Grok 4.7 vs Qwen3 235B A22B Instruct 2507
Grok 4.7 leads Qwen3 235B A22B Instruct 2507 on the Artificial Analysis Intelligence Index, 46.4 to 12.0, and Qwen3 235B A22B Instruct 2507 costs 7.7x less per output token ($0.775 vs $6.00 per million). Updated October 22, 2026; 14 benchmarks have a result for both.
vs boards won of 14 shared
Grok 4.7 or Qwen3 235B A22B Instruct 2507: which to pick
Only Grok 4.7 has a coding score, 66.7 on the Vibe Coding Index; Qwen3 235B A22B Instruct 2507 has none, so the two cannot be ranked on coding.
Pick Qwen3 235B A22B Instruct 2507 for output tokens 7.7x cheaper ($0.775 vs $6.00 per million).
Model AGrok 4.7xAI66.7/1005 independent benchmarksNo cost per solved taskModel BQwen3 235B A22B Instruct 2507QwenNot benchmarkedNo coding benchmarkNo cost per solved task
- Shared results
- 14
- Grok 4.7 only
- 88
- Qwen3 235B A22B Instruct 2507 only
- 10
- Like-for-like categories
- 5 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 12.0.
Same board, both measured
Web design
Design Arena: websites
Grok 4.7
Grok 4.7 leads, 1254 against 1058.
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 235B A22B Instruct 2507
Grok 4.7 $0.0050, Qwen3 235B A22B Instruct 2507 $0.0005 per turn.
List prices
At a glance
- Coding index
- Grok 4.7 66.7 from 5 benchmarks, Qwen3 235B A22B Instruct 2507 not benchmarked.
- Widest category
- Reasoning, 55.5 points apart on average over 3 shared benchmarks.
- Widest single gap
- ARC-AGI: Grok 4.7 90.2% against Qwen3 235B A22B Instruct 2507 11.0%, 79.2 points apart on a 0 to 100 scale.
- Output price
- Grok 4.7 $6.00 against Qwen3 235B A22B Instruct 2507 $0.775 per million output tokens, 7.7x apart.
- Context window
- Grok 4.7 takes 500K tokens, Qwen3 235B A22B Instruct 2507 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 235B A22B Instruct 2507 | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 3 | 0 | ||
| Web design | 6 | 0 | ||
| General | 3 | 0 | ||
| All shared boards | 14 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | Grok 4.7 | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| LiveBench coding | 84.5% | Not measured | Only Grok 4.7 measured |
| LMArena WebDev | 1637 | Not measured | Only Grok 4.7 measured |
| 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 |
| LiveCodeBench (Artificial Analysis run) | Not measured | 78.8% | Only Qwen3 235B A22B Instruct 2507 measured |
| SciCode | 57.8% | 41.4% | Grok 4.7 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 15.2% | Only Qwen3 235B A22B Instruct 2507 measured |
| FrontierCode | 47.6% | Not measured | Only Grok 4.7 measured |
| FrontierSWE | 29.5% | Not measured | Only Grok 4.7 measured |
| WeirdML | Not measured | 38.7% | Only Qwen3 235B A22B Instruct 2507 measured |
| LMArena Text: coding | 1432 | Not measured | Only Grok 4.7 measured |
| LMArena Text: software and IT | 1421 | Not measured | Only Grok 4.7 measured |
| LMArena WebDev: React | 1663 | Not measured | Only Grok 4.7 measured |
| LMArena WebDev: HTML | 1627 | Not measured | Only Grok 4.7 measured |
| LMArena WebDev: from an image | 1586 | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Grok 4.7 | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| AA Intelligence Index | 46.4 | 12.0 | Grok 4.7 |
| Epoch Capabilities Index | 154.4 | Not measured | Only Grok 4.7 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
| Benchmark | Grok 4.7 | Qwen3 235B A22B Instruct 2507 | 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 | 53.2% | Only Qwen3 235B A22B Instruct 2507 measured |
