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GLM 5.3 Flash vs Grok 4.7

Grok 4.7 leads GLM 5.3 Flash on coding, 66.7 to 57.7 on the Vibe Coding Index, and GLM 5.3 Flash costs 12.0x less per output token ($0.50 vs $6.00 per million). Updated October 22, 2026; 86 benchmarks have a result for both.

Replace GLM 5.3 Flash Replace Grok 4.7
GLM 5.3 FlashZ.ai
Coding
57.7
Overall
66.0
Output $/M
$0.50
46
Grok 4.7xAI
Coding
66.7
Overall
66.6
Output $/M
$6.00
38
vs boards won of 86 shared, 2 tied

GLM 5.3 Flash or Grok 4.7: which to pick

Pick Grok 4.7 for coding: it scores 66.7 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 12.0x cheaper ($0.50 vs $6.00 per million) and a larger context window (1.05M against 500K tokens).

Model AGLM 5.3 FlashZ.ai57.7/1006 independent benchmarks$0.02 per solved taskModel BGrok 4.7xAI66.7/1005 independent benchmarksNo cost per solved task
Shared results
86
GLM 5.3 Flash only
16
Grok 4.7 only
13
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
GLM 5.3 Flash 57.7 from 6 benchmarks, Grok 4.7 66.7 from 5 benchmarks.
Widest category
Coding, 11.2 points apart on average over 17 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): GLM 5.3 Flash 30.8% against Grok 4.7 86.2%, 55.4 points apart on a 0 to 100 scale.
Output price
GLM 5.3 Flash $0.50 against Grok 4.7 $6.00 per million output tokens, 12.0x apart.
Context window
GLM 5.3 Flash takes 1.05M tokens, Grok 4.7 500K.

