Enter opens the highlighted result. Esc closes.

Gemini 3.8 Flash vs GLM 5.3

GLM 5.3 leads Gemini 3.8 Flash on coding, 70.6 to 61.6 on the Vibe Coding Index, at about the same output price ($4.40 vs $3.75 per million). Updated October 22, 2026; 99 benchmarks have a result for both.

Replace Gemini 3.8 Flash Replace GLM 5.3
Gemini 3.8 FlashGoogle
Coding
61.6
Overall
69.0
Output $/M
$3.75
65
GLM 5.3Z.ai
Coding
70.6
Overall
67.9
Output $/M
$4.40
34
vs boards won of 99 shared

Gemini 3.8 Flash or GLM 5.3: which to pick

Pick GLM 5.3 for coding: it scores 70.6 on the Vibe Coding Index against 61.6 for Gemini 3.8 Flash.

Pick Gemini 3.8 Flash for output tokens 1.2x cheaper ($3.75 vs $4.40 per million) and work measured by AA Coding Index or LiveCodeBench (Vals AI), where it leads.

Model AGemini 3.8 FlashGoogle61.6/1006 independent benchmarks$2.74 per solved taskModel BGLM 5.3Z.ai70.6/1006 independent benchmarks$0.36 per solved task
Shared results
99
Gemini 3.8 Flash only
29
GLM 5.3 only
1
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.

