GPT-5 Mini vs Qwen3.8 Max (0902)

Qwen3.8 Max (0902) leads GPT-5 Mini on coding, 62.4 to 34.2 on the Vibe Coding Index, and GPT-5 Mini costs 3.0x less per output token ($2.00 vs $6.00 per million). Updated October 22, 2026; 72 benchmarks have a result for both.

Replace GPT-5 Mini Replace Qwen3.8 Max (0902)

GPT-5 MiniOpenAI

Coding: 34.2
Overall: 43.7
Output $/M: $2.00

Qwen3.8 Max (0902)Qwen

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

vs boards won of 72 shared

GPT-5 Mini or Qwen3.8 Max (0902): which to pick

Pick Qwen3.8 Max (0902) for coding: it scores 62.4 on the Vibe Coding Index against 34.2 for GPT-5 Mini.

Pick GPT-5 Mini for output tokens 3.0x cheaper ($2.00 vs $6.00 per million) and a lower cost per solved task ($0.08 against $1.32).

Model AGPT-5 MiniOpenAI34.2/1002 independent benchmarks$0.08 per solved task Model BQwen3.8 Max (0902)Qwen62.4/1005 independent benchmarks$1.32 per solved task

722941

Shared results: 72
GPT-5 Mini only: 29
Qwen3.8 Max (0902) only: 41
Like-for-like categories: 7 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
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) scores 62.4 against 34.2.
2 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 45.4 against 20.6.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3.8 Max (0902) has a AA Agentic Index result, 56.0.
Directional only
Reasoning
GPQA Diamond
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 93.7% against 80.3%.
Same board, both measured
Math
AIME
No call
Only GPT-5 Mini has a AIME result, 91.5%.
Directional only
Knowledge
MMLU Pro
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 88.6% against 82.2%.
Same board, both measured
Web design
Design Arena: websites
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 1275 against 1125.
Same board, both measured
Long documents
Listed context window
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) takes 1M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5 Mini
GPT-5 Mini $0.0013, Qwen3.8 Max (0902) $0.0050 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5 Mini
GPT-5 Mini $0.08, Qwen3.8 Max (0902) $1.32.
Published attempt cost and pass rate

At a glance

Coding index: GPT-5 Mini 34.2 from 2 benchmarks, Qwen3.8 Max (0902) 62.4 from 5 benchmarks.
Widest category: Math, 27.3 points apart on average over 6 shared benchmarks.
Widest single gap: Vibe Code Bench (Vals AI): GPT-5 Mini 14.2% against Qwen3.8 Max (0902) 64.7%, 50.5 points apart on a 0 to 100 scale.
Output price: GPT-5 Mini $2.00 against Qwen3.8 Max (0902) $6.00 per million output tokens, 3.0x apart.
Context window: GPT-5 Mini takes 400K 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-5 Mini	Qwen3.8 Max (0902)
Coding	0	6
Intelligence	0	2
Reasoning	0	12
Math	0	6
Knowledge	2	9
Web design	0	7
General	0	28
All shared boards	2	70

