Gemini 2.5 Pro vs GLM 5.3 Flash

Updated October 21, 2026. 62 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Gemini 2.5 Pro Replace GLM 5.3 Flash

Gemini 2.5 ProGoogle

Coding: 37.0
Overall: 16.1
Output $/M: $10.00

GLM 5.3 FlashZ.ai

Coding: 71.0
Overall: 41.8
Output $/M: $0.50

vs boards won of 62 shared

Decision reading

Pick GLM 5.3 Flash for coding: it scores 71.0 on the Vibe Coding Index against 37.0 for Gemini 2.5 Pro.

Pick Gemini 2.5 Pro when what matters is LMArena Text: medicine and healthcare or LMArena Text: legal and government, where it leads.

Model AGemini 2.5 ProGoogle37.0/1002 independent benchmarks$0.64 per solved task Model BGLM 5.3 FlashZ.ai71.0/1002 independent benchmarks$0.02 per solved task

622540

Shared results: 62
Gemini 2.5 Pro only: 25
GLM 5.3 Flash only: 40
Like-for-like categories: 8 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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, four public coding benchmarks
GLM 5.3 Flash
GLM 5.3 Flash scores 71.0 against 37.0.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
GLM 5.3 Flash
GLM 5.3 Flash leads, 41.8 against 16.1.
Same board, both measured
Agentic work
AA Agentic Index
GLM 5.3 Flash
GLM 5.3 Flash leads, 50.9 against 1.6.
Same board, both measured
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
GLM 5.3 Flash
GLM 5.3 Flash leads, 1272 against 1167.
Same board, both measured
General
Vals Index
No call
Only GLM 5.3 Flash has a Vals Index result, 50.9%.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5.3 Flash
Gemini 2.5 Pro $0.0063, GLM 5.3 Flash $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GLM 5.3 Flash
Gemini 2.5 Pro $0.64, GLM 5.3 Flash $0.02.
Published attempt cost and pass rate

At a glance

Coding index: Gemini 2.5 Pro 37.0 from 2 benchmarks, GLM 5.3 Flash 71.0 from 2 benchmarks.
Widest category: Agentic work, 49.3 points apart on average over 1 shared benchmark.
Widest single gap: ARC-AGI-2: Gemini 2.5 Pro 4.9% against GLM 5.3 Flash 65.8%, 61.0 points apart on a 0 to 100 scale.
Output price: Gemini 2.5 Pro $10.00 against GLM 5.3 Flash $0.50 per million output tokens, 20.0x apart.
Context window: Both take 1.05M tokens.

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	Gemini 2.5 Pro	GLM 5.3 Flash
Coding	0	9
Intelligence	0	2
Agentic work	0	1
Reasoning	0	10
Math	0	5
Knowledge	2	2
Web design	0	6
General	5	20
All shared boards	7	55

CodingLike-for-likeFour of these boards feed the Vibe Coding Index09

Coding benchmarks for Gemini 2.5 Pro and GLM 5.3 Flash
Benchmark	Gemini 2.5 Pro	GLM 5.3 Flash	Leader
SWE-bench Verified	53.6%	Not measured	Only Gemini 2.5 Pro measured
LiveBench coding	Not measured	80.6%	Only GLM 5.3 Flash measured
LMArena WebDev	1226	1607	GLM 5.3 Flash
AA Coding Index	33.3	71.5	GLM 5.3 Flash
LiveCodeBench (Vals AI)	Not measured	80.5%	Only GLM 5.3 Flash measured
SWE-bench Verified (Vals AI)	54.4%	92.0%	GLM 5.3 Flash
Terminal-Bench 4 (Vals AI)	Not measured	37.4%	Only GLM 5.3 Flash measured
Vibe Code Bench (Vals AI)	0.4%	30.8%	GLM 5.3 Flash
Code migration (Vals AI)	Not measured	20.5%	Only GLM 5.3 Flash measured
ProgramBench (Vals AI)	Not measured	0.0%	Only GLM 5.3 Flash measured
IOI (Vals AI)	Not measured	52.5%	Only GLM 5.3 Flash measured
Terminal-Bench 2.1 (Vals AI)	Not measured	62.9%	Only GLM 5.3 Flash measured
Vibe Code Bench 1-100 (Vals AI)	Not measured	16.0%	Only GLM 5.3 Flash measured
SkillsBench (Vals AI)	Not measured	40.2%	Only GLM 5.3 Flash measured
CyberBench (Vals AI)	Not measured	67.9%	Only GLM 5.3 Flash measured
LiveCodeBench (Artificial Analysis run)	80.1%	Not measured	Only Gemini 2.5 Pro measured
SciCode	46.3%	51.6%	GLM 5.3 Flash
Terminal-Bench Hard (Artificial Analysis run)	26.5%	Not measured	Only Gemini 2.5 Pro measured
Terminal-Bench	32.6%	Not measured	Only Gemini 2.5 Pro measured
FrontierCode	Not measured	31.8%	Only GLM 5.3 Flash measured
FrontierSWE	Not measured	18.1%	Only GLM 5.3 Flash measured
GSO-Bench	3.9%	Not measured	Only Gemini 2.5 Pro measured
WeirdML	54.0%	Not measured	Only Gemini 2.5 Pro measured
ALE-Bench	Not measured	303.6	Only GLM 5.3 Flash measured
LMArena Text: coding	1452	1507	GLM 5.3 Flash
LMArena Text: software and IT	1459	1500	GLM 5.3 Flash
LMArena WebDev: React	Not measured	1624	Only GLM 5.3 Flash measured
LMArena WebDev: HTML	1235	1577	GLM 5.3 Flash
LMArena WebDev: from an image	1285	1578	GLM 5.3 Flash
Neither model has a result on the other 9 boards here

