GPT-6 Astra vs Grok 4.7
GPT-6 Astra leads Grok 4.7 on coding, 85.1 to 66.7 on the Vibe Coding Index, and Grok 4.7 costs 8.3x less per output token ($6.00 vs $50.00 per million). Updated October 22, 2026; 100 benchmarks have a result for both.
GPT-6 Astra or Grok 4.7: which to pick
Pick GPT-6 Astra for coding: it scores 85.1 on the Vibe Coding Index against 66.7 for Grok 4.7.
Pick Grok 4.7 for output tokens 8.3x cheaper ($6.00 vs $50.00 per million) and work measured by CyberBench (Vals AI) or SciCode, where it leads.
- Shared results
- 100
- GPT-6 Astra only
- 29
- Grok 4.7 only
- 2
- 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
GPT-6 Astra
GPT-6 Astra scores 85.1 against 66.7.
5 benchmarks behind each score
Intelligence
AA Intelligence Index
GPT-6 Astra
GPT-6 Astra leads, 52.7 against 46.4.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-6 Astra has a AA Agentic Index result, 51.0.
Directional only
Web design
Design Arena: websites
GPT-6 Astra
GPT-6 Astra leads, 1336 against 1254.
Same board, both measured
General
Vals Index
GPT-6 Astra
GPT-6 Astra leads, 65.0% against 58.6%.
Same board, both measured
Long documents
Listed context window
GPT-6 Astra
GPT-6 Astra takes 1.05M tokens against 500K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Grok 4.7
GPT-6 Astra $0.035, Grok 4.7 $0.0050 per turn.
List prices
At a glance
- Coding index
- GPT-6 Astra 85.1 from 5 benchmarks, Grok 4.7 66.7 from 5 benchmarks.
- Widest category
- Math, 36.3 points apart on average over 7 shared benchmarks.
- Widest single gap
- FrontierMath, tier 4: GPT-6 Astra 97.6% against Grok 4.7 17.1%, 80.5 points apart on a 0 to 100 scale.
- Output price
- GPT-6 Astra $50.00 against Grok 4.7 $6.00 per million output tokens, 8.3x apart.
- Context window
- GPT-6 Astra takes 1.05M tokens, Grok 4.7 500K.
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-6 Astra | Bars | Grok 4.7 | Ties |
|---|---|---|---|---|
| Coding | 16 | 2 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 11 | 4 | ||
| Reasoning | 14 | 0 | ||
| Math | 7 | 0 | ||
| Knowledge | 6 | 1 | ||
| Web design | 7 | 0 | ||
| General | 29 | 1 | ||
| All shared boards | 92 | 8 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index162
| Benchmark | GPT-6 Astra | Grok 4.7 | Leader |
|---|---|---|---|
| LiveBench coding | 93.7% | 84.5% | GPT-6 Astra |
| LMArena WebDev | 1774 | 1637 | GPT-6 Astra |
| AA Coding Index | 76.9 | Not measured | Only GPT-6 Astra measured |
| Terminal-Bench 4 (Vals AI) | 59.6% | 28.8% | GPT-6 Astra |
| Vibe Code Bench (Vals AI) | 89.6% | 86.2% | GPT-6 Astra |
| Code migration (Vals AI) | 67.7% | 44.8% | GPT-6 Astra |
| ProgramBench (Vals AI) | 5.5% | 0.5% | GPT-6 Astra |
| IOI (Vals AI) | 100.0% | 57.7% | GPT-6 Astra |
| Terminal-Bench 2.1 (Vals AI) | 87.3% | 73.4% | GPT-6 Astra |
| SWE-bench Multimodal (Vals AI) | 43.3% | 42.9% | GPT-6 Astra |
| Vibe Code Bench 1-100 (Vals AI) | 27.6% | Not measured | Only GPT-6 Astra measured |
| CyberBench (Vals AI) | 41.1% | 69.5% | Grok 4.7 |
| SciCode | 56.5% | 57.8% | Grok 4.7 |
| FrontierCode | 53.3% | 47.6% | GPT-6 Astra |
| FrontierSWE | 65.5% | 29.5% | GPT-6 Astra |
| GSO-Bench | 79.4% | Not measured | Only GPT-6 Astra measured |
