GPT-6 Astra vs Qwen3.8 Max (0902)

GPT-6 Astra leads Qwen3.8 Max (0902) on coding, 85.1 to 62.4 on the Vibe Coding Index, and Qwen3.8 Max (0902) costs 8.3x less per output token ($6.00 vs $50.00 per million). Updated October 22, 2026; 99 benchmarks have a result for both.

Replace GPT-6 Astra Replace Qwen3.8 Max (0902)

GPT-6 AstraOpenAI

Coding: 85.1
Overall: 83.0
Output $/M: $50.00

Qwen3.8 Max (0902)Qwen

Coding: 62.4
Overall: 68.9
Output $/M: $6.00

vs boards won of 99 shared, 1 tied

GPT-6 Astra or Qwen3.8 Max (0902): which to pick

Pick GPT-6 Astra for coding: it scores 85.1 on the Vibe Coding Index against 62.4 for Qwen3.8 Max (0902).

Pick Qwen3.8 Max (0902) for output tokens 8.3x cheaper ($6.00 vs $50.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Model AGPT-6 AstraOpenAI85.1/1005 independent benchmarksNo cost per solved task Model BQwen3.8 Max (0902)Qwen62.4/1005 independent benchmarks$1.32 per solved task

993015

Shared results: 99
GPT-6 Astra only: 30
Qwen3.8 Max (0902) only: 15
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 62.4.
5 benchmarks behind each score
Intelligence
AA Intelligence Index
GPT-6 Astra
GPT-6 Astra leads, 52.7 against 45.4.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 56.0 against 51.0.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Qwen3.8 Max (0902) has a GPQA Diamond result, 93.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.8 Max (0902) has a MMLU Pro result, 88.6%.
Directional only
Web design
Design Arena: websites
GPT-6 Astra
GPT-6 Astra leads, 1336 against 1275.
Same board, both measured
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 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.8 Max (0902)
GPT-6 Astra $0.035, Qwen3.8 Max (0902) $0.0050 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.8 Max (0902) has the number, $1.32.
Directional only

At a glance

Coding index: GPT-6 Astra 85.1 from 5 benchmarks, Qwen3.8 Max (0902) 62.4 from 5 benchmarks.
Widest category: Math, 21.2 points apart on average over 7 shared benchmarks.
Widest single gap: Furniture assembly: GPT-6 Astra 80.0% against Qwen3.8 Max (0902) 20.0%, 60.0 points apart on a 0 to 100 scale.
Output price: GPT-6 Astra $50.00 against Qwen3.8 Max (0902) $6.00 per million output tokens, 8.3x apart.
Context window: GPT-6 Astra takes 1.05M tokens, Qwen3.8 Max (0902) 1M.

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.

Boards won, where both have a result
Category	GPT-6 Astra	Qwen3.8 Max (0902)	Ties
Coding	17	2
Intelligence	2	0
Agentic work	12	4
Reasoning	8	4
Math	4	2	1 tie
Knowledge	2	4
Web design	8	0
General	7	22
All shared boards	60	38	1 tie

CodingLike-for-likeSix of these boards feed the Vibe Coding Index172

Coding benchmarks for GPT-6 Astra and Qwen3.8 Max (0902)
Benchmark	GPT-6 Astra	Qwen3.8 Max (0902)	Leader
LiveBench coding	93.7%	60.3%	GPT-6 Astra
LMArena WebDev	1774	1674	GPT-6 Astra
AA Coding Index	76.9	76.2	GPT-6 Astra
LiveCodeBench (Vals AI)	Not measured	87.8%	Only Qwen3.8 Max (0902) measured
SWE-bench Verified (Vals AI)	Not measured	85.6%	Only Qwen3.8 Max (0902) measured
Terminal-Bench 4 (Vals AI)	59.6%	34.3%	GPT-6 Astra
Vibe Code Bench (Vals AI)	89.6%	64.7%	GPT-6 Astra
Code migration (Vals AI)	67.7%	24.0%	GPT-6 Astra
ProgramBench (Vals AI)	5.5%	0.0%	GPT-6 Astra
IOI (Vals AI)	100.0%	68.9%	GPT-6 Astra
Terminal-Bench 2.1 (Vals AI)	87.3%	67.4%	GPT-6 Astra
SWE-bench Multimodal (Vals AI)	43.3%	42.5%	GPT-6 Astra
Vibe Code Bench 1-100 (Vals AI)	27.6%	12.8%	GPT-6 Astra
SkillsBench (Vals AI)	Not measured	42.0%	Only Qwen3.8 Max (0902) measured
CyberBench (Vals AI)	41.1%	28.6%	GPT-6 Astra
SciCode	56.5%	53.2%	GPT-6 Astra
FrontierCode	53.3%	Not measured	Only GPT-6 Astra measured
FrontierSWE	65.5%	17.8%	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	1502	Qwen3.8 Max (0902)
LMArena Text: software and IT	1474	1498	Qwen3.8 Max (0902)
LMArena WebDev: React	1798	1692	GPT-6 Astra
LMArena WebDev: HTML	1775	1649	GPT-6 Astra
LMArena WebDev: from an image	1726	1637	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 11 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20