| APEX-Agents | 54.6% | Not measured | Only Grok 4.7 measured |
| Vending-Bench 2 | $10,537 | Not measured | Only Grok 4.7 measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 52.1% | Only Qwen3 235B A22B Instruct 2507 measured |
| Neither model has a result on the other 25 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Grok 4.7 | Qwen3 235B A22B Instruct 2507 | 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 | 79.0% | Only Qwen3 235B A22B Instruct 2507 measured |
| Humanity's Last Exam (Artificial Analysis run) | 43.1% | 15.9% | Grok 4.7 |
| GPQA Diamond (Epoch AI run) | 92.7% | Not measured | Only Grok 4.7 measured |
| ARC-AGI | 90.2% | 11.0% | Grok 4.7 |
| ARC-AGI-2 | 61.4% | 1.3% | Grok 4.7 |
| Chess puzzles | 41.0% | Not measured | Only Grok 4.7 measured |
| Mystery game puzzles | 29.0% | Not measured | Only Grok 4.7 measured |
| LMArena Text: hard prompts | 1415 | Not measured | Only Grok 4.7 measured |
| LMArena Text: expert | 1439 | Not measured | Only Grok 4.7 measured |
| LMArena Text: hard prompts in English | 1427 | Not measured | Only Grok 4.7 measured |
| LMArena Vision: diagrams | 1254 | Not measured | Only Grok 4.7 measured |
| LMArena Vision: homework | 1309 | Not measured | Only Grok 4.7 measured |
| Humanity's Last Exam (Scale run) | 23.4% | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 8 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Grok 4.7 | Qwen3 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 91.0 | Only Qwen3 235B A22B Instruct 2507 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 91.0% | Only Qwen3 235B A22B Instruct 2507 measured |
| OTIS Mock AIME | 98.1% | Not measured | Only Grok 4.7 measured |
| FrontierMath, tiers 1 to 3 | 53.0% | Not measured | Only Grok 4.7 measured |
| 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 | Not measured | Only Grok 4.7 measured |
| LMArena Text: mathematical work | 1435 | Not measured | Only Grok 4.7 measured |
| MathArena | 41.1% | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Grok 4.7 | Qwen3 235B A22B Instruct 2507 | 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 |
| MMLU Pro (Artificial Analysis run) | Not measured | 84.3% | Only Qwen3 235B A22B Instruct 2507 measured |
| SimpleQA Verified | 56.0% | Not measured | Only Grok 4.7 measured |
| LMArena Text: science | 1419 | Not measured | Only Grok 4.7 measured |
| LMArena Text: medicine and healthcare | 1395 | Not measured | Only Grok 4.7 measured |
| LMArena Text: legal and government | 1423 | Not measured | Only Grok 4.7 measured |
| LMArena Text: business and finance | 1389 | Not measured | Only Grok 4.7 measured |
| PRBench Legal | 47.6% | Not measured | Only Grok 4.7 measured |
| 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 235B A22B Instruct 2507 | Leader |
|---|---|---|---|
| Design Arena: websites | 1254 | 1058 | Grok 4.7 |
| Design Arena: UI components | 1276 | 963 | Grok 4.7 |
| Design Arena: game dev | 1314 | 951 | Grok 4.7 |
| Design Arena: data viz | 1238 | 1070 | Grok 4.7 |
| Design Arena: 3D | 1274 | 994 | Grok 4.7 |
| Design Arena: all code categories | 1272 | 1038 | Grok 4.7 |
| LiveBench design | 78.0% | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Grok 4.7 | Qwen3 235B A22B Instruct 2507 | 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 | 51.2% | Only Qwen3 235B A22B Instruct 2507 measured |
| Long context reasoning (AA-LCR) | 80.0% | 72.0% | Grok 4.7 |
| DTBench | 96.0% | 78.4% | Grok 4.7 |
| LMCA | 49.4% | 23.5% | Grok 4.7 |
| Furniture assembly | 20.8% | Not measured | Only Grok 4.7 measured |