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

Intelligence benchmarks for Gemini 2.5 Pro and GLM 5.3 Flash
Benchmark	Gemini 2.5 Pro	GLM 5.3 Flash	Leader
AA Intelligence Index	16.1	41.8	GLM 5.3 Flash
Epoch Capabilities Index	145.1	153.1	GLM 5.3 Flash

Agentic workLike-for-likePublic boards, shown as published, kept out of the index01

Agentic work benchmarks for Gemini 2.5 Pro and GLM 5.3 Flash
Benchmark	Gemini 2.5 Pro	GLM 5.3 Flash	Leader
AA Agentic Index	1.6	50.9	GLM 5.3 Flash
LiveBench research	Not measured	70.1%	Only GLM 5.3 Flash measured
LiveBench browser	Not measured	84.0%	Only GLM 5.3 Flash measured
LiveBench long agentic	Not measured	28.4%	Only GLM 5.3 Flash measured
SREBench (Vals AI)	Not measured	0.8%	Only GLM 5.3 Flash measured
Finance Agent (Vals AI)	Not measured	57.9%	Only GLM 5.3 Flash measured
Tax Agent Bench (Vals AI)	Not measured	31.6%	Only GLM 5.3 Flash measured
Legal Research Bench (Vals AI)	Not measured	45.2%	Only GLM 5.3 Flash measured
Harvey's Legal Agent Benchmark (Vals AI)	Not measured	10.4%	Only GLM 5.3 Flash measured
Excel Modeling Benchmark (Vals AI)	Not measured	55.9%	Only GLM 5.3 Flash measured
Terminal-Bench-Science (Vals AI)	Not measured	2.9%	Only GLM 5.3 Flash measured
τ²-Bench Telecom	54.1%	Not measured	Only Gemini 2.5 Pro measured
APEX-Agents	Not measured	52.8%	Only GLM 5.3 Flash measured
GDPval	23.3%	Not measured	Only Gemini 2.5 Pro measured
DeepResearch Bench	41.5%	Not measured	Only Gemini 2.5 Pro measured
Vending-Bench 2	$574	Not measured	Only Gemini 2.5 Pro measured
Neither model has a result on the other 23 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index010

Reasoning benchmarks for Gemini 2.5 Pro and GLM 5.3 Flash
Benchmark	Gemini 2.5 Pro	GLM 5.3 Flash	Leader
GPQA Diamond	Not measured	86.4%	Only GLM 5.3 Flash measured
LiveBench reasoning	Not measured	77.6%	Only GLM 5.3 Flash measured
MMMU Pro (Vals AI)	Not measured	86.0%	Only GLM 5.3 Flash measured
GPQA Diamond (Artificial Analysis run)	84.4%	91.2%	GLM 5.3 Flash
Humanity's Last Exam (Artificial Analysis run)	22.5%	39.9%	GLM 5.3 Flash
GPQA Diamond (Epoch AI run)	85.3%	90.2%	GLM 5.3 Flash
ARC-AGI	41.0%	91.0%	GLM 5.3 Flash
ARC-AGI-2	4.9%	65.8%	GLM 5.3 Flash
Chess puzzles	Not measured	21.0%	Only GLM 5.3 Flash measured
Mystery game puzzles	Not measured	8.0%	Only GLM 5.3 Flash measured
LMArena Text: hard prompts	1455	1490	GLM 5.3 Flash
LMArena Text: expert	1452	1511	GLM 5.3 Flash
LMArena Text: hard prompts in English	1453	1488	GLM 5.3 Flash
LMArena Vision: diagrams	1274	1317	GLM 5.3 Flash
LMArena Vision: homework	1281	1318	GLM 5.3 Flash
Neither model has a result on the other 6 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index05