CodingLike-for-likeSix of these boards feed the Vibe Coding Index06

Coding benchmarks for GPT-5 Mini and Qwen3.8 Max (0902)
Benchmark	GPT-5 Mini	Qwen3.8 Max (0902)	Leader
SWE-bench Verified	59.8%	Not measured	Only GPT-5 Mini measured
SWE-bench Multilingual	39.7%	Not measured	Only GPT-5 Mini measured
LiveBench coding	Not measured	60.3%	Only Qwen3.8 Max (0902) measured
LMArena WebDev	Not measured	1674	Only Qwen3.8 Max (0902) measured
AA Coding Index	Not measured	76.2	Only Qwen3.8 Max (0902) measured
LiveCodeBench (Vals AI)	86.6%	87.8%	Qwen3.8 Max (0902)
SWE-bench Verified (Vals AI)	60.8%	85.6%	Qwen3.8 Max (0902)
Terminal-Bench 4 (Vals AI)	Not measured	34.3%	Only Qwen3.8 Max (0902) measured
Vibe Code Bench (Vals AI)	14.2%	64.7%	Qwen3.8 Max (0902)
Code migration (Vals AI)	Not measured	24.0%	Only Qwen3.8 Max (0902) measured
ProgramBench (Vals AI)	Not measured	0.0%	Only Qwen3.8 Max (0902) measured
IOI (Vals AI)	Not measured	68.9%	Only Qwen3.8 Max (0902) measured
Terminal-Bench 2.1 (Vals AI)	Not measured	67.4%	Only Qwen3.8 Max (0902) measured
SWE-bench Multimodal (Vals AI)	Not measured	42.5%	Only Qwen3.8 Max (0902) measured
Vibe Code Bench 1-100 (Vals AI)	Not measured	12.8%	Only Qwen3.8 Max (0902) measured
SkillsBench (Vals AI)	Not measured	42.0%	Only Qwen3.8 Max (0902) measured
CyberBench (Vals AI)	Not measured	28.6%	Only Qwen3.8 Max (0902) measured
LiveCodeBench (Artificial Analysis run)	83.8%	Not measured	Only GPT-5 Mini measured
SciCode	39.0%	53.2%	Qwen3.8 Max (0902)
Terminal-Bench Hard (Artificial Analysis run)	33.3%	Not measured	Only GPT-5 Mini measured
Terminal-Bench	34.8%	Not measured	Only GPT-5 Mini measured
FrontierSWE	Not measured	17.8%	Only Qwen3.8 Max (0902) measured
WeirdML	52.7%	Not measured	Only GPT-5 Mini measured
LMArena Text: coding	1406	1502	Qwen3.8 Max (0902)
LMArena Text: software and IT	1394	1498	Qwen3.8 Max (0902)
LMArena WebDev: React	Not measured	1692	Only Qwen3.8 Max (0902) measured
LMArena WebDev: HTML	Not measured	1649	Only Qwen3.8 Max (0902) measured
LMArena WebDev: from an image	Not measured	1637	Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 11 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02

Intelligence benchmarks for GPT-5 Mini and Qwen3.8 Max (0902)
Benchmark	GPT-5 Mini	Qwen3.8 Max (0902)	Leader
AA Intelligence Index	20.6	45.4	Qwen3.8 Max (0902)
Epoch Capabilities Index	145.3	157.4	Qwen3.8 Max (0902)

Agentic workDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared

Agentic work benchmarks for GPT-5 Mini and Qwen3.8 Max (0902)
Benchmark	GPT-5 Mini	Qwen3.8 Max (0902)	Leader
AA Agentic Index	Not measured	56.0	Only Qwen3.8 Max (0902) measured
Design Arena: agents building web apps	Not measured	1300	Only Qwen3.8 Max (0902) measured
Design Arena: agents building full-stack apps	Not measured	1305	Only Qwen3.8 Max (0902) measured
Design Arena: agents building mobile apps	Not measured	1224	Only Qwen3.8 Max (0902) measured
Design Arena: agents building Android apps	Not measured	1196	Only Qwen3.8 Max (0902) measured
Design Arena: agents building Godot games	Not measured	1234	Only Qwen3.8 Max (0902) measured
Design Arena: PowerPoint slides	Not measured	1233	Only Qwen3.8 Max (0902) measured
Design Arena: spreadsheets	Not measured	967	Only Qwen3.8 Max (0902) measured
LiveBench research	Not measured	69.9%	Only Qwen3.8 Max (0902) measured
LiveBench browser	Not measured	32.0%	Only Qwen3.8 Max (0902) measured
LiveBench long agentic	Not measured	42.3%	Only Qwen3.8 Max (0902) measured
Finance Agent (Vals AI)	Not measured	50.6%	Only Qwen3.8 Max (0902) measured
Tax Agent Bench (Vals AI)	Not measured	32.1%	Only Qwen3.8 Max (0902) measured
Legal Research Bench (Vals AI)	Not measured	47.6%	Only Qwen3.8 Max (0902) measured
Excel Modeling Benchmark (Vals AI)	Not measured	60.1%	Only Qwen3.8 Max (0902) measured
Terminal-Bench-Science (Vals AI)	Not measured	12.9%	Only Qwen3.8 Max (0902) measured
τ²-Bench Telecom	71.1%	Not measured	Only GPT-5 Mini measured
APEX-Agents	Not measured	63.3%	Only Qwen3.8 Max (0902) measured
Vending-Bench 2	-$31	Not measured	Only GPT-5 Mini measured
LMArena Search	Not measured	1261	Only Qwen3.8 Max (0902) measured
Berkeley Function Calling Leaderboard (BFCL)	55.5%	Not measured	Only GPT-5 Mini measured
Neither model has a result on the other 20 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index012

