Gemini 3.8 Flash vs GLM 4.6

Gemini 3.8 Flash leads GLM 4.6 on coding, 61.6 to 8.8 on the Vibe Coding Index, and GLM 4.6 costs 1.7x less per output token ($2.20 vs $3.75 per million). Updated October 22, 2026; 53 benchmarks have a result for both.

Replace Gemini 3.8 Flash Replace GLM 4.6

Gemini 3.8 FlashGoogle

Coding: 61.6
Overall: 69.0
Output $/M: $3.75

GLM 4.6Z.ai

Coding: 8.8
Overall: 33.4
Output $/M: $2.20

vs boards won of 53 shared

Gemini 3.8 Flash or GLM 4.6: which to pick

Pick Gemini 3.8 Flash for coding: it scores 61.6 on the Vibe Coding Index against 8.8 for GLM 4.6.

Pick GLM 4.6 for output tokens 1.7x cheaper ($2.20 vs $3.75 per million) and work measured by Design Arena: agents building Android apps, where it leads.

Model AGemini 3.8 FlashGoogle61.6/1006 independent benchmarks$2.74 per solved task Model BGLM 4.6Z.ai8.8/1002 independent benchmarksNo cost per solved task

537516

Shared results: 53
Gemini 3.8 Flash only: 75
GLM 4.6 only: 16
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
Gemini 3.8 Flash
Gemini 3.8 Flash scores 61.6 against 8.8.
6 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 40.9 against 18.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Gemini 3.8 Flash has a AA Agentic Index result, 40.2.
Directional only
Reasoning
GPQA Diamond
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 94.4% against 74.5%.
Same board, both measured
Math
AIME
No call
Only GLM 4.6 has a AIME result, 92.7%.
Directional only
Knowledge
MMLU Pro
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 90.2% against 82.2%.
Same board, both measured
Web design
Design Arena: websites
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 1300 against 1174.
Same board, both measured
General
Vals Index
No call
Only Gemini 3.8 Flash has a Vals Index result, 56.0%.
Directional only
Long documents
Listed context window
Gemini 3.8 Flash
Gemini 3.8 Flash takes 1.05M tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 4.6
Gemini 3.8 Flash $0.0026, GLM 4.6 $0.0017 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 3.8 Flash has the number, $2.74.
Directional only

At a glance

Coding index: Gemini 3.8 Flash 61.6 from 6 benchmarks, GLM 4.6 8.8 from 2 benchmarks.
Widest category: Coding, 30.0 points apart on average over 8 shared benchmarks.
Widest single gap: Vibe Code Bench (Vals AI): Gemini 3.8 Flash 78.7% against GLM 4.6 3.1%, 75.6 points apart on a 0 to 100 scale.
Output price: Gemini 3.8 Flash $3.75 against GLM 4.6 $2.20 per million output tokens, 1.7x apart.
Context window: Gemini 3.8 Flash takes 1.05M tokens, GLM 4.6 205K.

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 3.8 Flash	GLM 4.6
Coding	8	0
Intelligence	1	0
Agentic work	3	1
Reasoning	6	0
Math	2	0
Knowledge	7	0
Web design	7	0
General	18	0
All shared boards	52	1