Math benchmarks for Gemini 2.5 Pro and GLM 5.3 Flash
Benchmark	Gemini 2.5 Pro	GLM 5.3 Flash	Leader
AA Math Index	87.7	Not measured	Only Gemini 2.5 Pro measured
AIME 2025 (Artificial Analysis run)	87.7%	Not measured	Only Gemini 2.5 Pro measured
OTIS Mock AIME	84.7%	93.9%	GLM 5.3 Flash
FrontierMath, tiers 1 to 3	24.6%	55.8%	GLM 5.3 Flash
FrontierMath, tier 4	0.0%	17.1%	GLM 5.3 Flash
ProofBench	Not measured	21.0%	Only GLM 5.3 Flash measured
LMArena Text: math	1450	1503	GLM 5.3 Flash
LMArena Text: mathematical work	1454	1497	GLM 5.3 Flash
Neither model has a result on the other 5 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22

Knowledge benchmarks for Gemini 2.5 Pro and GLM 5.3 Flash
Benchmark	Gemini 2.5 Pro	GLM 5.3 Flash	Leader
MMLU Pro	Not measured	86.1%	Only GLM 5.3 Flash measured
LegalBench (Vals AI)	Not measured	83.9%	Only GLM 5.3 Flash measured
CaseLaw (Vals AI)	63.9%	Not measured	Only Gemini 2.5 Pro measured
CorpFin (Vals AI)	60.8%	Not measured	Only Gemini 2.5 Pro measured
TaxEval (Vals AI)	Not measured	75.6%	Only GLM 5.3 Flash measured
MortgageTax (Vals AI)	68.9%	Not measured	Only Gemini 2.5 Pro measured
MedCode (Vals AI)	50.6%	Not measured	Only Gemini 2.5 Pro measured
MMLU Pro (Artificial Analysis run)	86.2%	Not measured	Only Gemini 2.5 Pro measured
LMArena Text: science	1480	1484	GLM 5.3 Flash
LMArena Text: medicine and healthcare	1476	1475	Gemini 2.5 Pro
LMArena Text: legal and government	1480	1473	Gemini 2.5 Pro
LMArena Text: business and finance	1439	1460	GLM 5.3 Flash
Neither model has a result on the other 5 boards here

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

Web design benchmarks for Gemini 2.5 Pro and GLM 5.3 Flash
Benchmark	Gemini 2.5 Pro	GLM 5.3 Flash	Leader
Design Arena: websites	1167	1272	GLM 5.3 Flash
Design Arena: UI components	1139	1316	GLM 5.3 Flash
Design Arena: game dev	1112	1279	GLM 5.3 Flash
Design Arena: data viz	1222	1262	GLM 5.3 Flash
Design Arena: 3D	1080	1316	GLM 5.3 Flash
Design Arena: all code categories	1152	1282	GLM 5.3 Flash
Design Arena: SVG	Not measured	1284	Only GLM 5.3 Flash measured
Design Arena: ASCII art	Not measured	1269	Only GLM 5.3 Flash measured
LiveBench design	Not measured	77.2%	Only GLM 5.3 Flash measured