| WeirdML | 93.3% | Not measured | Only GPT-6 Astra measured |
| MirrorCode | 46.7% | Not measured | Only GPT-6 Astra measured |
| ALE-Bench | 2951.3 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: coding | 1489 | 1432 | GPT-6 Astra |
| LMArena Text: software and IT | 1474 | 1421 | GPT-6 Astra |
| LMArena WebDev: React | 1798 | 1663 | GPT-6 Astra |
| LMArena WebDev: HTML | 1775 | 1627 | GPT-6 Astra |
| LMArena WebDev: from an image | 1726 | 1586 | GPT-6 Astra |
| SciCode | 12.3% | Not measured | Only GPT-6 Astra measured |
| SWE-Bench Pro V2 | 96.9% | Not measured | Only GPT-6 Astra measured |
| SWE Atlas: Codebase QnA | 59.1% | Not measured | Only GPT-6 Astra measured |
| SWE Atlas: Refactoring | 59.1% | Not measured | Only GPT-6 Astra measured |
| SWE Atlas: Test Writing | 50.7% | Not measured | Only GPT-6 Astra measured |
| Neither model has a result on the other 14 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-6 Astra | Grok 4.7 | Leader |
|---|---|---|---|
| AA Intelligence Index | 52.7 | 46.4 | GPT-6 Astra |
| Epoch Capabilities Index | 168.8 | 154.4 | GPT-6 Astra |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index114
| Benchmark | GPT-6 Astra | Grok 4.7 | Leader |
|---|---|---|---|
| AA Agentic Index | 51.0 | Not measured | Only GPT-6 Astra measured |
| Design Arena: agents building web apps | 1374 | Not measured | Only GPT-6 Astra measured |
| Design Arena: agents building full-stack apps | 1357 | Not measured | Only GPT-6 Astra measured |
| Design Arena: agents building mobile apps | 1312 | Not measured | Only GPT-6 Astra measured |
| Design Arena: agents building Godot games | 1348 | Not measured | Only GPT-6 Astra measured |
| Design Arena: PowerPoint slides | 1217 | Not measured | Only GPT-6 Astra measured |
| Design Arena: spreadsheets | 1378 | Not measured | Only GPT-6 Astra measured |
| LiveBench research | 85.2% | 86.4% | Grok 4.7 |
| LiveBench browser | 84.0% | 60.0% | GPT-6 Astra |
| LiveBench long agentic | 82.4% | 50.1% | GPT-6 Astra |
| SREBench (Vals AI) | 56.9% | 3.8% | GPT-6 Astra |
| Finance Agent (Vals AI) | 53.5% | 52.3% | GPT-6 Astra |
| Tax Agent Bench (Vals AI) | 20.7% | 34.2% | Grok 4.7 |
| Legal Research Bench (Vals AI) | 39.4% | 47.1% | Grok 4.7 |
| Harvey's Legal Agent Benchmark (Vals AI) | 7.1% | 18.3% | Grok 4.7 |
| Excel Modeling Benchmark (Vals AI) | 71.7% | 67.0% | GPT-6 Astra |
| BioMysteryBench (Vals AI) | 79.3% | 69.3% | GPT-6 Astra |
| Terminal-Bench-Science (Vals AI) | 62.9% | 10.0% | GPT-6 Astra |
| Vals Science Index | 65.1% | 34.8% | GPT-6 Astra |
| Time Horizon Index (Vals AI) | 90.5% | Not measured | Only GPT-6 Astra measured |
| CUA-bench (Vals AI) | 19.2% | Not measured | Only GPT-6 Astra measured |
| Robo-bench (Vals AI) | 23.3% | 0.2% | GPT-6 Astra |
| APEX-Agents | 64.7% | 54.6% | GPT-6 Astra |
| Remote Labor Index | 20.8% | Not measured | Only GPT-6 Astra measured |
| BALROG | 68.3% | Not measured | Only GPT-6 Astra measured |
| SpireClimb | 25.7% | Not measured | Only GPT-6 Astra measured |
| Vending-Bench 2 | $15,515 | $10,537 | GPT-6 Astra |
| Neither model has a result on the other 15 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index140