Intelligence benchmarks for GPT-6 Astra and Qwen3.8 Max (0902)
Benchmark	GPT-6 Astra	Qwen3.8 Max (0902)	Leader
AA Intelligence Index	52.7	45.4	GPT-6 Astra
Epoch Capabilities Index	168.8	157.4	GPT-6 Astra

Agentic workLike-for-likePublic boards, shown as published, kept out of the index124

Agentic work benchmarks for GPT-6 Astra and Qwen3.8 Max (0902)
Benchmark	GPT-6 Astra	Qwen3.8 Max (0902)	Leader
AA Agentic Index	51.0	56.0	Qwen3.8 Max (0902)
Design Arena: agents building web apps	1374	1300	GPT-6 Astra
Design Arena: agents building full-stack apps	1357	1305	GPT-6 Astra
Design Arena: agents building mobile apps	1312	1224	GPT-6 Astra
Design Arena: agents building Android apps	Not measured	1190	Only Qwen3.8 Max (0902) measured
Design Arena: agents building Godot games	1348	1234	GPT-6 Astra
Design Arena: PowerPoint slides	1217	1232	Qwen3.8 Max (0902)
Design Arena: spreadsheets	1378	993	GPT-6 Astra
LiveBench research	85.2%	69.9%	GPT-6 Astra
LiveBench browser	84.0%	32.0%	GPT-6 Astra
LiveBench long agentic	82.4%	42.3%	GPT-6 Astra
SREBench (Vals AI)	56.9%	Not measured	Only GPT-6 Astra measured
Finance Agent (Vals AI)	53.5%	50.6%	GPT-6 Astra
Tax Agent Bench (Vals AI)	20.7%	32.1%	Qwen3.8 Max (0902)
Legal Research Bench (Vals AI)	39.4%	47.6%	Qwen3.8 Max (0902)
Harvey's Legal Agent Benchmark (Vals AI)	7.1%	Not measured	Only GPT-6 Astra measured
Excel Modeling Benchmark (Vals AI)	71.7%	60.1%	GPT-6 Astra
BioMysteryBench (Vals AI)	79.3%	Not measured	Only GPT-6 Astra measured
Terminal-Bench-Science (Vals AI)	62.9%	12.9%	GPT-6 Astra
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
APEX-Agents	64.7%	63.3%	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	Not measured	Only GPT-6 Astra measured
LMArena Search	Not measured	1261	Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 13 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index84

Reasoning benchmarks for GPT-6 Astra and Qwen3.8 Max (0902)
Benchmark	GPT-6 Astra	Qwen3.8 Max (0902)	Leader
GPQA Diamond	Not measured	93.7%	Only Qwen3.8 Max (0902) measured
LiveBench reasoning	92.7%	88.2%	GPT-6 Astra
MysteryMechanism (Vals AI)	53.1%	23.9%	GPT-6 Astra
MMMU Pro (Vals AI)	Not measured	88.0%	Only Qwen3.8 Max (0902) measured
GPQA Diamond (Artificial Analysis run)	96.3%	92.8%	GPT-6 Astra
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%	Not measured	Only GPT-6 Astra measured
ARC-AGI-2	95.0%	Not measured	Only GPT-6 Astra measured
Chess puzzles	74.0%	46.0%	GPT-6 Astra
Mystery game puzzles	84.0%	38.0%	GPT-6 Astra
EBR-bench	76.2%	Not measured	Only GPT-6 Astra measured
LMArena Text: hard prompts	1463	1496	Qwen3.8 Max (0902)
LMArena Text: expert	1489	1507	Qwen3.8 Max (0902)
LMArena Text: hard prompts in English	1464	1503	Qwen3.8 Max (0902)
LMArena Vision: diagrams	1297	1323	Qwen3.8 Max (0902)
LMArena Vision: homework	1337	1336	GPT-6 Astra
Humanity's Last Exam (Scale run)	60.6%	Not measured	Only GPT-6 Astra measured
Neither model has a result on the other 5 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index42

