Grok 4.7 vs Qwen3.5 397B A17B
Grok 4.7 leads Qwen3.5 397B A17B on the Artificial Analysis Intelligence Index, 46.4 to 21.4, and Qwen3.5 397B A17B costs 2.6x less per output token ($2.34 vs $6.00 per million). Updated October 22, 2026; 56 benchmarks have a result for both.
Grok 4.7 or Qwen3.5 397B A17B: which to pick
Only Grok 4.7 has a coding score, 66.7 on the Vibe Coding Index; Qwen3.5 397B A17B has none, so the two cannot be ranked on coding.
Pick Qwen3.5 397B A17B for output tokens 2.6x cheaper ($2.34 vs $6.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
- Shared results
- 56
- Grok 4.7 only
- 43
- Qwen3.5 397B A17B only
- 9
- Like-for-like categories
- 8 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 Grok 4.7 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Grok 4.7
Grok 4.7 leads, 46.4 against 21.4.
Same board, both measured
Web design
Design Arena: websites
Grok 4.7
Grok 4.7 leads, 1255 against 1190.
Same board, both measured
General
Vals Index
No call
Only Grok 4.7 has a Vals Index result, 58.6%.
Directional only
Long documents
Listed context window
Grok 4.7
Grok 4.7 takes 500K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5 397B A17B
Grok 4.7 $0.0050, Qwen3.5 397B A17B $0.0016 per turn.
List prices
At a glance
- Coding index
- Grok 4.7 66.7 from 5 benchmarks, Qwen3.5 397B A17B not benchmarked.
- Widest category
- Agentic work, 29.7 points apart on average over 1 shared benchmark.
- Widest single gap
- LMArena WebDev: React: Grok 4.7 1663 against Qwen3.5 397B A17B 1388, 35.4 points apart on a 0 to 100 scale.
- Output price
- Grok 4.7 $6.00 against Qwen3.5 397B A17B $2.34 per million output tokens, 2.6x apart.
- Context window
- Grok 4.7 takes 500K tokens, Qwen3.5 397B A17B 262K.
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 4.7 | Bars | Qwen3.5 397B A17B | Ties |
|---|---|---|---|---|
| Coding | 4 | 2 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 4 | 4 | ||
| Math | 2 | 2 | ||
| Knowledge | 0 | 4 | ||
| Web design | 6 | 0 | ||
| General | 3 | 22 | ||
| All shared boards | 22 | 34 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index42
| Benchmark | Grok 4.7 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| LiveBench coding | 84.5% | Not measured | Only Grok 4.7 measured |
| LMArena WebDev | 1637 | 1400 | Grok 4.7 |
| Terminal-Bench 4 (Vals AI) | 28.8% | Not measured | Only Grok 4.7 measured |
| Vibe Code Bench (Vals AI) | 86.2% | Not measured | Only Grok 4.7 measured |
| Code migration (Vals AI) | 44.8% | Not measured | Only Grok 4.7 measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only Grok 4.7 measured |
| IOI (Vals AI) | 57.7% | Not measured | Only Grok 4.7 measured |
| Terminal-Bench 2.1 (Vals AI) | 73.4% | Not measured | Only Grok 4.7 measured |
| SWE-bench Multimodal (Vals AI) | 42.9% | Not measured | Only Grok 4.7 measured |
| CyberBench (Vals AI) | 69.5% | Not measured | Only Grok 4.7 measured |
| SciCode | 57.8% | 44.8% | Grok 4.7 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 40.9% | Only Qwen3.5 397B A17B measured |
| FrontierCode | 47.6% | Not measured | Only Grok 4.7 measured |
| FrontierSWE | 29.5% | Not measured | Only Grok 4.7 measured |
| ALE-Bench | Not measured | 621.9 | Only Qwen3.5 397B A17B measured |
| LMArena Text: coding | 1432 | 1464 | Qwen3.5 397B A17B |
| LMArena Text: software and IT | 1421 | 1463 | Qwen3.5 397B A17B |
| LMArena WebDev: React | 1663 | 1388 | Grok 4.7 |
| LMArena WebDev: HTML | 1627 | 1410 | Grok 4.7 |
| LMArena WebDev: from an image | 1586 | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Grok 4.7 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| AA Intelligence Index | 46.4 | 21.4 | Grok 4.7 |
| Epoch Capabilities Index | 154.4 | 146.8 | Grok 4.7 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Grok 4.7 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| LiveBench research | 86.4% | Not measured | Only Grok 4.7 measured |