CodingLike-for-likeSix of these boards feed the Vibe Coding Index80

Coding benchmarks for Gemini 3.8 Flash and GLM 4.6
Benchmark	Gemini 3.8 Flash	GLM 4.6	Leader
SWE-bench Verified	Not measured	68.2%	Only GLM 4.6 measured
LiveBench coding	82.2%	Not measured	Only Gemini 3.8 Flash measured
LMArena WebDev	1585	1341	Gemini 3.8 Flash
AA Coding Index	76.3	45.8	Gemini 3.8 Flash
LiveCodeBench (Vals AI)	89.5%	81.0%	Gemini 3.8 Flash
SWE-bench Verified (Vals AI)	80.0%	Not measured	Only Gemini 3.8 Flash measured
Terminal-Bench 4 (Vals AI)	19.7%	Not measured	Only Gemini 3.8 Flash measured
Vibe Code Bench (Vals AI)	78.7%	3.1%	Gemini 3.8 Flash
Code migration (Vals AI)	36.5%	Not measured	Only Gemini 3.8 Flash measured
ProgramBench (Vals AI)	1.0%	Not measured	Only Gemini 3.8 Flash measured
IOI (Vals AI)	56.9%	Not measured	Only Gemini 3.8 Flash measured
Terminal-Bench 2.1 (Vals AI)	81.3%	Not measured	Only Gemini 3.8 Flash measured
SWE-bench Multimodal (Vals AI)	40.8%	Not measured	Only Gemini 3.8 Flash measured
Vibe Code Bench 1-100 (Vals AI)	18.8%	Not measured	Only Gemini 3.8 Flash measured
SkillsBench (Vals AI)	58.0%	Not measured	Only Gemini 3.8 Flash measured
CyberBench (Vals AI)	43.8%	Not measured	Only Gemini 3.8 Flash measured
LiveCodeBench (Artificial Analysis run)	Not measured	69.5%	Only GLM 4.6 measured
SciCode	56.6%	Not measured	Only Gemini 3.8 Flash measured
Terminal-Bench Hard (Artificial Analysis run)	Not measured	28.8%	Only GLM 4.6 measured
Terminal-Bench	Not measured	24.5%	Only GLM 4.6 measured
FrontierCode	41.2%	Not measured	Only Gemini 3.8 Flash measured
FrontierSWE	19.6%	Not measured	Only Gemini 3.8 Flash measured
WeirdML	84.8%	Not measured	Only Gemini 3.8 Flash measured
ALE-Bench	1269.7	340.8	Gemini 3.8 Flash
LMArena Text: coding	1508	1449	Gemini 3.8 Flash
LMArena Text: software and IT	1507	1455	Gemini 3.8 Flash
LMArena WebDev: React	1577	Not measured	Only Gemini 3.8 Flash measured
LMArena WebDev: HTML	1616	1350	Gemini 3.8 Flash
LMArena WebDev: from an image	1593	Not measured	Only Gemini 3.8 Flash measured
SciCode	12.3%	Not measured	Only Gemini 3.8 Flash measured
Neither model has a result on the other 9 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10

Intelligence benchmarks for Gemini 3.8 Flash and GLM 4.6
Benchmark	Gemini 3.8 Flash	GLM 4.6	Leader
AA Intelligence Index	40.9	18.5	Gemini 3.8 Flash
Epoch Capabilities Index	157.4	Not measured	Only Gemini 3.8 Flash measured

Agentic workLike-for-likePublic boards, shown as published, kept out of the index31