At a glance

Coding index
Gemini 3.8 Flash 61.6 from 6 benchmarks, GLM 5.3 70.6 from 6 benchmarks.
Widest category
Agentic work, 11.8 points apart on average over 15 shared benchmarks.
Widest single gap
LiveBench browser: Gemini 3.8 Flash 64.0% against GLM 5.3 0.0%, 64.0 points apart on a 0 to 100 scale.
Output price
Gemini 3.8 Flash $3.75 against GLM 5.3 $4.40 per million output tokens, 1.2x 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
CategoryGemini 3.8 FlashBarsGLM 5.3Ties
Coding1013
Intelligence11
Agentic work87
Reasoning110
Math33
Knowledge90
Web design54
General186
All shared boards6534
CodingLike-for-likeSix of these boards feed the Vibe Coding Index1013
Coding benchmarks for Gemini 3.8 Flash and GLM 5.3
BenchmarkGemini 3.8 FlashGLM 5.3Leader
LiveBench coding82.2%82.8%GLM 5.3
LMArena WebDev15851621GLM 5.3
AA Coding Index76.374.8Gemini 3.8 Flash
LiveCodeBench (Vals AI)89.5%80.5%Gemini 3.8 Flash
SWE-bench Verified (Vals AI)80.0%95.4%GLM 5.3
Terminal-Bench 4 (Vals AI)19.7%38.9%GLM 5.3
Vibe Code Bench (Vals AI)78.7%78.1%Gemini 3.8 Flash
Code migration (Vals AI)36.5%44.2%GLM 5.3
ProgramBench (Vals AI)1.0%1.5%GLM 5.3
IOI (Vals AI)56.9%68.4%GLM 5.3
Terminal-Bench 2.1 (Vals AI)81.3%71.5%Gemini 3.8 Flash
SWE-bench Multimodal (Vals AI)40.8%Not measuredOnly Gemini 3.8 Flash measured
Vibe Code Bench 1-100 (Vals AI)18.8%20.0%GLM 5.3
SkillsBench (Vals AI)58.0%47.5%Gemini 3.8 Flash
CyberBench (Vals AI)43.8%72.1%GLM 5.3
SciCode56.6%59.0%GLM 5.3
FrontierCode41.2%40.1%Gemini 3.8 Flash
FrontierSWE19.6%30.2%GLM 5.3
WeirdML84.8%75.4%Gemini 3.8 Flash
ALE-Bench1269.71317.4GLM 5.3
LMArena Text: coding15081497Gemini 3.8 Flash
LMArena Text: software and IT15071493Gemini 3.8 Flash
LMArena WebDev: React15771641GLM 5.3
LMArena WebDev: HTML16161595Gemini 3.8 Flash
LMArena WebDev: from an image1593Not measuredOnly Gemini 3.8 Flash measured
SciCode12.3%Not measuredOnly Gemini 3.8 Flash measured
Neither model has a result on the other 13 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for Gemini 3.8 Flash and GLM 5.3
BenchmarkGemini 3.8 FlashGLM 5.3Leader
AA Intelligence Index40.944.8GLM 5.3
Epoch Capabilities Index157.4156.0Gemini 3.8 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index87
Agentic work benchmarks for Gemini 3.8 Flash and GLM 5.3
BenchmarkGemini 3.8 FlashGLM 5.3Leader
AA Agentic Index40.253.1GLM 5.3
Design Arena: agents building web apps1238Not measuredOnly Gemini 3.8 Flash measured
Design Arena: agents building full-stack apps1244Not measuredOnly Gemini 3.8 Flash measured
Design Arena: agents building mobile apps12361194Gemini 3.8 Flash
Design Arena: agents building Android apps1078Not measuredOnly Gemini 3.8 Flash measured
Design Arena: agents building Godot games1273Not measuredOnly Gemini 3.8 Flash measured
Design Arena: HTML slidesNot measured1189Only GLM 5.3 measured
Design Arena: PowerPoint slides11531230GLM 5.3
Design Arena: spreadsheets1022Not measuredOnly Gemini 3.8 Flash measured
LiveBench research79.1%73.2%Gemini 3.8 Flash
LiveBench browser64.0%0.0%Gemini 3.8 Flash
LiveBench long agentic30.1%35.9%GLM 5.3
SREBench (Vals AI)11.1%9.2%Gemini 3.8 Flash
Finance Agent (Vals AI)61.4%55.8%Gemini 3.8 Flash
Tax Agent Bench (Vals AI)32.1%39.7%GLM 5.3
Legal Research Bench (Vals AI)38.9%49.0%GLM 5.3
Harvey's Legal Agent Benchmark (Vals AI)12.1%14.6%GLM 5.3
Excel Modeling Benchmark (Vals AI)72.2%56.3%Gemini 3.8 Flash
BioMysteryBench (Vals AI)62.2%Not measuredOnly Gemini 3.8 Flash measured
Terminal-Bench-Science (Vals AI)8.6%5.7%Gemini 3.8 Flash
Vals Science Index35.8%Not measuredOnly Gemini 3.8 Flash measured
Time Horizon Index (Vals AI)18.8%Not measuredOnly Gemini 3.8 Flash measured
CUA-bench (Vals AI)4.2%Not measuredOnly Gemini 3.8 Flash measured
APEX-Agents64.3%56.6%Gemini 3.8 Flash
Remote Labor Index5.8%Not measuredOnly Gemini 3.8 Flash measured
Vending-Bench 2$5,094$8,164GLM 5.3
Neither model has a result on the other 15 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index110
Reasoning benchmarks for Gemini 3.8 Flash and GLM 5.3
BenchmarkGemini 3.8 FlashGLM 5.3Leader
GPQA Diamond94.4%88.1%Gemini 3.8 Flash
LiveBench reasoning89.3%85.8%Gemini 3.8 Flash
MysteryMechanism (Vals AI)36.5%23.0%Gemini 3.8 Flash
MMMU Pro (Vals AI)89.1%Not measuredOnly Gemini 3.8 Flash measured
GPQA Diamond (Artificial Analysis run)95.3%91.7%Gemini 3.8 Flash