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
CategoryGLM 5.3 FlashBarsGrok 4.7Ties
Coding314
Intelligence02
Agentic work29
Reasoning75
Math321 tie
Knowledge41
Web design52
General2231 tie
All shared boards46382 ties
CodingLike-for-likeSix of these boards feed the Vibe Coding Index314
Coding benchmarks for GLM 5.3 Flash and Grok 4.7
BenchmarkGLM 5.3 FlashGrok 4.7Leader
LiveBench coding80.6%84.5%Grok 4.7
LMArena WebDev16071637Grok 4.7
AA Coding Index71.5Not measuredOnly GLM 5.3 Flash measured
LiveCodeBench (Vals AI)80.5%Not measuredOnly GLM 5.3 Flash measured
SWE-bench Verified (Vals AI)92.0%Not measuredOnly GLM 5.3 Flash measured
Terminal-Bench 4 (Vals AI)37.4%28.8%GLM 5.3 Flash
Vibe Code Bench (Vals AI)30.8%86.2%Grok 4.7
Code migration (Vals AI)20.5%44.8%Grok 4.7
ProgramBench (Vals AI)0.0%0.5%Grok 4.7
IOI (Vals AI)52.5%57.7%Grok 4.7
Terminal-Bench 2.1 (Vals AI)62.9%73.4%Grok 4.7
SWE-bench Multimodal (Vals AI)Not measured42.9%Only Grok 4.7 measured
Vibe Code Bench 1-100 (Vals AI)16.0%Not measuredOnly GLM 5.3 Flash measured
SkillsBench (Vals AI)40.2%Not measuredOnly GLM 5.3 Flash measured
CyberBench (Vals AI)67.9%69.5%Grok 4.7
SciCode51.6%57.8%Grok 4.7
FrontierCode31.8%47.6%Grok 4.7
FrontierSWE18.1%29.5%Grok 4.7
ALE-Bench303.6Not measuredOnly GLM 5.3 Flash measured
LMArena Text: coding15071432GLM 5.3 Flash
LMArena Text: software and IT15001421GLM 5.3 Flash
LMArena WebDev: React16241663Grok 4.7
LMArena WebDev: HTML15771627Grok 4.7
LMArena WebDev: from an image15781586Grok 4.7
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GLM 5.3 Flash and Grok 4.7
BenchmarkGLM 5.3 FlashGrok 4.7Leader
AA Intelligence Index41.846.4Grok 4.7
Epoch Capabilities Index153.1154.4Grok 4.7
Agentic workLike-for-likePublic boards, shown as published, kept out of the index29
Agentic work benchmarks for GLM 5.3 Flash and Grok 4.7
BenchmarkGLM 5.3 FlashGrok 4.7Leader
AA Agentic Index50.9Not measuredOnly GLM 5.3 Flash measured
LiveBench research70.1%86.4%Grok 4.7
LiveBench browser84.0%60.0%GLM 5.3 Flash
LiveBench long agentic28.4%50.1%Grok 4.7
SREBench (Vals AI)0.8%3.8%Grok 4.7
Finance Agent (Vals AI)57.9%52.3%GLM 5.3 Flash
Tax Agent Bench (Vals AI)31.6%34.2%Grok 4.7
Legal Research Bench (Vals AI)45.2%47.1%Grok 4.7
Harvey's Legal Agent Benchmark (Vals AI)10.4%18.3%Grok 4.7
Excel Modeling Benchmark (Vals AI)55.9%67.0%Grok 4.7
BioMysteryBench (Vals AI)Not measured69.3%Only Grok 4.7 measured
Terminal-Bench-Science (Vals AI)2.9%10.0%Grok 4.7
Vals Science IndexNot measured34.8%Only Grok 4.7 measured
Robo-bench (Vals AI)Not measured0.2%Only Grok 4.7 measured
APEX-Agents52.8%54.6%Grok 4.7
Vending-Bench 2Not measured$10,537Only Grok 4.7 measured
Neither model has a result on the other 25 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index75
Reasoning benchmarks for GLM 5.3 Flash and Grok 4.7
BenchmarkGLM 5.3 FlashGrok 4.7Leader
GPQA Diamond86.4%Not measuredOnly GLM 5.3 Flash measured
LiveBench reasoning77.6%82.7%Grok 4.7
MysteryMechanism (Vals AI)Not measured25.2%Only Grok 4.7 measured
MMMU Pro (Vals AI)86.0%Not measuredOnly GLM 5.3 Flash measured
GPQA Diamond (Artificial Analysis run)91.2%Not measuredOnly GLM 5.3 Flash measured
Humanity's Last Exam (Artificial Analysis run)39.9%43.1%Grok 4.7
GPQA Diamond (Epoch AI run)90.2%92.7%Grok 4.7
ARC-AGI91.0%90.2%GLM 5.3 Flash
ARC-AGI-265.8%61.4%GLM 5.3 Flash
Chess puzzles21.0%41.0%Grok 4.7
Mystery game puzzles8.0%29.0%Grok 4.7
LMArena Text: hard prompts14901415GLM 5.3 Flash
LMArena Text: expert15111439GLM 5.3 Flash
LMArena Text: hard prompts in English14881427GLM 5.3 Flash
LMArena Vision: diagrams13171254GLM 5.3 Flash
LMArena Vision: homework13181309GLM 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 index32
Math benchmarks for GLM 5.3 Flash and Grok 4.7
BenchmarkGLM 5.3 FlashGrok 4.7Leader
OTIS Mock AIME93.9%98.1%Grok 4.7
FrontierMath, tiers 1 to 355.8%53.0%GLM 5.3 Flash
FrontierMath, tier 417.1%17.1%Tie
ProofBench21.0%26.0%Grok 4.7
LMArena Text: math15031414GLM 5.3 Flash
LMArena Text: mathematical work14971435GLM 5.3 Flash
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
Knowledge benchmarks for GLM 5.3 Flash and Grok 4.7
BenchmarkGLM 5.3 FlashGrok 4.7Leader
MMLU Pro86.1%Not measuredOnly GLM 5.3 Flash measured
LegalBench (Vals AI)83.9%84.4%Grok 4.7
TaxEval (Vals AI)75.6%Not measuredOnly GLM 5.3 Flash measured
