GLM 5.3 Flash vs GPT-6.1 Sol

GPT-6.1 Sol leads GLM 5.3 Flash on coding, 82.4 to 57.7 on the Vibe Coding Index, and GLM 5.3 Flash costs 20.0x less per output token ($0.50 vs $10.00 per million). Updated October 22, 2026; 79 benchmarks have a result for both.

Replace GLM 5.3 Flash Replace GPT-6.1 Sol

GLM 5.3 FlashZ.ai

Coding: 57.7
Overall: 66.0
Output $/M: $0.50

GPT-6.1 SolOpenAI

Coding: 82.4
Overall: 81.4
Output $/M: $10.00

vs boards won of 79 shared

GLM 5.3 Flash or GPT-6.1 Sol: which to pick

Pick GPT-6.1 Sol for coding: it scores 82.4 on the Vibe Coding Index against 57.7 for GLM 5.3 Flash, though on 5 benchmarks against 6.

Pick GLM 5.3 Flash for output tokens 20.0x cheaper ($0.50 vs $10.00 per million) and work measured by CyberBench (Vals AI) or LMArena Text: coding, where it leads.

Model AGLM 5.3 FlashZ.ai57.7/1006 independent benchmarks$0.02 per solved task Model BGPT-6.1 SolOpenAI82.4/1005 independent benchmarksNo cost per solved task

792319

Shared results: 79
GLM 5.3 Flash only: 23
GPT-6.1 Sol only: 19
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-6.1 Sol
GPT-6.1 Sol scores 82.4 against 57.7.
6 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-6.1 Sol
GPT-6.1 Sol leads, 51.8 against 41.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GLM 5.3 Flash has a AA Agentic Index result, 50.9.
Directional only
Reasoning
GPQA Diamond
No call
Only GLM 5.3 Flash has a GPQA Diamond result, 86.4%.
Directional only
Knowledge
MMLU Pro
No call
Only GLM 5.3 Flash has a MMLU Pro result, 86.1%.
Directional only
Web design
Design Arena: websites
GPT-6.1 Sol
GPT-6.1 Sol leads, 1321 against 1272.
Same board, both measured
General
Vals Index
GPT-6.1 Sol
GPT-6.1 Sol leads, 63.9% against 50.9%.
Same board, both measured
Long documents
Listed context window
GPT-6.1 Sol
GPT-6.1 Sol takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5.3 Flash
GLM 5.3 Flash $0.0004, GPT-6.1 Sol $0.0070 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GLM 5.3 Flash has the number, $0.02.
Directional only

At a glance

Coding index: GLM 5.3 Flash 57.7 from 6 benchmarks, GPT-6.1 Sol 82.4 from 5 benchmarks.
Widest category: Math, 35.0 points apart on average over 6 shared benchmarks.
Widest single gap: FrontierMath, tier 4: GLM 5.3 Flash 17.1% against GPT-6.1 Sol 100.0%, 82.9 points apart on a 0 to 100 scale.
Output price: GLM 5.3 Flash $0.50 against GPT-6.1 Sol $10.00 per million output tokens, 20.0x apart.
Context window: GLM 5.3 Flash takes 1.05M tokens, GPT-6.1 Sol 1.05M.

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	GLM 5.3 Flash	GPT-6.1 Sol
Coding	3	13
Intelligence	0	2
Agentic work	4	7
Reasoning	4	8
Math	1	5
Knowledge	4	0
Web design	0	7
General	17	4
All shared boards	33	46