Humanity's Last Exam (Artificial Analysis run)47.8%42.3%Gemini 3.8 Flash
GPQA Diamond (Epoch AI run)95.4%90.9%Gemini 3.8 Flash
ARC-AGI98.5%Not measuredOnly Gemini 3.8 Flash measured
ARC-AGI-289.2%Not measuredOnly Gemini 3.8 Flash measured
Chess puzzles58.0%37.0%Gemini 3.8 Flash
Mystery game puzzles47.0%33.0%Gemini 3.8 Flash
LMArena Text: hard prompts15091490Gemini 3.8 Flash
LMArena Text: expert15261514Gemini 3.8 Flash
LMArena Text: hard prompts in English15041496Gemini 3.8 Flash
LMArena Vision: diagrams1345Not measuredOnly Gemini 3.8 Flash measured
LMArena Vision: homework1351Not measuredOnly Gemini 3.8 Flash measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index33
Math benchmarks for Gemini 3.8 Flash and GLM 5.3
BenchmarkGemini 3.8 FlashGLM 5.3Leader
OTIS Mock AIME98.9%91.1%Gemini 3.8 Flash
FrontierMath, tiers 1 to 368.4%68.8%GLM 5.3
FrontierMath, tier 422.0%29.3%GLM 5.3
ProofBench48.0%49.0%GLM 5.3
LMArena Text: math15321495Gemini 3.8 Flash
LMArena Text: mathematical work15191497Gemini 3.8 Flash
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index90
Knowledge benchmarks for Gemini 3.8 Flash and GLM 5.3
BenchmarkGemini 3.8 FlashGLM 5.3Leader
MMLU Pro90.2%86.8%Gemini 3.8 Flash
LegalBench (Vals AI)87.0%84.8%Gemini 3.8 Flash
TaxEval (Vals AI)74.5%72.4%Gemini 3.8 Flash
MortgageTax (Vals AI)65.3%Not measuredOnly Gemini 3.8 Flash measured
MedCode (Vals AI)48.1%42.9%Gemini 3.8 Flash
SimpleQA Verified69.7%41.0%Gemini 3.8 Flash
LMArena Text: science15231498Gemini 3.8 Flash
LMArena Text: medicine and healthcare15081481Gemini 3.8 Flash
LMArena Text: legal and government14971473Gemini 3.8 Flash
LMArena Text: business and finance14791459Gemini 3.8 Flash
FACTS Benchmark Suite69.4%Not measuredOnly Gemini 3.8 Flash measured
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index54
Web design benchmarks for Gemini 3.8 Flash and GLM 5.3
BenchmarkGemini 3.8 FlashGLM 5.3Leader
Design Arena: websites13001295Gemini 3.8 Flash
Design Arena: UI components13161314Gemini 3.8 Flash
Design Arena: game dev13041311GLM 5.3
Design Arena: data viz12701260Gemini 3.8 Flash
Design Arena: 3D12941332GLM 5.3
Design Arena: all code categories13031304GLM 5.3
Design Arena: SVG12961294Gemini 3.8 Flash
Design Arena: ASCII art12621208Gemini 3.8 Flash
LiveBench design72.7%77.3%GLM 5.3
GeneralLike-for-likePublic boards, shown as published, kept out of the index186
General benchmarks for Gemini 3.8 Flash and GLM 5.3
BenchmarkGemini 3.8 FlashGLM 5.3Leader
Vals Index56.0%59.7%GLM 5.3
LiveBench data analysis54.0%70.2%GLM 5.3
Public Benefits Bench (Vals AI)65.3%68.5%GLM 5.3
SAGE (Vals AI)35.1%Not measuredOnly Gemini 3.8 Flash measured
MedScribe (Vals AI)84.5%88.8%GLM 5.3
Long context reasoning (AA-LCR)84.0%79.7%Gemini 3.8 Flash
DTBench95.7%87.7%Gemini 3.8 Flash
LMCA52.9%55.5%GLM 5.3
Surface Evolver Bench76.9%Not measuredOnly Gemini 3.8 Flash measured
Furniture assembly31.7%Not measuredOnly Gemini 3.8 Flash measured
LMArena Text14991474Gemini 3.8 Flash
LMArena Text: instruction following14921479Gemini 3.8 Flash
LMArena Text: creative writing14881458Gemini 3.8 Flash
LMArena Vision1315Not measuredOnly Gemini 3.8 Flash measured
LMArena Text: English14981482Gemini 3.8 Flash
LMArena Text: non-English14911459Gemini 3.8 Flash
LMArena Text: Chinese15531532Gemini 3.8 Flash
LMArena Text: German15011488Gemini 3.8 Flash
LMArena Text: Japanese15071460Gemini 3.8 Flash
LMArena Text: Korean14641460Gemini 3.8 Flash
LMArena Text: French14961503GLM 5.3
LMArena Text: Spanish14871462Gemini 3.8 Flash
LMArena Text: Russian15141469Gemini 3.8 Flash
LMArena Text: Polish14971466Gemini 3.8 Flash
LMArena Text: multi-turn15031472Gemini 3.8 Flash
LMArena Text: longer queries15071483Gemini 3.8 Flash
LMArena Text: writing and language14941469Gemini 3.8 Flash
LMArena Text: entertainment and media14801447Gemini 3.8 Flash
LMArena Vision: English1318Not measuredOnly Gemini 3.8 Flash measured
LMArena Vision: Chinese1416Not measuredOnly Gemini 3.8 Flash measured
LMArena Vision: reading text1333Not measuredOnly Gemini 3.8 Flash measured
LMArena Vision: humor1321Not measuredOnly Gemini 3.8 Flash measured
LMArena Vision: creative writing1299Not measuredOnly Gemini 3.8 Flash measured
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 Gemini 3.8 Flash and GLM 5.3
BenchmarkGemini 3.8 FlashGLM 5.3Leader
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 5.3$0.0036Fits in one request