Agentic work benchmarks for Gemini 3.8 Flash and GLM 4.6
Benchmark	Gemini 3.8 Flash	GLM 4.6	Leader
AA Agentic Index	40.2	Not measured	Only Gemini 3.8 Flash measured
Design Arena: agents building web apps	1238	Not measured	Only Gemini 3.8 Flash measured
Design Arena: agents building full-stack apps	1244	1029	Gemini 3.8 Flash
Design Arena: agents building mobile apps	1236	1096	Gemini 3.8 Flash
Design Arena: agents building Android apps	1078	1084	GLM 4.6
Design Arena: agents building Godot games	1273	1180	Gemini 3.8 Flash
Design Arena: PowerPoint slides	1153	Not measured	Only Gemini 3.8 Flash measured
Design Arena: spreadsheets	1022	Not measured	Only Gemini 3.8 Flash measured
LiveBench research	79.1%	Not measured	Only Gemini 3.8 Flash measured
LiveBench browser	64.0%	Not measured	Only Gemini 3.8 Flash measured
LiveBench long agentic	30.1%	Not measured	Only Gemini 3.8 Flash measured
SREBench (Vals AI)	11.1%	Not measured	Only Gemini 3.8 Flash measured
Finance Agent (Vals AI)	61.4%	Not measured	Only Gemini 3.8 Flash measured
Tax Agent Bench (Vals AI)	32.1%	Not measured	Only Gemini 3.8 Flash measured
Legal Research Bench (Vals AI)	38.9%	Not measured	Only Gemini 3.8 Flash measured
Harvey's Legal Agent Benchmark (Vals AI)	12.1%	Not measured	Only Gemini 3.8 Flash measured
Excel Modeling Benchmark (Vals AI)	72.2%	Not measured	Only Gemini 3.8 Flash measured
BioMysteryBench (Vals AI)	62.2%	Not measured	Only Gemini 3.8 Flash measured
Terminal-Bench-Science (Vals AI)	8.6%	Not measured	Only Gemini 3.8 Flash measured
Vals Science Index	35.8%	Not measured	Only Gemini 3.8 Flash measured
Time Horizon Index (Vals AI)	18.8%	Not measured	Only Gemini 3.8 Flash measured
CUA-bench (Vals AI)	4.2%	Not measured	Only Gemini 3.8 Flash measured
τ²-Bench Telecom	Not measured	76.9%	Only GLM 4.6 measured
APEX-Agents	64.3%	Not measured	Only Gemini 3.8 Flash measured
Remote Labor Index	5.8%	Not measured	Only Gemini 3.8 Flash measured
Vending-Bench 2	$5,094	Not measured	Only Gemini 3.8 Flash measured
Berkeley Function Calling Leaderboard (BFCL)	Not measured	72.4%	Only GLM 4.6 measured
BrowseComp-Plus	Not measured	48.2%	Only GLM 4.6 measured
Neither model has a result on the other 13 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index60

Reasoning benchmarks for Gemini 3.8 Flash and GLM 4.6
Benchmark	Gemini 3.8 Flash	GLM 4.6	Leader
GPQA Diamond	94.4%	74.5%	Gemini 3.8 Flash
LiveBench reasoning	89.3%	Not measured	Only Gemini 3.8 Flash measured
MysteryMechanism (Vals AI)	36.5%	Not measured	Only Gemini 3.8 Flash measured
MMMU Pro (Vals AI)	89.1%	Not measured	Only Gemini 3.8 Flash measured
GPQA Diamond (Artificial Analysis run)	95.3%	78.0%	Gemini 3.8 Flash
Humanity's Last Exam (Artificial Analysis run)	47.8%	14.5%	Gemini 3.8 Flash
GPQA Diamond (Epoch AI run)	95.4%	Not measured	Only Gemini 3.8 Flash measured
ARC-AGI	98.5%	Not measured	Only Gemini 3.8 Flash measured
ARC-AGI-2	89.2%	Not measured	Only Gemini 3.8 Flash measured
Chess puzzles	58.0%	Not measured	Only Gemini 3.8 Flash measured
Mystery game puzzles	47.0%	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: hard prompts	1509	1440	Gemini 3.8 Flash
LMArena Text: expert	1526	1432	Gemini 3.8 Flash
LMArena Text: hard prompts in English	1504	1445	Gemini 3.8 Flash
LMArena Vision: diagrams	1345	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: homework	1351	Not measured	Only Gemini 3.8 Flash measured
Kagi LLM Benchmark	Not measured	45.7%	Only GLM 4.6 measured
Neither model has a result on the other 5 boards here

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

Math benchmarks for Gemini 3.8 Flash and GLM 4.6
Benchmark	Gemini 3.8 Flash	GLM 4.6	Leader
AIME	Not measured	92.7%	Only GLM 4.6 measured
MGSM (Vals AI)	Not measured	89.8%	Only GLM 4.6 measured
AA Math Index	Not measured	86.0	Only GLM 4.6 measured
AIME 2025 (Artificial Analysis run)	Not measured	86.0%	Only GLM 4.6 measured
OTIS Mock AIME	98.9%	Not measured	Only Gemini 3.8 Flash measured
FrontierMath, tiers 1 to 3	68.4%	Not measured	Only Gemini 3.8 Flash measured
FrontierMath, tier 4	22.0%	Not measured	Only Gemini 3.8 Flash measured
ProofBench	48.0%	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: math	1532	1432	Gemini 3.8 Flash
LMArena Text: mathematical work	1519	1447	Gemini 3.8 Flash
Neither model has a result on the other 3 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index70