| LiveBench browser | 60.0% | Not measured | Only Grok 4.7 measured |
| LiveBench long agentic | 50.1% | Not measured | Only Grok 4.7 measured |
| SREBench (Vals AI) | 3.8% | Not measured | Only Grok 4.7 measured |
| Finance Agent (Vals AI) | 52.3% | Not measured | Only Grok 4.7 measured |
| Tax Agent Bench (Vals AI) | 34.2% | Not measured | Only Grok 4.7 measured |
| Legal Research Bench (Vals AI) | 47.1% | Not measured | Only Grok 4.7 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 18.3% | Not measured | Only Grok 4.7 measured |
| Excel Modeling Benchmark (Vals AI) | 67.0% | Not measured | Only Grok 4.7 measured |
| BioMysteryBench (Vals AI) | 69.3% | Not measured | Only Grok 4.7 measured |
| Terminal-Bench-Science (Vals AI) | 10.0% | Not measured | Only Grok 4.7 measured |
| Vals Science Index | 34.8% | Not measured | Only Grok 4.7 measured |
| Robo-bench (Vals AI) | 0.2% | Not measured | Only Grok 4.7 measured |
| τ²-Bench Telecom | Not measured | 95.6% | Only Qwen3.5 397B A17B measured |
| APEX-Agents | 54.6% | 24.9% | Grok 4.7 |
| Vending-Bench 2 | $10,537 | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 25 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index44
| Benchmark | Grok 4.7 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| LiveBench reasoning | 82.7% | Not measured | Only Grok 4.7 measured |
| MysteryMechanism (Vals AI) | 25.2% | Not measured | Only Grok 4.7 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 89.3% | Only Qwen3.5 397B A17B measured |
| Humanity's Last Exam (Artificial Analysis run) | 43.1% | 29.0% | Grok 4.7 |
| GPQA Diamond (Epoch AI run) | 92.7% | 86.4% | Grok 4.7 |
| ARC-AGI | 90.2% | Not measured | Only Grok 4.7 measured |
| ARC-AGI-2 | 61.4% | Not measured | Only Grok 4.7 measured |
| Chess puzzles | 41.0% | Not measured | Only Grok 4.7 measured |
| Mystery game puzzles | 29.0% | 18.0% | Grok 4.7 |
| LMArena Text: hard prompts | 1415 | 1448 | Qwen3.5 397B A17B |
| LMArena Text: expert | 1439 | 1462 | Qwen3.5 397B A17B |
| LMArena Text: hard prompts in English | 1427 | 1450 | Qwen3.5 397B A17B |
| LMArena Vision: diagrams | 1254 | 1277 | Qwen3.5 397B A17B |
| LMArena Vision: homework | 1309 | 1292 | Grok 4.7 |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | Grok 4.7 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.1% | 88.9% | Grok 4.7 |
| FrontierMath, tiers 1 to 3 | 53.0% | 31.2% | Grok 4.7 |
| FrontierMath, tier 4 | 17.1% | Not measured | Only Grok 4.7 measured |
| ProofBench | 26.0% | Not measured | Only Grok 4.7 measured |
| LMArena Text: math | 1414 | 1453 | Qwen3.5 397B A17B |
| LMArena Text: mathematical work | 1435 | 1454 | Qwen3.5 397B A17B |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Grok 4.7 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 84.4% | Not measured | Only Grok 4.7 measured |
| MedCode (Vals AI) | 49.5% | Not measured | Only Grok 4.7 measured |
| SimpleQA Verified | 56.0% | Not measured | Only Grok 4.7 measured |
| LMArena Text: science | 1419 | 1457 | Qwen3.5 397B A17B |
| LMArena Text: medicine and healthcare | 1395 | 1455 | Qwen3.5 397B A17B |
| LMArena Text: legal and government | 1423 | 1441 | Qwen3.5 397B A17B |
| LMArena Text: business and finance | 1389 | 1435 | Qwen3.5 397B A17B |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Grok 4.7 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| Design Arena: websites | 1255 | 1190 | Grok 4.7 |
| Design Arena: UI components | 1275 | 1160 | Grok 4.7 |
| Design Arena: game dev | 1314 | 1140 | Grok 4.7 |
| Design Arena: data viz | 1238 | 1175 | Grok 4.7 |
| Design Arena: 3D | 1274 | 1160 | Grok 4.7 |
| Design Arena: all code categories | 1273 | 1179 | Grok 4.7 |
| Design Arena: SVG | Not measured | 1139 | Only Qwen3.5 397B A17B measured |
| LiveBench design | 78.0% | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index322