Math benchmarks for GPT-6 Astra and Qwen3.8 Max (0902)
Benchmark	GPT-6 Astra	Qwen3.8 Max (0902)	Leader
OTIS Mock AIME	100.0%	100.0%	Tie
FrontierMath, tiers 1 to 3	93.7%	74.7%	GPT-6 Astra
FrontierMath, tier 4	97.6%	46.3%	GPT-6 Astra
ProofBench	99.0%	58.0%	GPT-6 Astra
LMArena Text: math	1465	1501	Qwen3.8 Max (0902)
LMArena Text: mathematical work	1484	1491	Qwen3.8 Max (0902)
MathArena	81.9%	51.6%	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 index24

Knowledge benchmarks for GPT-6 Astra and Qwen3.8 Max (0902)
Benchmark	GPT-6 Astra	Qwen3.8 Max (0902)	Leader
MMLU Pro	Not measured	88.6%	Only Qwen3.8 Max (0902) measured
LegalBench (Vals AI)	Not measured	83.6%	Only Qwen3.8 Max (0902) measured
CorpFin (Vals AI)	Not measured	65.8%	Only Qwen3.8 Max (0902) measured
TaxEval (Vals AI)	Not measured	75.5%	Only Qwen3.8 Max (0902) measured
MortgageTax (Vals AI)	Not measured	64.0%	Only Qwen3.8 Max (0902) measured
MedCode (Vals AI)	48.5%	40.7%	GPT-6 Astra
SimpleQA Verified	75.6%	47.3%	GPT-6 Astra
LMArena Text: science	1451	1512	Qwen3.8 Max (0902)
LMArena Text: medicine and healthcare	1425	1503	Qwen3.8 Max (0902)
LMArena Text: legal and government	1462	1492	Qwen3.8 Max (0902)
LMArena Text: business and finance	1439	1480	Qwen3.8 Max (0902)
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%	Not measured	Only GPT-6 Astra measured
Neither model has a result on the other 6 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index80

Web design benchmarks for GPT-6 Astra and Qwen3.8 Max (0902)
Benchmark	GPT-6 Astra	Qwen3.8 Max (0902)	Leader
Design Arena: websites	1336	1275	GPT-6 Astra
Design Arena: UI components	1394	1336	GPT-6 Astra
Design Arena: game dev	1480	1312	GPT-6 Astra
Design Arena: data viz	1334	1282	GPT-6 Astra
Design Arena: 3D	1500	1336	GPT-6 Astra
Design Arena: all code categories	1379	1292	GPT-6 Astra
Design Arena: SVG	1430	Not measured	Only GPT-6 Astra measured
Design Arena: ASCII art	1353	1200	GPT-6 Astra
LiveBench design	82.0%	78.6%	GPT-6 Astra

