GPT-6 Astra vs Qwen3 Coder Next
GPT-6 Astra leads Qwen3 Coder Next on the Artificial Analysis Intelligence Index, 52.7 to 9.2, and Qwen3 Coder Next costs 62.5x less per output token ($0.80 vs $50.00 per million). Updated October 21, 2026; 8 benchmarks have a result for both.
vs boards won of 8 shared
GPT-6 Astra or Qwen3 Coder Next: which to pick
Only GPT-6 Astra has a coding score, 85.1 on the Vibe Coding Index; Qwen3 Coder Next has none, so the two cannot be ranked on coding.
Pick Qwen3 Coder Next for output tokens 62.5x cheaper ($0.80 vs $50.00 per million).
Model AGPT-6 AstraOpenAI85.1/1005 independent benchmarksNo cost per solved taskModel BQwen3 Coder NextQwenNot benchmarkedNo coding benchmarkNo cost per solved task
- Shared results
- 8
- GPT-6 Astra only
- 113
- Qwen3 Coder Next only
- 3
- 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 GPT-6 Astra has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-6 Astra
GPT-6 Astra leads, 52.7 against 9.2.
Same board, both measured
Agentic work
AA Agentic Index
GPT-6 Astra
GPT-6 Astra leads, 51.0 against 0.9.
Same board, both measured
Web design
Design Arena: websites
No call
Only GPT-6 Astra has a Design Arena: websites result, 1337.
Directional only
General
Vals Index
No call
Only GPT-6 Astra has a Vals Index result, 65.0%.
Directional only
Long documents
Listed context window
GPT-6 Astra
GPT-6 Astra takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 Coder Next
GPT-6 Astra $0.035, Qwen3 Coder Next $0.0005 per turn.
List prices
At a glance
- Coding index
- GPT-6 Astra 85.1 from 5 benchmarks, Qwen3 Coder Next not benchmarked.
- Widest category
- Agentic work, 50.1 points apart on average over 1 shared benchmark.
- Widest single gap
- WeirdML: GPT-6 Astra 93.3% against Qwen3 Coder Next 34.4%, 58.9 points apart on a 0 to 100 scale.
- Output price
- GPT-6 Astra $50.00 against Qwen3 Coder Next $0.80 per million output tokens, 62.5x apart.
- Context window
- GPT-6 Astra takes 1.05M tokens, Qwen3 Coder Next 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 | GPT-6 Astra | Bars | Qwen3 Coder Next | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 8 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
| Benchmark | GPT-6 Astra | Qwen3 Coder Next | Leader |
|---|---|---|---|
| LiveBench coding | 93.7% | Not measured | Only GPT-6 Astra measured |
| LMArena WebDev | 1774 | Not measured | Only GPT-6 Astra measured |
| AA Coding Index | 76.9 | 36.2 | GPT-6 Astra |
| Terminal-Bench 4 (Vals AI) | 59.6% | Not measured | Only GPT-6 Astra measured |
| Vibe Code Bench (Vals AI) | 89.6% | Not measured | Only GPT-6 Astra measured |
| Code migration (Vals AI) | 67.7% | Not measured | Only GPT-6 Astra measured |
| ProgramBench (Vals AI) | 5.5% | Not measured | Only GPT-6 Astra measured |
| IOI (Vals AI) | 100.0% | Not measured | Only GPT-6 Astra measured |
| Terminal-Bench 2.1 (Vals AI) | 87.3% | Not measured | Only GPT-6 Astra measured |
| SWE-bench Multimodal (Vals AI) | 43.3% | Not measured | Only GPT-6 Astra measured |
| Vibe Code Bench 1-100 (Vals AI) | 27.6% | Not measured | Only GPT-6 Astra measured |
| CyberBench (Vals AI) | 41.1% | Not measured | Only GPT-6 Astra measured |
| SciCode | 56.5% | 36.2% | GPT-6 Astra |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 18.2% | Only Qwen3 Coder Next measured |
| FrontierCode | 53.3% | Not measured | Only GPT-6 Astra measured |
| FrontierSWE | 65.5% | Not measured | Only GPT-6 Astra measured |
| GSO-Bench | 79.4% | Not measured | Only GPT-6 Astra measured |
| WeirdML | 93.3% | 34.4% | GPT-6 Astra |
| 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 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: software and IT | 1474 | Not measured | Only GPT-6 Astra measured |
| LMArena WebDev: React | 1798 | Not measured | Only GPT-6 Astra measured |
| LMArena WebDev: HTML | 1775 | Not measured | Only GPT-6 Astra measured |
| LMArena WebDev: from an image | 1726 | Not measured | Only GPT-6 Astra measured |
| SciCode | 12.3% | Not measured | Only GPT-6 Astra measured |
| Neither model has a result on the other 13 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6 Astra | Qwen3 Coder Next | Leader |
|---|---|---|---|
| AA Intelligence Index | 52.7 | 9.2 | GPT-6 Astra |
| Epoch Capabilities Index | 168.8 | Not measured | Only GPT-6 Astra measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6 Astra | Qwen3 Coder Next | Leader |
|---|---|---|---|
| AA Agentic Index | 51.0 | 0.9 | GPT-6 Astra |