Knowledge benchmarks for Gemini 3.8 Flash and GLM 4.6
Benchmark	Gemini 3.8 Flash	GLM 4.6	Leader
MMLU Pro	90.2%	82.2%	Gemini 3.8 Flash
LegalBench (Vals AI)	87.0%	79.6%	Gemini 3.8 Flash
CorpFin (Vals AI)	Not measured	56.8%	Only GLM 4.6 measured
TaxEval (Vals AI)	74.5%	66.2%	Gemini 3.8 Flash
MortgageTax (Vals AI)	65.3%	Not measured	Only Gemini 3.8 Flash measured
MedQA (Vals AI)	Not measured	92.2%	Only GLM 4.6 measured
MedCode (Vals AI)	48.1%	Not measured	Only Gemini 3.8 Flash measured
MMLU Pro (Artificial Analysis run)	Not measured	82.9%	Only GLM 4.6 measured
SimpleQA Verified	69.7%	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: science	1523	1456	Gemini 3.8 Flash
LMArena Text: medicine and healthcare	1508	1455	Gemini 3.8 Flash
LMArena Text: legal and government	1497	1448	Gemini 3.8 Flash
LMArena Text: business and finance	1479	1416	Gemini 3.8 Flash
FACTS Benchmark Suite	69.4%	Not measured	Only Gemini 3.8 Flash measured
Neither model has a result on the other 4 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index70

Web design benchmarks for Gemini 3.8 Flash and GLM 4.6
Benchmark	Gemini 3.8 Flash	GLM 4.6	Leader
Design Arena: websites	1300	1174	Gemini 3.8 Flash
Design Arena: UI components	1316	1145	Gemini 3.8 Flash
Design Arena: game dev	1304	1150	Gemini 3.8 Flash
Design Arena: data viz	1270	1161	Gemini 3.8 Flash
Design Arena: 3D	1294	1128	Gemini 3.8 Flash
Design Arena: all code categories	1303	1165	Gemini 3.8 Flash
Design Arena: SVG	1296	1108	Gemini 3.8 Flash
Design Arena: ASCII art	1262	Not measured	Only Gemini 3.8 Flash measured
LiveBench design	72.7%	Not measured	Only Gemini 3.8 Flash measured