GeneralLike-for-likePublic boards, shown as published, kept out of the index722

General benchmarks for GPT-6 Astra and Qwen3.8 Max (0902)
Benchmark	GPT-6 Astra	Qwen3.8 Max (0902)	Leader
Vals Index	65.0%	Not measured	Only GPT-6 Astra measured
LiveBench data analysis	83.0%	78.4%	GPT-6 Astra
Public Benefits Bench (Vals AI)	Not measured	67.1%	Only Qwen3.8 Max (0902) measured
SAGE (Vals AI)	46.4%	51.2%	Qwen3.8 Max (0902)
MedScribe (Vals AI)	87.9%	85.0%	GPT-6 Astra
Vals Multimodal Index	Not measured	65.4%	Only Qwen3.8 Max (0902) measured
Long context reasoning (AA-LCR)	80.7%	80.3%	GPT-6 Astra
DTBench	97.3%	92.0%	GPT-6 Astra
LMCA	64.4%	46.2%	GPT-6 Astra
Furniture assembly	80.0%	20.0%	GPT-6 Astra
LMArena Text	1441	1483	Qwen3.8 Max (0902)
LMArena Text: instruction following	1455	1481	Qwen3.8 Max (0902)
LMArena Text: creative writing	1420	1477	Qwen3.8 Max (0902)
LMArena Vision	1280	1313	Qwen3.8 Max (0902)
LMArena Text: English	1447	1491	Qwen3.8 Max (0902)
LMArena Text: non-English	1432	1473	Qwen3.8 Max (0902)
LMArena Text: Chinese	1489	1539	Qwen3.8 Max (0902)
LMArena Text: German	1459	1478	Qwen3.8 Max (0902)
LMArena Text: Japanese	1405	1473	Qwen3.8 Max (0902)
LMArena Text: Korean	1428	1460	Qwen3.8 Max (0902)
LMArena Text: French	1432	1498	Qwen3.8 Max (0902)
LMArena Text: Spanish	1422	1489	Qwen3.8 Max (0902)
LMArena Text: Russian	1438	1482	Qwen3.8 Max (0902)
LMArena Text: Polish	1422	1471	Qwen3.8 Max (0902)
LMArena Text: multi-turn	1447	1489	Qwen3.8 Max (0902)
LMArena Text: longer queries	1460	1488	Qwen3.8 Max (0902)
LMArena Text: writing and language	1437	1477	Qwen3.8 Max (0902)
LMArena Text: entertainment and media	1427	1464	Qwen3.8 Max (0902)
LMArena Vision: English	1280	1311	Qwen3.8 Max (0902)
LMArena Vision: Chinese	1361	1358	GPT-6 Astra
LMArena Vision: reading text	1292	1322	Qwen3.8 Max (0902)
LMArena Vision: humor	Not measured	1304	Only Qwen3.8 Max (0902) measured
LMArena Vision: creative writing	1286	1312	Qwen3.8 Max (0902)
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

Image generation benchmarks for GPT-6 Astra and Qwen3.8 Max (0902)
Benchmark	GPT-6 Astra	Qwen3.8 Max (0902)	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

Qwen3.8 Max (0902)$0.0050Fits in one request

Qwen3.8 Max (0902) costs less

Repository review

50K input + 3K output tokens

GPT-6 Astra$0.650Fits in one request

Qwen3.8 Max (0902)$0.118Fits in one request

Qwen3.8 Max (0902) costs less

Agent loop

200K input + 10K output tokens

GPT-6 Astra$2.50Fits in one request

Qwen3.8 Max (0902)$0.460Fits in one request

Qwen3.8 Max (0902) 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.

Specifications of GPT-6 Astra and Qwen3.8 Max (0902)
Specification	OpenAI GPT-6 Astra	Qwen3.8 Max (0902)
Maker	OpenAI	Qwen
Weights	No public weights listed	No public weights listed
Released	September 4, 2026	September 3, 2026
Context window	1.05M	1M
Input $/Mtok	$10.00	$2.00
Output $/Mtok	$50.00	$6.00
Coding index	85.1	62.4
Independent measurements behind it	5	5
Cost per solved task	Not computable	$1.32
Source	OpenRouter listing	OpenRouter listing

Questions

Is GPT-6 Astra better than Qwen3.8 Max (0902) for coding?

Pick GPT-6 Astra for coding: it scores 85.1 on the Vibe Coding Index against 62.4 for Qwen3.8 Max (0902). Pick Qwen3.8 Max (0902) for output tokens 8.3x cheaper ($6.00 vs $50.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, GPT-6 Astra or Qwen3.8 Max (0902)?

GPT-6 Astra costs $10.00 per million input tokens and $50.00 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Cost per solved task is known for Qwen3.8 Max (0902) only.

Which has the bigger context window, GPT-6 Astra or Qwen3.8 Max (0902)?

GPT-6 Astra, with 1.05M tokens against 1M.

How many benchmarks is the GPT-6 Astra vs Qwen3.8 Max (0902) comparison based on?

99 benchmarks have a result for both models as of October 22, 2026. GPT-6 Astra's coding index rests on 5 independent benchmarks and Qwen3.8 Max (0902)'s on 5. Where only one model has a result, the page says so instead of naming a winner.

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GPT-6 Astra or Qwen3.8 Max (0902): which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Knowledge

Web design

General

Long documents

Everyday cost

Cost per solved task

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

Compare next