| Design Arena: agents building web apps | 1373 | 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 | 1315 | 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 | 1243 | Not measured | Only GPT-6 Astra measured |
| Design Arena: spreadsheets | 1361 | Not measured | Only GPT-6 Astra measured |
| LiveBench research | 85.2% | Not measured | Only GPT-6 Astra measured |
| LiveBench browser | 84.0% | Not measured | Only GPT-6 Astra measured |
| LiveBench long agentic | 82.4% | Not measured | Only GPT-6 Astra measured |
| SREBench (Vals AI) | 56.9% | Not measured | Only GPT-6 Astra measured |
| Finance Agent (Vals AI) | 53.5% | Not measured | Only GPT-6 Astra measured |
| Tax Agent Bench (Vals AI) | 20.7% | Not measured | Only GPT-6 Astra measured |
| Legal Research Bench (Vals AI) | 39.4% | Not measured | Only GPT-6 Astra measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 7.1% | Not measured | Only GPT-6 Astra measured |
| Excel Modeling Benchmark (Vals AI) | 71.7% | Not measured | Only GPT-6 Astra measured |
| BioMysteryBench (Vals AI) | 79.3% | Not measured | Only GPT-6 Astra measured |
| Terminal-Bench-Science (Vals AI) | 62.9% | Not measured | Only GPT-6 Astra measured |
| Vals Science Index | 65.1% | Not measured | Only GPT-6 Astra measured |
| 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% | Not measured | Only GPT-6 Astra measured |
| τ²-Bench Telecom | Not measured | 79.5% | Only Qwen3 Coder Next measured |
| APEX-Agents | 64.7% | Not measured | Only GPT-6 Astra measured |
| 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 | Not measured | Only GPT-6 Astra measured |
| Neither model has a result on the other 13 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-6 Astra | Qwen3 Coder Next | Leader |
|---|---|---|---|
| LiveBench reasoning | 92.7% | Not measured | Only GPT-6 Astra measured |
| MysteryMechanism (Vals AI) | 53.1% | Not measured | Only GPT-6 Astra measured |
| GPQA Diamond (Artificial Analysis run) | 96.3% | 73.7% | GPT-6 Astra |
| Humanity's Last Exam (Artificial Analysis run) | 54.7% | 10.1% | GPT-6 Astra |
| GPQA Diamond (Epoch AI run) | 95.8% | Not measured | Only GPT-6 Astra measured |
| ARC-AGI | 98.5% | Not measured | Only GPT-6 Astra measured |
| ARC-AGI-2 | 95.0% | Not measured | Only GPT-6 Astra measured |
| Chess puzzles | 74.0% | Not measured | Only GPT-6 Astra measured |
| Mystery game puzzles | 84.0% | Not measured | Only GPT-6 Astra measured |
| EBR-bench | 76.2% | Not measured | Only GPT-6 Astra measured |
| LMArena Text: hard prompts | 1463 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: expert | 1489 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: hard prompts in English | 1464 | Not measured | Only GPT-6 Astra measured |
| LMArena Vision: diagrams | 1297 | Not measured | Only GPT-6 Astra measured |
| LMArena Vision: homework | 1337 | Not measured | Only GPT-6 Astra measured |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-6 Astra | Qwen3 Coder Next | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | Not measured | Only GPT-6 Astra measured |
| FrontierMath, tiers 1 to 3 | 93.7% | Not measured | Only GPT-6 Astra measured |
| FrontierMath, tier 4 | 97.6% | Not measured | Only GPT-6 Astra measured |
| ProofBench | 99.0% | Not measured | Only GPT-6 Astra measured |
| LMArena Text: math | 1465 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: mathematical work | 1484 | Not measured | Only GPT-6 Astra measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-6 Astra | Qwen3 Coder Next | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 48.5% | Not measured | Only GPT-6 Astra measured |
| SimpleQA Verified | 75.6% | Not measured | Only GPT-6 Astra measured |
| LMArena Text: science | 1451 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: medicine and healthcare | 1425 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: legal and government | 1462 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: business and finance | 1439 | Not measured | Only GPT-6 Astra measured |
| FACTS Benchmark Suite | 75.7% | Not measured | Only GPT-6 Astra measured |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-6 Astra | Qwen3 Coder Next | Leader |
|---|---|---|---|
| Design Arena: websites | 1337 | Not measured | Only GPT-6 Astra measured |
| Design Arena: UI components | 1396 | Not measured | Only GPT-6 Astra measured |
| Design Arena: game dev | 1475 | Not measured | Only GPT-6 Astra measured |
| Design Arena: data viz | 1334 | Not measured | Only GPT-6 Astra measured |