| Benchmark | GPT-6 Astra | Grok 4.7 | Leader |
|---|---|---|---|
| LiveBench reasoning | 92.7% | 82.7% | GPT-6 Astra |
| MysteryMechanism (Vals AI) | 53.1% | 25.2% | GPT-6 Astra |
| GPQA Diamond (Artificial Analysis run) | 96.3% | Not measured | Only GPT-6 Astra measured |
| Humanity's Last Exam (Artificial Analysis run) | 54.7% | 43.1% | GPT-6 Astra |
| GPQA Diamond (Epoch AI run) | 95.8% | 92.7% | GPT-6 Astra |
| ARC-AGI | 98.5% | 90.2% | GPT-6 Astra |
| ARC-AGI-2 | 95.0% | 61.4% | GPT-6 Astra |
| Chess puzzles | 74.0% | 41.0% | GPT-6 Astra |
| Mystery game puzzles | 84.0% | 29.0% | GPT-6 Astra |
| EBR-bench | 76.2% | Not measured | Only GPT-6 Astra measured |
| LMArena Text: hard prompts | 1463 | 1415 | GPT-6 Astra |
| LMArena Text: expert | 1489 | 1439 | GPT-6 Astra |
| LMArena Text: hard prompts in English | 1464 | 1427 | GPT-6 Astra |
| LMArena Vision: diagrams | 1297 | 1254 | GPT-6 Astra |
| LMArena Vision: homework | 1337 | 1309 | GPT-6 Astra |
| Humanity's Last Exam (Scale run) | 60.6% | 23.4% | GPT-6 Astra |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | GPT-6 Astra | Grok 4.7 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | 98.1% | GPT-6 Astra |
| FrontierMath, tiers 1 to 3 | 93.7% | 53.0% | GPT-6 Astra |
| FrontierMath, tier 4 | 97.6% | 17.1% | GPT-6 Astra |
| ProofBench | 99.0% | 26.0% | GPT-6 Astra |
| LMArena Text: math | 1465 | 1414 | GPT-6 Astra |
| LMArena Text: mathematical work | 1484 | 1435 | GPT-6 Astra |
| MathArena | 81.9% | 41.1% | GPT-6 Astra |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index61
| Benchmark | GPT-6 Astra | Grok 4.7 | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | Not measured | 84.4% | Only Grok 4.7 measured |
| MedCode (Vals AI) | 48.5% | 49.5% | Grok 4.7 |
| SimpleQA Verified | 75.6% | 56.0% | GPT-6 Astra |
| LMArena Text: science | 1451 | 1419 | GPT-6 Astra |
| LMArena Text: medicine and healthcare | 1425 | 1395 | GPT-6 Astra |
| LMArena Text: legal and government | 1462 | 1423 | GPT-6 Astra |
| LMArena Text: business and finance | 1439 | 1389 | GPT-6 Astra |
| FACTS Benchmark Suite | 75.7% | Not measured | Only GPT-6 Astra measured |
| PRBench Finance | 47.5% | Not measured | Only GPT-6 Astra measured |
| PRBench Legal | 48.4% | 47.6% | GPT-6 Astra |
| Neither model has a result on the other 10 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | GPT-6 Astra | Grok 4.7 | Leader |
|---|---|---|---|
| Design Arena: websites | 1336 | 1254 | GPT-6 Astra |
| Design Arena: UI components | 1394 | 1276 | GPT-6 Astra |
| Design Arena: game dev | 1480 | 1314 | GPT-6 Astra |
| Design Arena: data viz | 1334 | 1238 | GPT-6 Astra |
| Design Arena: 3D | 1500 | 1274 | GPT-6 Astra |
| Design Arena: all code categories | 1379 | 1272 | GPT-6 Astra |
| Design Arena: SVG | 1430 | Not measured | Only GPT-6 Astra measured |
| Design Arena: ASCII art | 1353 | Not measured | Only GPT-6 Astra measured |
| LiveBench design | 82.0% | 78.0% | GPT-6 Astra |
GeneralLike-for-likePublic boards, shown as published, kept out of the index291
| Benchmark | GPT-6 Astra | Grok 4.7 | Leader |
|---|---|---|---|
| Vals Index | 65.0% | 58.6% | GPT-6 Astra |
| LiveBench data analysis | 83.0% | 76.9% | GPT-6 Astra |
