 1059 | 1153 | Qwen3.7 Max |
| Design Arena: agents building Android apps | 967 | 1165 | Qwen3.7 Max |
| Design Arena: agents building Godot games | 914 | 1187 | Qwen3.7 Max |
| Design Arena: agents building games | 1007 | 1161 | Qwen3.7 Max |
| Design Arena: HTML slides | 1008 | 1158 | Qwen3.7 Max |
| Design Arena: PowerPoint slides | 1012 | 1196 | Qwen3.7 Max |
| Finance Agent (Vals AI) | 37.7% | 47.8% | Qwen3.7 Max |
| Tax Agent Bench (Vals AI) | 6.2% | 15.8% | Qwen3.7 Max |
| Legal Research Bench (Vals AI) | 15.4% | 25.5% | Qwen3.7 Max |
| Excel Modeling Benchmark (Vals AI) | 18.4% | 57.0% | Qwen3.7 Max |
| τ²-Bench Telecom | 97.7% | 94.7% | Grok 4.3 |
| Vending-Bench 2 | $35 | Not measured | Only Grok 4.3 measured |
| LMArena Search | 1166 | Not measured | Only Grok 4.3 measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | Grok 4.3 | Qwen3.7 Max | Leader |
|---|---|---|---|
| GPQA Diamond | 91.4% | 90.2% | Grok 4.3 |
| MMMU Pro (Vals AI) | 83.1% | Not measured | Only Grok 4.3 measured |
| GPQA Diamond (Artificial Analysis run) | 90.1% | 92.3% | Qwen3.7 Max |
| Humanity's Last Exam (Artificial Analysis run) | 37.2% | 40.5% | Qwen3.7 Max |
| GPQA Diamond (Epoch AI run) | 88.8% | 90.9% | Qwen3.7 Max |
| SimpleBench | Not measured | 70.4% | Only Qwen3.7 Max measured |
| Chess puzzles | 18.0% | 26.0% | Qwen3.7 Max |
| Mystery game puzzles | Not measured | 32.0% | Only Qwen3.7 Max measured |
| EBR-bench | Not measured | 9.5% | Only Qwen3.7 Max measured |
| LMArena Text: hard prompts | 1396 | Not measured | Only Grok 4.3 measured |
| LMArena Text: expert | 1384 | Not measured | Only Grok 4.3 measured |
| LMArena Text: hard prompts in English | 1402 | Not measured | Only Grok 4.3 measured |
| LMArena Vision: diagrams | 1241 | Not measured | Only Grok 4.3 measured |
| LMArena Vision: homework | 1241 | Not measured | Only Grok 4.3 measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Grok 4.3 | Qwen3.7 Max | Leader |
|---|---|---|---|
| OTIS Mock AIME | 93.3% | 95.6% | Qwen3.7 Max |
| FrontierMath, tiers 1 to 3 | 42.8% | 64.6% | Qwen3.7 Max |
| FrontierMath, tier 4 | 14.6% | 34.1% | Qwen3.7 Max |
| ProofBench | 11.0% | 26.0% | Qwen3.7 Max |
| LMArena Text: math | 1387 | Not measured | Only Grok 4.3 measured |
| LMArena Text: mathematical work | 1396 | Not measured | Only Grok 4.3 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index15
| Benchmark | Grok 4.3 | Qwen3.7 Max | Leader |
|---|---|---|---|
| MMLU Pro | 85.8% | 89.3% | Qwen3.7 Max |
| LegalBench (Vals AI) | 84.5% | 84.9% | Qwen3.7 Max |
| CaseLaw (Vals AI) | 79.3% | Not measured | Only Grok 4.3 measured |
| CorpFin (Vals AI) | 68.5% | 63.7% | Grok 4.3 |
| TaxEval (Vals AI) | 70.8% | 75.3% | Qwen3.7 Max |
| MortgageTax (Vals AI) | 48.3% | Not measured | Only Grok 4.3 measured |
| MedCode (Vals AI) | 38.1% | 38.8% | Qwen3.7 Max |
| SimpleQA Verified | 33.2% | 55.8% | Qwen3.7 Max |
| LMArena Text: science | 1399 | Not measured | Only Grok 4.3 measured |
| LMArena Text: medicine and healthcare | 1384 | Not measured | Only Grok 4.3 measured |
| LMArena Text: legal and government | 1386 | Not measured | Only Grok 4.3 measured |
| LMArena Text: business and finance | 1381 | Not measured | Only Grok 4.3 measured |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | Grok 4.3 | Qwen3.7 Max | Leader |
|---|---|---|---|
| Design Arena: websites | 1196 | 1274 | Qwen3.7 Max |
| Design Arena: UI components | 1192 | 1269 | Qwen3.7 Max |
| Design Arena: game dev | 1174 | 1265 | Qwen3.7 Max |
| Design Arena: data viz | 1180 | 1275 | Qwen3.7 Max |
| Design Arena: 3D | 1125 | 1266 | Qwen3.7 Max |
| Design Arena: all code categories | 1187 | 1275 | Qwen3.7 Max |
| Design Arena: SVG | 1081 | 1216 | Qwen3.7 Max |
| Design Arena: ASCII art | 1125 | 1211 | Qwen3.7 Max |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | Grok 4.3 | Qwen3.7 Max | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 51.7% | Not measured | Only Grok 4.3 measured |