Reasoning benchmarks for GPT-5 Mini and Qwen3.8 Max (0902)
Benchmark	GPT-5 Mini	Qwen3.8 Max (0902)	Leader
GPQA Diamond	80.3%	93.7%	Qwen3.8 Max (0902)
LiveBench reasoning	Not measured	88.2%	Only Qwen3.8 Max (0902) measured
MysteryMechanism (Vals AI)	Not measured	23.9%	Only Qwen3.8 Max (0902) measured
MMMU Pro (Vals AI)	78.9%	88.0%	Qwen3.8 Max (0902)
GPQA Diamond (Artificial Analysis run)	82.8%	92.8%	Qwen3.8 Max (0902)
Humanity's Last Exam (Artificial Analysis run)	21.5%	43.1%	Qwen3.8 Max (0902)
GPQA Diamond (Epoch AI run)	75.0%	92.7%	Qwen3.8 Max (0902)
ARC-AGI	54.3%	Not measured	Only GPT-5 Mini measured
ARC-AGI-2	4.4%	Not measured	Only GPT-5 Mini measured
Chess puzzles	24.0%	46.0%	Qwen3.8 Max (0902)
Mystery game puzzles	10.0%	38.0%	Qwen3.8 Max (0902)
VPCT	40.2%	Not measured	Only GPT-5 Mini measured
LMArena Text: hard prompts	1380	1496	Qwen3.8 Max (0902)
LMArena Text: expert	1379	1507	Qwen3.8 Max (0902)
LMArena Text: hard prompts in English	1383	1503	Qwen3.8 Max (0902)
LMArena Vision: diagrams	1202	1323	Qwen3.8 Max (0902)
LMArena Vision: homework	1210	1336	Qwen3.8 Max (0902)
Kagi LLM Benchmark	70.3%	Not measured	Only GPT-5 Mini measured
Neither model has a result on the other 4 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index06

Math benchmarks for GPT-5 Mini and Qwen3.8 Max (0902)
Benchmark	GPT-5 Mini	Qwen3.8 Max (0902)	Leader
AIME	91.5%	Not measured	Only GPT-5 Mini measured
MATH 500 (Vals AI)	94.8%	Not measured	Only GPT-5 Mini measured
MGSM (Vals AI)	92.6%	Not measured	Only GPT-5 Mini measured
AA Math Index	90.7	Not measured	Only GPT-5 Mini measured
AIME 2025 (Artificial Analysis run)	90.7%	Not measured	Only GPT-5 Mini measured
OTIS Mock AIME	86.7%	100.0%	Qwen3.8 Max (0902)
FrontierMath, tiers 1 to 3	46.7%	74.7%	Qwen3.8 Max (0902)
FrontierMath, tier 4	12.2%	46.3%	Qwen3.8 Max (0902)
ProofBench	9.0%	58.0%	Qwen3.8 Max (0902)
MATH level 5	97.8%	Not measured	Only GPT-5 Mini measured
LMArena Text: math	1378	1501	Qwen3.8 Max (0902)
LMArena Text: mathematical work	1380	1491	Qwen3.8 Max (0902)
Neither model has a result on the other 1 board here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index29