| Public Benefits Bench (Vals AI) | Not measured | 65.6% | Only Grok 4.7 measured |
| SAGE (Vals AI) | 46.4% | 40.8% | GPT-6 Astra |
| MedScribe (Vals AI) | 87.9% | 89.4% | Grok 4.7 |
| Long context reasoning (AA-LCR) | 80.7% | 80.0% | GPT-6 Astra |
| DTBench | 97.3% | 96.0% | GPT-6 Astra |
| LMCA | 64.4% | 49.4% | GPT-6 Astra |
| Furniture assembly | 80.0% | 20.8% | GPT-6 Astra |
| LMArena Text | 1441 | 1399 | GPT-6 Astra |
| LMArena Text: instruction following | 1455 | 1406 | GPT-6 Astra |
| LMArena Text: creative writing | 1420 | 1381 | GPT-6 Astra |
| LMArena Vision | 1280 | 1231 | GPT-6 Astra |
| LMArena Text: English | 1447 | 1411 | GPT-6 Astra |
| LMArena Text: non-English | 1432 | 1386 | GPT-6 Astra |
| LMArena Text: Chinese | 1489 | 1449 | GPT-6 Astra |
| LMArena Text: German | 1459 | 1366 | GPT-6 Astra |
| LMArena Text: Japanese | 1405 | 1359 | GPT-6 Astra |
| LMArena Text: Korean | 1428 | 1383 | GPT-6 Astra |
| LMArena Text: French | 1432 | 1431 | GPT-6 Astra |
| LMArena Text: Spanish | 1422 | 1406 | GPT-6 Astra |
| LMArena Text: Russian | 1438 | 1399 | GPT-6 Astra |
| LMArena Text: Polish | 1422 | 1420 | GPT-6 Astra |
| LMArena Text: multi-turn | 1447 | 1394 | GPT-6 Astra |
| LMArena Text: longer queries | 1460 | 1416 | GPT-6 Astra |
| LMArena Text: writing and language | 1437 | 1394 | GPT-6 Astra |
| LMArena Text: entertainment and media | 1427 | 1376 | GPT-6 Astra |
| LMArena Vision: English | 1280 | 1229 | GPT-6 Astra |
| LMArena Vision: Chinese | 1361 | 1250 | GPT-6 Astra |
| LMArena Vision: reading text | 1292 | 1241 | GPT-6 Astra |
| LMArena Vision: creative writing | 1286 | 1217 | GPT-6 Astra |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6 Astra | Grok 4.7 | 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 costs less
Repository review
50K input + 3K output tokens
Grok 4.7 costs less
Agent loop
200K input + 10K output tokens
Grok 4.7 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-6 Astra | SpaceXAI Grok 4.7 |
|---|---|---|
| Maker | OpenAI | xAI |
| Weights | No public weights listed | No public weights listed |
| Released | September 4, 2026 | September 21, 2026 |
| Context window | 1.05M | 500K |
| Input $/Mtok | $10.00 | $2.00 |
| Output $/Mtok | $50.00 | $6.00 |
| Coding index | 85.1 | 66.7 |
| Independent measurements behind it | 5 | 5 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6 Astra better than Grok 4.7 for coding?
Pick GPT-6 Astra for coding: it scores 85.1 on the Vibe Coding Index against 66.7 for Grok 4.7. Pick Grok 4.7 for output tokens 8.3x cheaper ($6.00 vs $50.00 per million) and work measured by CyberBench (Vals AI) or SciCode, where it leads.
Which is cheaper, GPT-6 Astra or Grok 4.7?
GPT-6 Astra costs $10.00 per million input tokens and $50.00 per million output tokens; Grok 4.7 costs $2.00 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-6 Astra or Grok 4.7?
GPT-6 Astra, with 1.05M tokens against 500K.
How many benchmarks is the GPT-6 Astra vs Grok 4.7 comparison based on?
100 benchmarks have a result for both models as of October 22, 2026. GPT-6 Astra's coding index rests on 5 independent benchmarks and Grok 4.7's on 5. Where only one model has a result, the page says so instead of naming a winner.