| LMArena Text | 1399 | Not measured | Only Grok 4.7 measured |
| LMArena Text: instruction following | 1406 | Not measured | Only Grok 4.7 measured |
| LMArena Text: creative writing | 1381 | Not measured | Only Grok 4.7 measured |
| LMArena Vision | 1231 | Not measured | Only Grok 4.7 measured |
| LMArena Text: English | 1411 | Not measured | Only Grok 4.7 measured |
| LMArena Text: non-English | 1386 | Not measured | Only Grok 4.7 measured |
| LMArena Text: Chinese | 1449 | Not measured | Only Grok 4.7 measured |
| LMArena Text: German | 1366 | Not measured | Only Grok 4.7 measured |
| LMArena Text: Japanese | 1359 | Not measured | Only Grok 4.7 measured |
| LMArena Text: Korean | 1383 | Not measured | Only Grok 4.7 measured |
| LMArena Text: French | 1431 | Not measured | Only Grok 4.7 measured |
| LMArena Text: Spanish | 1406 | Not measured | Only Grok 4.7 measured |
| LMArena Text: Russian | 1399 | Not measured | Only Grok 4.7 measured |
| LMArena Text: Polish | 1420 | Not measured | Only Grok 4.7 measured |
| LMArena Text: multi-turn | 1394 | Not measured | Only Grok 4.7 measured |
| LMArena Text: longer queries | 1416 | Not measured | Only Grok 4.7 measured |
| LMArena Text: writing and language | 1394 | Not measured | Only Grok 4.7 measured |
| LMArena Text: entertainment and media | 1376 | Not measured | Only Grok 4.7 measured |
| LMArena Vision: English | 1229 | Not measured | Only Grok 4.7 measured |
| LMArena Vision: Chinese | 1250 | Not measured | Only Grok 4.7 measured |
| LMArena Vision: reading text | 1241 | Not measured | Only Grok 4.7 measured |
| LMArena Vision: creative writing | 1217 | Not measured | Only Grok 4.7 measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Grok 4.7 | Qwen3 235B A22B Instruct 2507 | 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 4.7$0.0050Fits in one request
Qwen3 235B A22B Instruct 2507$0.0005Fits in one request
Qwen3 235B A22B Instruct 2507 costs less
Repository review
50K input + 3K output tokens
Grok 4.7$0.118Fits in one request
Qwen3 235B A22B Instruct 2507$0.0096Fits in one request
Qwen3 235B A22B Instruct 2507 costs less
Agent loop
200K input + 10K output tokens
Grok 4.7$0.460Fits in one request
Qwen3 235B A22B Instruct 2507$0.037Fits in one request
Qwen3 235B A22B Instruct 2507 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 235B A22B Instruct 2507 |
|---|---|---|
| Maker | xAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | September 21, 2026 | July 21, 2025 |
| Context window | 500K | 262K |
| Input $/Mtok | $2.00 | $0.145 |
| Output $/Mtok | $6.00 | $0.775 |
| Coding index | 66.7 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Grok 4.7 better than Qwen3 235B A22B Instruct 2507 for coding?
Only Grok 4.7 has a coding score, 66.7 on the Vibe Coding Index; Qwen3 235B A22B Instruct 2507 has none, so the two cannot be ranked on coding. Pick Qwen3 235B A22B Instruct 2507 for output tokens 7.7x cheaper ($0.775 vs $6.00 per million).
Which is cheaper, Grok 4.7 or Qwen3 235B A22B Instruct 2507?
Grok 4.7 costs $2.00 per million input tokens and $6.00 per million output tokens; Qwen3 235B A22B Instruct 2507 costs $0.145 and $0.775. Cost per solved task is known for neither of them.
Which has the bigger context window, Grok 4.7 or Qwen3 235B A22B Instruct 2507?
Grok 4.7, with 500K tokens against 262K.
How many benchmarks is the Grok 4.7 vs Qwen3 235B A22B Instruct 2507 comparison based on?
14 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 235B A22B Instruct 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.