Knowledge benchmarks for GPT-5 Mini and Qwen3.8 Max (0902)
Benchmark	GPT-5 Mini	Qwen3.8 Max (0902)	Leader
MMLU Pro	82.2%	88.6%	Qwen3.8 Max (0902)
LegalBench (Vals AI)	81.8%	83.6%	Qwen3.8 Max (0902)
CaseLaw (Vals AI)	68.5%	Not measured	Only GPT-5 Mini measured
CorpFin (Vals AI)	60.2%	65.8%	Qwen3.8 Max (0902)
TaxEval (Vals AI)	75.2%	75.5%	Qwen3.8 Max (0902)
MortgageTax (Vals AI)	66.9%	64.0%	GPT-5 Mini
MedQA (Vals AI)	96.1%	Not measured	Only GPT-5 Mini measured
MedCode (Vals AI)	43.0%	40.7%	GPT-5 Mini
MMLU Pro (Artificial Analysis run)	83.7%	Not measured	Only GPT-5 Mini measured
SimpleQA Verified	21.6%	47.3%	Qwen3.8 Max (0902)
LMArena Text: science	1371	1512	Qwen3.8 Max (0902)
LMArena Text: medicine and healthcare	1380	1503	Qwen3.8 Max (0902)
LMArena Text: legal and government	1375	1492	Qwen3.8 Max (0902)
LMArena Text: business and finance	1358	1480	Qwen3.8 Max (0902)
FACTS Benchmark Suite	38.6%	Not measured	Only GPT-5 Mini measured
Neither model has a result on the other 3 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index07

Web design benchmarks for GPT-5 Mini and Qwen3.8 Max (0902)
Benchmark	GPT-5 Mini	Qwen3.8 Max (0902)	Leader
Design Arena: websites	1125	1275	Qwen3.8 Max (0902)
Design Arena: UI components	1103	1338	Qwen3.8 Max (0902)
Design Arena: game dev	1129	1312	Qwen3.8 Max (0902)
Design Arena: data viz	1131	1281	Qwen3.8 Max (0902)
Design Arena: 3D	1036	1336	Qwen3.8 Max (0902)
Design Arena: all code categories	1114	1293	Qwen3.8 Max (0902)
Design Arena: SVG	1091	Not measured	Only GPT-5 Mini measured
Design Arena: ASCII art	1125	1200	Qwen3.8 Max (0902)
LiveBench design	Not measured	78.6%	Only Qwen3.8 Max (0902) measured