CodingLike-for-likeSix of these boards feed the Vibe Coding Index313

Coding benchmarks for GLM 5.3 Flash and GPT-6.1 Sol
Benchmark	GLM 5.3 Flash	GPT-6.1 Sol	Leader
LiveBench coding	80.6%	96.0%	GPT-6.1 Sol
LMArena WebDev	1607	1753	GPT-6.1 Sol
AA Coding Index	71.5	Not measured	Only GLM 5.3 Flash measured
LiveCodeBench (Vals AI)	80.5%	Not measured	Only GLM 5.3 Flash measured
SWE-bench Verified (Vals AI)	92.0%	Not measured	Only GLM 5.3 Flash measured
Terminal-Bench 4 (Vals AI)	37.4%	55.0%	GPT-6.1 Sol
Vibe Code Bench (Vals AI)	30.8%	88.9%	GPT-6.1 Sol
Code migration (Vals AI)	20.5%	65.1%	GPT-6.1 Sol
ProgramBench (Vals AI)	0.0%	3.0%	GPT-6.1 Sol
IOI (Vals AI)	52.5%	96.9%	GPT-6.1 Sol
Terminal-Bench 2.1 (Vals AI)	62.9%	Not measured	Only GLM 5.3 Flash measured
SWE-bench Multimodal (Vals AI)	Not measured	43.5%	Only GPT-6.1 Sol measured
Vibe Code Bench 1-100 (Vals AI)	16.0%	Not measured	Only GLM 5.3 Flash measured
SkillsBench (Vals AI)	40.2%	Not measured	Only GLM 5.3 Flash measured
CyberBench (Vals AI)	67.9%	39.3%	GLM 5.3 Flash
SciCode	51.6%	55.8%	GPT-6.1 Sol
FrontierCode	31.8%	50.2%	GPT-6.1 Sol
FrontierSWE	18.1%	Not measured	Only GLM 5.3 Flash measured
ALE-Bench	303.6	2743.8	GPT-6.1 Sol
LMArena Text: coding	1507	1478	GLM 5.3 Flash
LMArena Text: software and IT	1500	1476	GLM 5.3 Flash
LMArena WebDev: React	1624	1754	GPT-6.1 Sol
LMArena WebDev: HTML	1577	1800	GPT-6.1 Sol
LMArena WebDev: from an image	1578	1702	GPT-6.1 Sol
SciCode	Not measured	9.2%	Only GPT-6.1 Sol measured
Neither model has a result on the other 14 boards here

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

Intelligence benchmarks for GLM 5.3 Flash and GPT-6.1 Sol
Benchmark	GLM 5.3 Flash	GPT-6.1 Sol	Leader
AA Intelligence Index	41.8	51.8	GPT-6.1 Sol
Epoch Capabilities Index	153.1	168.4	GPT-6.1 Sol

Agentic workLike-for-likePublic boards, shown as published, kept out of the index47

Agentic work benchmarks for GLM 5.3 Flash and GPT-6.1 Sol
Benchmark	GLM 5.3 Flash	GPT-6.1 Sol	Leader
AA Agentic Index	50.9	Not measured	Only GLM 5.3 Flash measured
Design Arena: agents building web apps	Not measured	1306	Only GPT-6.1 Sol measured
Design Arena: agents building mobile apps	Not measured	1213	Only GPT-6.1 Sol measured
Design Arena: spreadsheets	Not measured	1259	Only GPT-6.1 Sol measured
LiveBench research	70.1%	83.5%	GPT-6.1 Sol
LiveBench browser	84.0%	88.0%	GPT-6.1 Sol
LiveBench long agentic	28.4%	73.0%	GPT-6.1 Sol
SREBench (Vals AI)	0.8%	50.8%	GPT-6.1 Sol
Finance Agent (Vals AI)	57.9%	52.0%	GLM 5.3 Flash
Tax Agent Bench (Vals AI)	31.6%	21.8%	GLM 5.3 Flash
Legal Research Bench (Vals AI)	45.2%	38.5%	GLM 5.3 Flash
Harvey's Legal Agent Benchmark (Vals AI)	10.4%	6.3%	GLM 5.3 Flash
Excel Modeling Benchmark (Vals AI)	55.9%	70.8%	GPT-6.1 Sol
BioMysteryBench (Vals AI)	Not measured	79.6%	Only GPT-6.1 Sol measured
Terminal-Bench-Science (Vals AI)	2.9%	52.9%	GPT-6.1 Sol
Vals Science Index	Not measured	59.6%	Only GPT-6.1 Sol measured
Robo-bench (Vals AI)	Not measured	28.3%	Only GPT-6.1 Sol measured
APEX-Agents	52.8%	60.0%	GPT-6.1 Sol
SpireClimb	Not measured	24.7%	Only GPT-6.1 Sol measured
Neither model has a result on the other 22 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index48