Gemini 3.8 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 3.8 Flash$0.049Fits in one request
GLM 5.3$0.083Fits in one request

Gemini 3.8 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 3.8 Flash$0.188Fits in one request
GLM 5.3$0.324Fits in one request

Gemini 3.8 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 3.8 Flash and GLM 5.3
SpecificationGoogle Gemini 3.8 FlashZ.ai GLM 5.3
MakerGoogleZ.ai
WeightsNo public weights listedOpen weights
ReleasedSeptember 2, 2026August 18, 2026
Context window1.05M1.05M
Input $/Mtok$0.75$1.40
Output $/Mtok$3.75$4.40
Coding index61.670.6
Independent measurements behind it66
Cost per solved task$2.74$0.36
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.8 Flash better than GLM 5.3 for coding?

Pick GLM 5.3 for coding: it scores 70.6 on the Vibe Coding Index against 61.6 for Gemini 3.8 Flash. Pick Gemini 3.8 Flash for output tokens 1.2x cheaper ($3.75 vs $4.40 per million) and work measured by AA Coding Index or LiveCodeBench (Vals AI), where it leads.

Which is cheaper, Gemini 3.8 Flash or GLM 5.3?

Gemini 3.8 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; GLM 5.3 costs $1.40 and $4.40. Per solved SWE-bench Verified task, Gemini 3.8 Flash costs $2.74 and GLM 5.3 $0.36.

Which has the bigger context window, Gemini 3.8 Flash or GLM 5.3?

Neither: both take 1.05M tokens.

How many benchmarks is the Gemini 3.8 Flash vs GLM 5.3 comparison based on?

99 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 5.3's on 6. Where only one model has a result, the page says so instead of naming a winner.

Compare next

Embed this comparison on your site

Free under CC BY 4.0, while the source link stays visible. Preview the frame · Terms and other embeds

<iframe src="https://llmbenchmark.ai/embed/compare/gemini-3-8-flash-vs-glm-5-3" title="Gemini 3.8 Flash vs GLM 5.3, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/gemini-3-8-flash-vs-glm-5-3">LLMBenchmark.ai, Gemini 3.8 Flash vs GLM 5.3</a></p>