GeneralLike-for-likePublic boards, shown as published, kept out of the index028

General benchmarks for GPT-5 Mini and Qwen3.8 Max (0902)
Benchmark	GPT-5 Mini	Qwen3.8 Max (0902)	Leader
LiveBench data analysis	Not measured	78.4%	Only Qwen3.8 Max (0902) measured
Public Benefits Bench (Vals AI)	Not measured	67.1%	Only Qwen3.8 Max (0902) measured
SAGE (Vals AI)	43.0%	51.2%	Qwen3.8 Max (0902)
MedScribe (Vals AI)	80.6%	85.0%	Qwen3.8 Max (0902)
Vals Multimodal Index	Not measured	65.4%	Only Qwen3.8 Max (0902) measured
IFBench	75.4%	Not measured	Only GPT-5 Mini measured
Long context reasoning (AA-LCR)	72.3%	80.3%	Qwen3.8 Max (0902)
DTBench	80.5%	92.0%	Qwen3.8 Max (0902)
LMCA	34.2%	46.2%	Qwen3.8 Max (0902)
Fiction.LiveBench	69.4%	Not measured	Only GPT-5 Mini measured
Creative writing (Lech Mazur)	83.1%	Not measured	Only GPT-5 Mini measured
Furniture assembly	Not measured	20.0%	Only Qwen3.8 Max (0902) measured
LMArena Text	1373	1483	Qwen3.8 Max (0902)
LMArena Text: instruction following	1357	1481	Qwen3.8 Max (0902)
LMArena Text: creative writing	1325	1477	Qwen3.8 Max (0902)
LMArena Vision	1202	1313	Qwen3.8 Max (0902)
LMArena Text: English	1379	1491	Qwen3.8 Max (0902)
LMArena Text: non-English	1363	1473	Qwen3.8 Max (0902)
LMArena Text: Chinese	1386	1539	Qwen3.8 Max (0902)
LMArena Text: German	1366	1478	Qwen3.8 Max (0902)
LMArena Text: Japanese	1341	1473	Qwen3.8 Max (0902)
LMArena Text: Korean	1308	1460	Qwen3.8 Max (0902)
LMArena Text: French	1386	1498	Qwen3.8 Max (0902)
LMArena Text: Spanish	1354	1489	Qwen3.8 Max (0902)
LMArena Text: Russian	1362	1482	Qwen3.8 Max (0902)
LMArena Text: Polish	1378	1471	Qwen3.8 Max (0902)
LMArena Text: multi-turn	1363	1489	Qwen3.8 Max (0902)
LMArena Text: longer queries	1355	1488	Qwen3.8 Max (0902)
LMArena Text: writing and language	1344	1477	Qwen3.8 Max (0902)
LMArena Text: entertainment and media	1340	1464	Qwen3.8 Max (0902)
LMArena Vision: English	1216	1311	Qwen3.8 Max (0902)
LMArena Vision: Chinese	1214	1358	Qwen3.8 Max (0902)
LMArena Vision: reading text	1199	1322	Qwen3.8 Max (0902)
LMArena Vision: humor	1205	1304	Qwen3.8 Max (0902)
LMArena Vision: captioning	1217	Not measured	Only GPT-5 Mini measured
LMArena Vision: recognizing things	1226	Not measured	Only GPT-5 Mini measured
LMArena Vision: creative writing	1181	1312	Qwen3.8 Max (0902)
Neither model has a result on the other 9 boards here

Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared

Image generation benchmarks for GPT-5 Mini and Qwen3.8 Max (0902)
Benchmark	GPT-5 Mini	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-5 Mini$0.0013Fits in one request

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

GPT-5 Mini costs less

Repository review

50K input + 3K output tokens

GPT-5 Mini$0.018Fits in one request

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

GPT-5 Mini costs less

Agent loop

200K input + 10K output tokens

GPT-5 Mini$0.070Fits in one request

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

GPT-5 Mini 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-5 Mini and Qwen3.8 Max (0902)
Specification	OpenAI GPT-5 Mini	Qwen3.8 Max (0902)
Maker	OpenAI	Qwen
Weights	No public weights listed	No public weights listed
Released	August 7, 2025	September 3, 2026
Context window	400K	1M
Input $/Mtok	$0.25	$2.00
Output $/Mtok	$2.00	$6.00
Coding index	34.2	62.4
Independent measurements behind it	2	5
Cost per solved task	$0.08	$1.32
Source	OpenRouter listing	OpenRouter listing

Questions

Is GPT-5 Mini better than Qwen3.8 Max (0902) for coding?

Pick Qwen3.8 Max (0902) for coding: it scores 62.4 on the Vibe Coding Index against 34.2 for GPT-5 Mini. Pick GPT-5 Mini for output tokens 3.0x cheaper ($2.00 vs $6.00 per million) and a lower cost per solved task ($0.08 against $1.32).

Which is cheaper, GPT-5 Mini or Qwen3.8 Max (0902)?

GPT-5 Mini costs $0.25 per million input tokens and $2.00 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Per solved SWE-bench Verified task, GPT-5 Mini costs $0.08 and Qwen3.8 Max (0902) $1.32.

Which has the bigger context window, GPT-5 Mini or Qwen3.8 Max (0902)?

Qwen3.8 Max (0902), with 1M tokens against 400K.

How many benchmarks is the GPT-5 Mini vs Qwen3.8 Max (0902) comparison based on?

72 benchmarks have a result for both models as of October 22, 2026. GPT-5 Mini's coding index rests on 2 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-5 Mini or Qwen3.8 Max (0902): which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Math

Knowledge

Web design

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