Reasoning benchmarks for GLM 5.3 Flash and GPT-6.1 Sol
Benchmark	GLM 5.3 Flash	GPT-6.1 Sol	Leader
GPQA Diamond	86.4%	Not measured	Only GLM 5.3 Flash measured
LiveBench reasoning	77.6%	92.6%	GPT-6.1 Sol
MysteryMechanism (Vals AI)	Not measured	46.4%	Only GPT-6.1 Sol measured
MMMU Pro (Vals AI)	86.0%	Not measured	Only GLM 5.3 Flash measured
GPQA Diamond (Artificial Analysis run)	91.2%	Not measured	Only GLM 5.3 Flash measured
Humanity's Last Exam (Artificial Analysis run)	39.9%	52.9%	GPT-6.1 Sol
GPQA Diamond (Epoch AI run)	90.2%	95.4%	GPT-6.1 Sol
ARC-AGI	91.0%	98.5%	GPT-6.1 Sol
ARC-AGI-2	65.8%	94.2%	GPT-6.1 Sol
Chess puzzles	21.0%	68.0%	GPT-6.1 Sol
Mystery game puzzles	8.0%	80.0%	GPT-6.1 Sol
EBR-bench	Not measured	54.3%	Only GPT-6.1 Sol measured
LMArena Text: hard prompts	1490	1463	GLM 5.3 Flash
LMArena Text: expert	1511	1489	GLM 5.3 Flash
LMArena Text: hard prompts in English	1488	1465	GLM 5.3 Flash
LMArena Vision: diagrams	1317	1306	GLM 5.3 Flash
LMArena Vision: homework	1318	1356	GPT-6.1 Sol
Neither model has a result on the other 5 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index15

Math benchmarks for GLM 5.3 Flash and GPT-6.1 Sol
Benchmark	GLM 5.3 Flash	GPT-6.1 Sol	Leader
OTIS Mock AIME	93.9%	100.0%	GPT-6.1 Sol
FrontierMath, tiers 1 to 3	55.8%	93.7%	GPT-6.1 Sol
FrontierMath, tier 4	17.1%	100.0%	GPT-6.1 Sol
ProofBench	21.0%	99.0%	GPT-6.1 Sol
LMArena Text: math	1503	1489	GLM 5.3 Flash
LMArena Text: mathematical work	1497	1513	GPT-6.1 Sol
Neither model has a result on the other 7 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40

Knowledge benchmarks for GLM 5.3 Flash and GPT-6.1 Sol
Benchmark	GLM 5.3 Flash	GPT-6.1 Sol	Leader
MMLU Pro	86.1%	Not measured	Only GLM 5.3 Flash measured
LegalBench (Vals AI)	83.9%	Not measured	Only GLM 5.3 Flash measured
TaxEval (Vals AI)	75.6%	Not measured	Only GLM 5.3 Flash measured
MedCode (Vals AI)	Not measured	48.8%	Only GPT-6.1 Sol measured
SimpleQA Verified	Not measured	73.9%	Only GPT-6.1 Sol measured
LMArena Text: science	1484	1444	GLM 5.3 Flash
LMArena Text: medicine and healthcare	1475	1433	GLM 5.3 Flash
LMArena Text: legal and government	1473	1471	GLM 5.3 Flash
LMArena Text: business and finance	1460	1445	GLM 5.3 Flash
FACTS Benchmark Suite	Not measured	75.3%	Only GPT-6.1 Sol measured
Neither model has a result on the other 8 boards here

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

Web design benchmarks for GLM 5.3 Flash and GPT-6.1 Sol
Benchmark	GLM 5.3 Flash	GPT-6.1 Sol	Leader
Design Arena: websites	1272	1321	GPT-6.1 Sol
Design Arena: UI components	1316	1317	GPT-6.1 Sol
Design Arena: game dev	1278	1389	GPT-6.1 Sol
Design Arena: data viz	1262	1281	GPT-6.1 Sol
Design Arena: 3D	1316	1460	GPT-6.1 Sol
Design Arena: all code categories	1282	1345	GPT-6.1 Sol
Design Arena: SVG	1285	Not measured	Only GLM 5.3 Flash measured
Design Arena: ASCII art	1267	Not measured	Only GLM 5.3 Flash measured
LiveBench design	77.2%	82.1%	GPT-6.1 Sol