GeneralLike-for-likePublic boards, shown as published, kept out of the index520

General benchmarks for Gemini 2.5 Pro and GLM 5.3 Flash
Benchmark	Gemini 2.5 Pro	GLM 5.3 Flash	Leader
Vals Index	Not measured	50.9%	Only GLM 5.3 Flash measured
LiveBench data analysis	Not measured	76.4%	Only GLM 5.3 Flash measured
SAGE (Vals AI)	41.9%	Not measured	Only Gemini 2.5 Pro measured
MedScribe (Vals AI)	73.5%	88.9%	GLM 5.3 Flash
IFBench	48.7%	Not measured	Only Gemini 2.5 Pro measured
Long context reasoning (AA-LCR)	69.0%	80.0%	GLM 5.3 Flash
DTBench	82.4%	Not measured	Only Gemini 2.5 Pro measured
LMCA	34.8%	Not measured	Only Gemini 2.5 Pro measured
Creative writing (Lech Mazur)	83.8%	Not measured	Only Gemini 2.5 Pro measured
Surface Evolver Bench	Not measured	52.5%	Only GLM 5.3 Flash measured
LMArena Text	1458	1471	GLM 5.3 Flash
LMArena Text: instruction following	1437	1478	GLM 5.3 Flash
LMArena Text: creative writing	1454	1441	Gemini 2.5 Pro
LMArena Vision	1263	1294	GLM 5.3 Flash
LMArena Text: English	1458	1474	GLM 5.3 Flash
LMArena Text: non-English	1452	1462	GLM 5.3 Flash
LMArena Text: Chinese	1507	1531	GLM 5.3 Flash
LMArena Text: German	1487	1462	Gemini 2.5 Pro
LMArena Text: Japanese	1461	1444	Gemini 2.5 Pro
LMArena Text: Korean	1434	1436	GLM 5.3 Flash
LMArena Text: French	1473	1491	GLM 5.3 Flash
LMArena Text: Spanish	1474	1475	GLM 5.3 Flash
LMArena Text: Russian	1461	1465	GLM 5.3 Flash
LMArena Text: Polish	1479	1450	Gemini 2.5 Pro
LMArena Text: multi-turn	1453	1469	GLM 5.3 Flash
LMArena Text: longer queries	1449	1481	GLM 5.3 Flash
LMArena Text: writing and language	1454	1455	GLM 5.3 Flash
LMArena Text: entertainment and media	1441	1440	Gemini 2.5 Pro
LMArena Vision: English	1261	1295	GLM 5.3 Flash
LMArena Vision: Chinese	1300	1363	GLM 5.3 Flash
LMArena Vision: reading text	1270	1299	GLM 5.3 Flash
LMArena Vision: humor	1262	1279	GLM 5.3 Flash
LMArena Vision: captioning	1304	Not measured	Only Gemini 2.5 Pro measured
LMArena Vision: recognizing things	1283	Not measured	Only Gemini 2.5 Pro measured
LMArena Vision: creative writing	1265	1270	GLM 5.3 Flash
LMArena Document	1421	Not measured	Only Gemini 2.5 Pro measured
Neither model has a result on the other 10 boards here

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

Image generation benchmarks for Gemini 2.5 Pro and GLM 5.3 Flash
Benchmark	Gemini 2.5 Pro	GLM 5.3 Flash	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

Gemini 2.5 Pro$0.0063Fits in one request

GLM 5.3 Flash$0.0004Fits in one request

GLM 5.3 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Pro$0.092Fits in one request

GLM 5.3 Flash$0.0090Fits in one request

GLM 5.3 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 2.5 Pro$0.350Fits in one request

GLM 5.3 Flash$0.035Fits 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 Gemini 2.5 Pro and GLM 5.3 Flash
Specification	Google Gemini 2.5 Pro	Z.ai GLM 5.3 Flash
Maker	Google	Z.ai
Weights	No public weights listed	Open weights
Released	June 17, 2025	August 26, 2026
Context window	1.05M	1.05M
Input $/Mtok	$1.25	$0.15
Output $/Mtok	$10.00	$0.50
Coding index	37.0	71.0
Independent measurements behind it	2	2
Cost per solved task	$0.64	$0.02
Source	OpenRouter listing	OpenRouter listing

Questions

Is Gemini 2.5 Pro better than GLM 5.3 Flash for coding?

Pick GLM 5.3 Flash for coding: it scores 71.0 on the Vibe Coding Index against 37.0 for Gemini 2.5 Pro. Pick Gemini 2.5 Pro when what matters is LMArena Text: medicine and healthcare or LMArena Text: legal and government, where it leads.

Which is cheaper, Gemini 2.5 Pro or GLM 5.3 Flash?

Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; GLM 5.3 Flash costs $0.15 and $0.50. Per solved SWE-bench Verified task, Gemini 2.5 Pro costs $0.64 and GLM 5.3 Flash $0.02.

Which has the bigger context window, Gemini 2.5 Pro or GLM 5.3 Flash?

Neither: both take 1.05M tokens.

How many benchmarks is the Gemini 2.5 Pro vs GLM 5.3 Flash comparison based on?

62 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Pro's coding index rests on 2 independent benchmarks and GLM 5.3 Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.

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<iframe src="https://llmbenchmark.ai/embed/compare/gemini-2-5-pro-vs-glm-5-3-flash" title="Gemini 2.5 Pro vs GLM 5.3 Flash, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
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Decision reading

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