MedCode (Vals AI)Not measured49.5%Only Grok 4.7 measured
SimpleQA VerifiedNot measured56.0%Only Grok 4.7 measured
LMArena Text: science14841419GLM 5.3 Flash
LMArena Text: medicine and healthcare14751395GLM 5.3 Flash
LMArena Text: legal and government14731423GLM 5.3 Flash
LMArena Text: business and finance14601389GLM 5.3 Flash
Neither model has a result on the other 9 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index52
Web design benchmarks for GLM 5.3 Flash and Grok 4.7
BenchmarkGLM 5.3 FlashGrok 4.7Leader
Design Arena: websites12721255GLM 5.3 Flash
Design Arena: UI components13161275GLM 5.3 Flash
Design Arena: game dev12781314Grok 4.7
Design Arena: data viz12621238GLM 5.3 Flash
Design Arena: 3D13161274GLM 5.3 Flash
Design Arena: all code categories12821273GLM 5.3 Flash
Design Arena: SVG1285Not measuredOnly GLM 5.3 Flash measured
Design Arena: ASCII art1267Not measuredOnly GLM 5.3 Flash measured
LiveBench design77.2%78.0%Grok 4.7
GeneralLike-for-likePublic boards, shown as published, kept out of the index223
General benchmarks for GLM 5.3 Flash and Grok 4.7
BenchmarkGLM 5.3 FlashGrok 4.7Leader
Vals Index50.9%58.6%Grok 4.7
LiveBench data analysis76.4%76.9%Grok 4.7
Public Benefits Bench (Vals AI)Not measured65.6%Only Grok 4.7 measured
SAGE (Vals AI)Not measured40.8%Only Grok 4.7 measured
MedScribe (Vals AI)88.9%89.4%Grok 4.7
Long context reasoning (AA-LCR)80.0%80.0%Tie
DTBenchNot measured96.0%Only Grok 4.7 measured
LMCANot measured49.4%Only Grok 4.7 measured
Surface Evolver Bench52.5%Not measuredOnly GLM 5.3 Flash measured
Furniture assemblyNot measured20.8%Only Grok 4.7 measured
LMArena Text14711399GLM 5.3 Flash
LMArena Text: instruction following14781406GLM 5.3 Flash
LMArena Text: creative writing14411381GLM 5.3 Flash
LMArena Vision12941231GLM 5.3 Flash
LMArena Text: English14741411GLM 5.3 Flash
LMArena Text: non-English14621386GLM 5.3 Flash
LMArena Text: Chinese15311449GLM 5.3 Flash
LMArena Text: German14621366GLM 5.3 Flash
LMArena Text: Japanese14441359GLM 5.3 Flash
LMArena Text: Korean14361383GLM 5.3 Flash
LMArena Text: French14911431GLM 5.3 Flash
LMArena Text: Spanish14751406GLM 5.3 Flash
LMArena Text: Russian14651399GLM 5.3 Flash
LMArena Text: Polish14501420GLM 5.3 Flash
LMArena Text: multi-turn14691394GLM 5.3 Flash
LMArena Text: longer queries14811416GLM 5.3 Flash
LMArena Text: writing and language14551394GLM 5.3 Flash
LMArena Text: entertainment and media14401376GLM 5.3 Flash
LMArena Vision: English12951229GLM 5.3 Flash
LMArena Vision: Chinese13631250GLM 5.3 Flash
LMArena Vision: reading text12991241GLM 5.3 Flash
LMArena Vision: humor1279Not measuredOnly GLM 5.3 Flash measured
LMArena Vision: creative writing12701217GLM 5.3 Flash
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 Grok 4.7
BenchmarkGLM 5.3 FlashGrok 4.7Leader
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
Grok 4.7$0.0050Fits 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
Grok 4.7$0.118Fits 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
Grok 4.7$0.460Fits 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 Grok 4.7
SpecificationZ.ai GLM 5.3 FlashSpaceXAI Grok 4.7
MakerZ.aixAI
WeightsOpen weightsNo public weights listed
ReleasedAugust 26, 2026September 21, 2026
Context window1.05M500K
Input $/Mtok$0.15$2.00
Output $/Mtok$0.50$6.00
Coding index57.766.7
Independent measurements behind it65
Cost per solved task$0.02Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.3 Flash better than Grok 4.7 for coding?

Pick Grok 4.7 for coding: it scores 66.7 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 12.0x cheaper ($0.50 vs $6.00 per million) and a larger context window (1.05M against 500K tokens).

Which is cheaper, GLM 5.3 Flash or Grok 4.7?

GLM 5.3 Flash costs $0.15 per million input tokens and $0.50 per million output tokens; Grok 4.7 costs $2.00 and $6.00. Cost per solved task is known for GLM 5.3 Flash only.

Which has the bigger context window, GLM 5.3 Flash or Grok 4.7?

GLM 5.3 Flash, with 1.05M tokens against 500K.

How many benchmarks is the GLM 5.3 Flash vs Grok 4.7 comparison based on?

86 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 Grok 4.7's on 5. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/glm-5-3-flash-vs-grok-4-7">LLMBenchmark.ai, GLM 5.3 Flash vs Grok 4.7</a></p>