GeneralLike-for-likePublic boards, shown as published, kept out of the index174

General benchmarks for GLM 5.3 Flash and GPT-6.1 Sol
Benchmark	GLM 5.3 Flash	GPT-6.1 Sol	Leader
Vals Index	50.9%	63.9%	GPT-6.1 Sol
LiveBench data analysis	76.4%	82.7%	GPT-6.1 Sol
Public Benefits Bench (Vals AI)	Not measured	59.3%	Only GPT-6.1 Sol measured
SAGE (Vals AI)	Not measured	46.5%	Only GPT-6.1 Sol measured
MedScribe (Vals AI)	88.9%	86.5%	GLM 5.3 Flash
Long context reasoning (AA-LCR)	80.0%	84.0%	GPT-6.1 Sol
DTBench	Not measured	96.5%	Only GPT-6.1 Sol measured
LMCA	Not measured	62.8%	Only GPT-6.1 Sol measured
Surface Evolver Bench	52.5%	Not measured	Only GLM 5.3 Flash measured
Furniture assembly	Not measured	80.0%	Only GPT-6.1 Sol measured
LMArena Text	1471	1443	GLM 5.3 Flash
LMArena Text: instruction following	1478	1466	GLM 5.3 Flash
LMArena Text: creative writing	1441	1425	GLM 5.3 Flash
LMArena Vision	1294	1288	GLM 5.3 Flash
LMArena Text: English	1474	1450	GLM 5.3 Flash
LMArena Text: non-English	1462	1433	GLM 5.3 Flash
LMArena Text: Chinese	1531	1487	GLM 5.3 Flash
LMArena Text: German	1462	Not measured	Only GLM 5.3 Flash measured
LMArena Text: Japanese	1444	Not measured	Only GLM 5.3 Flash measured
LMArena Text: Korean	1436	Not measured	Only GLM 5.3 Flash measured
LMArena Text: French	1491	1460	GLM 5.3 Flash
LMArena Text: Spanish	1475	1439	GLM 5.3 Flash
LMArena Text: Russian	1465	1457	GLM 5.3 Flash
LMArena Text: Polish	1450	Not measured	Only GLM 5.3 Flash measured
LMArena Text: multi-turn	1469	1442	GLM 5.3 Flash
LMArena Text: longer queries	1481	1458	GLM 5.3 Flash
LMArena Text: writing and language	1455	1444	GLM 5.3 Flash
LMArena Text: entertainment and media	1440	1426	GLM 5.3 Flash
LMArena Vision: English	1295	1274	GLM 5.3 Flash
LMArena Vision: Chinese	1363	Not measured	Only GLM 5.3 Flash measured
LMArena Vision: reading text	1299	1289	GLM 5.3 Flash
LMArena Vision: humor	1279	Not measured	Only GLM 5.3 Flash measured
LMArena Vision: creative writing	1270	1301	GPT-6.1 Sol
Neither model has a result on the other 13 boards here

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

Image generation benchmarks for GLM 5.3 Flash and GPT-6.1 Sol
Benchmark	GLM 5.3 Flash	GPT-6.1 Sol	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

GLM 5.3 Flash$0.0004Fits in one request

GPT-6.1 Sol$0.0070Fits in one request

GLM 5.3 Flash costs less

Repository review

50K input + 3K output tokens

GLM 5.3 Flash$0.0090Fits in one request

GPT-6.1 Sol$0.130Fits in one request

GLM 5.3 Flash costs less

Agent loop

200K input + 10K output tokens

GLM 5.3 Flash$0.035Fits in one request

GPT-6.1 Sol$0.500Fits in one request

GLM 5.3 Flash 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 GLM 5.3 Flash and GPT-6.1 Sol
Specification	Z.ai GLM 5.3 Flash	OpenAI GPT-6.1 Sol
Maker	Z.ai	OpenAI
Weights	Open weights	No public weights listed
Released	August 26, 2026	September 29, 2026
Context window	1.05M	1.05M
Input $/Mtok	$0.15	$2.00
Output $/Mtok	$0.50	$10.00
Coding index	57.7	82.4
Independent measurements behind it	6	5
Cost per solved task	$0.02	Not computable
Source	OpenRouter listing	OpenRouter listing

Questions

Is GLM 5.3 Flash better than GPT-6.1 Sol for coding?

Pick GPT-6.1 Sol for coding: it scores 82.4 on the Vibe Coding Index against 57.7 for GLM 5.3 Flash, though on 5 benchmarks against 6. Pick GLM 5.3 Flash for output tokens 20.0x cheaper ($0.50 vs $10.00 per million) and work measured by CyberBench (Vals AI) or LMArena Text: coding, where it leads.

Which is cheaper, GLM 5.3 Flash or GPT-6.1 Sol?

GLM 5.3 Flash costs $0.15 per million input tokens and $0.50 per million output tokens; GPT-6.1 Sol costs $2.00 and $10.00. Cost per solved task is known for GLM 5.3 Flash only.

Which has the bigger context window, GLM 5.3 Flash or GPT-6.1 Sol?

GPT-6.1 Sol, with 1.05M tokens against 1.05M.

How many benchmarks is the GLM 5.3 Flash vs GPT-6.1 Sol comparison based on?

79 benchmarks have a result for both models as of October 22, 2026. GLM 5.3 Flash's coding index rests on 6 independent benchmarks and GPT-6.1 Sol's on 5. Where only one model has a result, the page says so instead of naming a winner.

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GLM 5.3 Flash or GPT-6.1 Sol: 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