GeneralLike-for-likePublic boards, shown as published, kept out of the index180

General benchmarks for Gemini 3.8 Flash and GLM 4.6
Benchmark	Gemini 3.8 Flash	GLM 4.6	Leader
Vals Index	56.0%	Not measured	Only Gemini 3.8 Flash measured
LiveBench data analysis	54.0%	Not measured	Only Gemini 3.8 Flash measured
Public Benefits Bench (Vals AI)	65.3%	Not measured	Only Gemini 3.8 Flash measured
SAGE (Vals AI)	35.1%	Not measured	Only Gemini 3.8 Flash measured
MedScribe (Vals AI)	84.5%	Not measured	Only Gemini 3.8 Flash measured
IFBench	Not measured	43.4%	Only GLM 4.6 measured
Long context reasoning (AA-LCR)	84.0%	54.0%	Gemini 3.8 Flash
DTBench	95.7%	Not measured	Only Gemini 3.8 Flash measured
LMCA	52.9%	Not measured	Only Gemini 3.8 Flash measured
Surface Evolver Bench	76.9%	Not measured	Only Gemini 3.8 Flash measured
Furniture assembly	31.7%	Not measured	Only Gemini 3.8 Flash measured
LMArena Text	1499	1440	Gemini 3.8 Flash
LMArena Text: instruction following	1492	1410	Gemini 3.8 Flash
LMArena Text: creative writing	1488	1412	Gemini 3.8 Flash
LMArena Vision	1315	Not measured	Only Gemini 3.8 Flash measured
LMArena Text: English	1498	1449	Gemini 3.8 Flash
LMArena Text: non-English	1491	1426	Gemini 3.8 Flash
LMArena Text: Chinese	1553	1499	Gemini 3.8 Flash
LMArena Text: German	1501	1447	Gemini 3.8 Flash
LMArena Text: Japanese	1507	1393	Gemini 3.8 Flash
LMArena Text: Korean	1464	1400	Gemini 3.8 Flash
LMArena Text: French	1496	1459	Gemini 3.8 Flash
LMArena Text: Spanish	1487	1436	Gemini 3.8 Flash
LMArena Text: Russian	1514	1418	Gemini 3.8 Flash
LMArena Text: Polish	1497	1447	Gemini 3.8 Flash
LMArena Text: multi-turn	1503	1427	Gemini 3.8 Flash
LMArena Text: longer queries	1507	1422	Gemini 3.8 Flash
LMArena Text: writing and language	1494	1415	Gemini 3.8 Flash
LMArena Text: entertainment and media	1480	1409	Gemini 3.8 Flash
LMArena Vision: English	1318	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: Chinese	1416	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: reading text	1333	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: humor	1321	Not measured	Only Gemini 3.8 Flash measured
LMArena Vision: creative writing	1299	Not measured	Only Gemini 3.8 Flash measured
Neither model has a result on the other 12 boards here

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

Image generation benchmarks for Gemini 3.8 Flash and GLM 4.6
Benchmark	Gemini 3.8 Flash	GLM 4.6	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 3.8 Flash$0.0026Fits in one request

GLM 4.6$0.0017Fits in one request

GLM 4.6 costs less

Repository review

50K input + 3K output tokens

Gemini 3.8 Flash$0.049Fits in one request

GLM 4.6$0.037Fits in one request

GLM 4.6 costs less

Agent loop

200K input + 10K output tokens

Gemini 3.8 Flash$0.188Fits in one request

GLM 4.6$0.142Exceeds the context window

GLM 4.6 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 3.8 Flash and GLM 4.6
Specification	Google Gemini 3.8 Flash	Z.ai GLM 4.6
Maker	Google	Z.ai
Weights	No public weights listed	Open weights
Released	September 2, 2026	September 30, 2025
Context window	1.05M	205K
Input $/Mtok	$0.75	$0.60
Output $/Mtok	$3.75	$2.20
Coding index	61.6	8.8
Independent measurements behind it	6	2
Cost per solved task	$2.74	Not computable
Source	OpenRouter listing	OpenRouter listing

Questions

Is Gemini 3.8 Flash better than GLM 4.6 for coding?

Pick Gemini 3.8 Flash for coding: it scores 61.6 on the Vibe Coding Index against 8.8 for GLM 4.6. Pick GLM 4.6 for output tokens 1.7x cheaper ($2.20 vs $3.75 per million) and work measured by Design Arena: agents building Android apps, where it leads.

Which is cheaper, Gemini 3.8 Flash or GLM 4.6?

Gemini 3.8 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; GLM 4.6 costs $0.60 and $2.20. Cost per solved task is known for Gemini 3.8 Flash only.

Which has the bigger context window, Gemini 3.8 Flash or GLM 4.6?

Gemini 3.8 Flash, with 1.05M tokens against 205K.

How many benchmarks is the Gemini 3.8 Flash vs GLM 4.6 comparison based on?

53 benchmarks have a result for both models as of October 22, 2026. Gemini 3.8 Flash's coding index rests on 6 independent benchmarks and GLM 4.6's on 2. Where only one model has a result, the page says so instead of naming a winner.

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Gemini 3.8 Flash or GLM 4.6: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Math

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