| SAGE (Vals AI) | 19.7% | Not measured | Only Grok 4.3 measured |
| MedScribe (Vals AI) | 74.4% | 79.4% | Qwen3.7 Max |
| Vals Multimodal Index | 43.3% | Not measured | Only Grok 4.3 measured |
| IFBench | 83.3% | 80.5% | Grok 4.3 |
| Long context reasoning (AA-LCR) | 75.0% | 79.0% | Qwen3.7 Max |
| DTBench | 90.7% | 92.3% | Qwen3.7 Max |
| LMCA | 38.3% | 44.0% | Qwen3.7 Max |
| LMArena Text | 1397 | Not measured | Only Grok 4.3 measured |
| LMArena Text: instruction following | 1366 | Not measured | Only Grok 4.3 measured |
| LMArena Text: creative writing | 1380 | Not measured | Only Grok 4.3 measured |
| LMArena Vision | 1229 | Not measured | Only Grok 4.3 measured |
| LMArena Text: English | 1404 | Not measured | Only Grok 4.3 measured |
| LMArena Text: non-English | 1385 | Not measured | Only Grok 4.3 measured |
| LMArena Text: Chinese | 1422 | Not measured | Only Grok 4.3 measured |
| LMArena Text: German | 1395 | Not measured | Only Grok 4.3 measured |
| LMArena Text: Japanese | 1379 | Not measured | Only Grok 4.3 measured |
| LMArena Text: Korean | 1354 | Not measured | Only Grok 4.3 measured |
| LMArena Text: French | 1411 | Not measured | Only Grok 4.3 measured |
| LMArena Text: Spanish | 1399 | Not measured | Only Grok 4.3 measured |
| LMArena Text: Russian | 1399 | Not measured | Only Grok 4.3 measured |
| LMArena Text: Polish | 1398 | Not measured | Only Grok 4.3 measured |
| LMArena Text: multi-turn | 1406 | Not measured | Only Grok 4.3 measured |
| LMArena Text: longer queries | 1393 | Not measured | Only Grok 4.3 measured |
| LMArena Text: writing and language | 1385 | Not measured | Only Grok 4.3 measured |
| LMArena Text: entertainment and media | 1370 | Not measured | Only Grok 4.3 measured |
| LMArena Vision: English | 1235 | Not measured | Only Grok 4.3 measured |
| LMArena Vision: Chinese | 1257 | Not measured | Only Grok 4.3 measured |
| LMArena Vision: reading text | 1235 | Not measured | Only Grok 4.3 measured |
| LMArena Vision: humor | 1222 | Not measured | Only Grok 4.3 measured |
| LMArena Vision: recognizing things | 1217 | Not measured | Only Grok 4.3 measured |
| LMArena Vision: creative writing | 1237 | Not measured | Only Grok 4.3 measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Grok 4.3 | Qwen3.7 Max | 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
Grok 4.3 costs less
Repository review
50K input + 3K output tokens
Grok 4.3 costs less
Agent loop
200K input + 10K output tokens
Grok 4.3 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 | SpaceXAI Grok 4.3 | Qwen3.7 Max |
|---|---|---|
| Maker | xAI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | April 30, 2026 | May 21, 2026 |
| Context window | 1M | 1M |
| Input $/Mtok | $1.25 | $1.475 |
| Output $/Mtok | $2.50 | $4.425 |
| Coding index | 22.5 | 45.1 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $0.31 | $4.69 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Grok 4.3 better than Qwen3.7 Max for coding?
Pick Qwen3.7 Max for coding: it scores 45.1 on the Vibe Coding Index against 22.5 for Grok 4.3. Pick Grok 4.3 when output tokens cost 1.8x less, or when a solved task costs $0.31 against $4.69.
Which is cheaper, Grok 4.3 or Qwen3.7 Max?
Grok 4.3 costs $1.25 per million input tokens and $2.50 per million output tokens; Qwen3.7 Max costs $1.475 and $4.425. Per solved SWE-bench Verified task, Grok 4.3 costs $0.31 and Qwen3.7 Max $4.69.
Which has the bigger context window, Grok 4.3 or Qwen3.7 Max?
Neither: both take 1M tokens.
How many benchmarks is the Grok 4.3 vs Qwen3.7 Max comparison based on?
55 benchmarks have a result for both models as of October 21, 2026. Grok 4.3's coding index rests on 1 independent benchmark and Qwen3.7 Max's on 1. Where only one model has a result, the page says so instead of naming a winner.