| Benchmark | Grok 4.7 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| Vals Index | 58.6% | Not measured | Only Grok 4.7 measured |
| LiveBench data analysis | 76.9% | Not measured | Only Grok 4.7 measured |
| Public Benefits Bench (Vals AI) | 65.6% | Not measured | Only Grok 4.7 measured |
| SAGE (Vals AI) | 40.8% | Not measured | Only Grok 4.7 measured |
| MedScribe (Vals AI) | 89.4% | Not measured | Only Grok 4.7 measured |
| IFBench | Not measured | 78.8% | Only Qwen3.5 397B A17B measured |
| Long context reasoning (AA-LCR) | 80.0% | 77.3% | Grok 4.7 |
| DTBench | 96.0% | 87.5% | Grok 4.7 |
| LMCA | 49.4% | 37.9% | Grok 4.7 |
| Furniture assembly | 20.8% | Not measured | Only Grok 4.7 measured |
| LMArena Text | 1399 | 1437 | Qwen3.5 397B A17B |
| LMArena Text: instruction following | 1406 | 1424 | Qwen3.5 397B A17B |
| LMArena Text: creative writing | 1381 | 1402 | Qwen3.5 397B A17B |
| LMArena Vision | 1231 | 1262 | Qwen3.5 397B A17B |
| LMArena Text: English | 1411 | 1443 | Qwen3.5 397B A17B |
| LMArena Text: non-English | 1386 | 1430 | Qwen3.5 397B A17B |
| LMArena Text: Chinese | 1449 | 1498 | Qwen3.5 397B A17B |
| LMArena Text: German | 1366 | 1445 | Qwen3.5 397B A17B |
| LMArena Text: Japanese | 1359 | 1429 | Qwen3.5 397B A17B |
| LMArena Text: Korean | 1383 | 1384 | Qwen3.5 397B A17B |
| LMArena Text: French | 1431 | 1462 | Qwen3.5 397B A17B |
| LMArena Text: Spanish | 1406 | 1441 | Qwen3.5 397B A17B |
| LMArena Text: Russian | 1399 | 1430 | Qwen3.5 397B A17B |
| LMArena Text: Polish | 1420 | 1447 | Qwen3.5 397B A17B |
| LMArena Text: multi-turn | 1394 | 1446 | Qwen3.5 397B A17B |
| LMArena Text: longer queries | 1416 | 1441 | Qwen3.5 397B A17B |
| LMArena Text: writing and language | 1394 | 1415 | Qwen3.5 397B A17B |
| LMArena Text: entertainment and media | 1376 | 1399 | Qwen3.5 397B A17B |
| LMArena Vision: English | 1229 | 1268 | Qwen3.5 397B A17B |
| LMArena Vision: Chinese | 1250 | 1314 | Qwen3.5 397B A17B |
| LMArena Vision: reading text | 1241 | 1271 | Qwen3.5 397B A17B |
| LMArena Vision: humor | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: captioning | Not measured | 1230 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: recognizing things | Not measured | 1265 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: creative writing | 1217 | 1260 | Qwen3.5 397B A17B |
| 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 | Grok 4.7 | Qwen3.5 397B A17B | 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
Qwen3.5 397B A17B costs less
Repository review
50K input + 3K output tokens
Qwen3.5 397B A17B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5 397B A17B 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 4.7 | Qwen3.5 397B A17B |
|---|---|---|
| Maker | xAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | September 21, 2026 | February 16, 2026 |
| Context window | 500K | 262K |
| Input $/Mtok | $2.00 | $0.39 |
| Output $/Mtok | $6.00 | $2.34 |
| Coding index | 66.7 | Not benchmarked |
| Independent measurements behind it | 5 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Grok 4.7 better than Qwen3.5 397B A17B for coding?
Only Grok 4.7 has a coding score, 66.7 on the Vibe Coding Index; Qwen3.5 397B A17B has none, so the two cannot be ranked on coding. Pick Qwen3.5 397B A17B for output tokens 2.6x cheaper ($2.34 vs $6.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, Grok 4.7 or Qwen3.5 397B A17B?
Grok 4.7 costs $2.00 per million input tokens and $6.00 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for neither of them.
Which has the bigger context window, Grok 4.7 or Qwen3.5 397B A17B?
Grok 4.7, with 500K tokens against 262K.
How many benchmarks is the Grok 4.7 vs Qwen3.5 397B A17B comparison based on?
56 benchmarks have a result for both models as of October 22, 2026. Grok 4.7's coding index rests on 5 independent benchmarks and Qwen3.5 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.