| Design Arena: 3D | 1500 | Not measured | Only GPT-6 Astra measured |
| Design Arena: all code categories | 1379 | Not measured | Only GPT-6 Astra measured |
| Design Arena: SVG | 1431 | Not measured | Only GPT-6 Astra measured |
| Design Arena: ASCII art | 1353 | Not measured | Only GPT-6 Astra measured |
| LiveBench design | 82.0% | Not measured | Only GPT-6 Astra measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6 Astra | Qwen3 Coder Next | Leader |
|---|---|---|---|
| Vals Index | 65.0% | Not measured | Only GPT-6 Astra measured |
| LiveBench data analysis | 83.0% | Not measured | Only GPT-6 Astra measured |
| SAGE (Vals AI) | 46.4% | Not measured | Only GPT-6 Astra measured |
| MedScribe (Vals AI) | 87.9% | Not measured | Only GPT-6 Astra measured |
| IFBench | Not measured | 35.2% | Only Qwen3 Coder Next measured |
| Long context reasoning (AA-LCR) | 80.7% | 47.0% | GPT-6 Astra |
| DTBench | 97.3% | Not measured | Only GPT-6 Astra measured |
| LMCA | 64.4% | Not measured | Only GPT-6 Astra measured |
| Furniture assembly | 80.0% | Not measured | Only GPT-6 Astra measured |
| LMArena Text | 1441 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: instruction following | 1455 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: creative writing | 1420 | Not measured | Only GPT-6 Astra measured |
| LMArena Vision | 1280 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: English | 1447 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: non-English | 1432 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: Chinese | 1489 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: German | 1459 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: Japanese | 1405 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: Korean | 1428 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: French | 1432 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: Spanish | 1422 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: Russian | 1438 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: Polish | 1422 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: multi-turn | 1447 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: longer queries | 1460 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: writing and language | 1437 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: entertainment and media | 1427 | Not measured | Only GPT-6 Astra measured |
| LMArena Vision: English | 1280 | Not measured | Only GPT-6 Astra measured |
| LMArena Vision: Chinese | 1361 | Not measured | Only GPT-6 Astra measured |
| LMArena Vision: reading text | 1292 | Not measured | Only GPT-6 Astra measured |
| LMArena Vision: creative writing | 1286 | Not measured | Only GPT-6 Astra measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6 Astra | Qwen3 Coder Next | 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-6 Astra$0.035Fits in one request
Qwen3 Coder Next$0.0005Fits in one request
Qwen3 Coder Next costs less
Repository review
50K input + 3K output tokens
GPT-6 Astra$0.650Fits in one request
Qwen3 Coder Next$0.0084Fits in one request
Qwen3 Coder Next costs less
Agent loop
200K input + 10K output tokens
GPT-6 Astra$2.50Fits in one request
Qwen3 Coder Next$0.032Fits in one request
Qwen3 Coder Next 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 | Qwen3 Coder Next |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | September 4, 2026 | February 4, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $10.00 | $0.12 |
| Output $/Mtok | $50.00 | $0.80 |
| Coding index | 85.1 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6 Astra better than Qwen3 Coder Next for coding?
Only GPT-6 Astra has a coding score, 85.1 on the Vibe Coding Index; Qwen3 Coder Next has none, so the two cannot be ranked on coding. Pick Qwen3 Coder Next for output tokens 62.5x cheaper ($0.80 vs $50.00 per million).
Which is cheaper, GPT-6 Astra or Qwen3 Coder Next?
GPT-6 Astra costs $10.00 per million input tokens and $50.00 per million output tokens; Qwen3 Coder Next costs $0.12 and $0.80. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-6 Astra or Qwen3 Coder Next?
GPT-6 Astra, with 1.05M tokens against 262K.
How many benchmarks is the GPT-6 Astra vs Qwen3 Coder Next comparison based on?
8 benchmarks have a result for both models as of October 21, 2026. GPT-6 Astra's coding index rests on 5 independent benchmarks and Qwen3 Coder Next's on 0. Where only one model has a result, the page says so instead of naming a winner.