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GLM 5.3 vs Mistral Large 4

GLM 5.3 leads Mistral Large 4 on coding, 70.6 to 56.4 on the Vibe Coding Index, at about the same output price ($4.40 vs $4.18 per million). Updated October 21, 2026; 73 benchmarks have a result for both.

Replace GLM 5.3 Replace Mistral Large 4
GLM 5.3Z.ai
Coding
70.6
Overall
67.9
Output $/M
$4.40
65
Mistral Large 4Mistral AI
Coding
56.4
Overall
54.6
Output $/M
$4.18
8
vs boards won of 73 shared

GLM 5.3 or Mistral Large 4: which to pick

Pick GLM 5.3 for coding: it scores 70.6 on the Vibe Coding Index against 56.4 for Mistral Large 4.

Pick Mistral Large 4 for output tokens 1.1x cheaper ($4.18 vs $4.40 per million) and work measured by Vibe Code Bench (Vals AI) or LiveBench browser, where it leads.

Model AGLM 5.3Z.ai70.6/1006 independent benchmarks$0.36 per solved taskModel BMistral Large 4Mistral AI56.4/1005 independent benchmarksNo cost per solved task
Shared results
73
GLM 5.3 only
27
Mistral Large 4 only
8
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 70.6 from 6 benchmarks, Mistral Large 4 56.4 from 5 benchmarks.
Widest category
Agentic work, 13.5 points apart on average over 8 shared benchmarks.
Widest single gap
LiveBench research: GLM 5.3 73.2% against Mistral Large 4 28.1%, 45.1 points apart on a 0 to 100 scale.
Output price
GLM 5.3 $4.40 against Mistral Large 4 $4.18 per million output tokens, 1.1x 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
CategoryGLM 5.3BarsMistral Large 4Ties
Coding131
Intelligence20
Agentic work62
Reasoning90
Math51
Knowledge60
Web design81
General163
All shared boards658
CodingLike-for-likeSix of these boards feed the Vibe Coding Index131
Coding benchmarks for GLM 5.3 and Mistral Large 4
BenchmarkGLM 5.3Mistral Large 4Leader
LiveBench coding82.8%60.0%GLM 5.3
LMArena WebDev16211543GLM 5.3
AA Coding Index74.8Not measuredOnly GLM 5.3 measured
LiveCodeBench (Vals AI)80.5%Not measuredOnly GLM 5.3 measured
SWE-bench Verified (Vals AI)95.4%Not measuredOnly GLM 5.3 measured
Terminal-Bench 4 (Vals AI)38.9%27.8%GLM 5.3
Vibe Code Bench (Vals AI)78.1%78.4%Mistral Large 4
Code migration (Vals AI)44.2%30.6%GLM 5.3
ProgramBench (Vals AI)1.5%Not measuredOnly GLM 5.3 measured
IOI (Vals AI)68.4%45.3%GLM 5.3
Terminal-Bench 2.1 (Vals AI)71.5%Not measuredOnly GLM 5.3 measured
SWE-bench Multimodal (Vals AI)Not measured33.1%Only Mistral Large 4 measured
Vibe Code Bench 1-100 (Vals AI)20.0%14.3%GLM 5.3
SkillsBench (Vals AI)47.5%Not measuredOnly GLM 5.3 measured
CyberBench (Vals AI)72.1%Not measuredOnly GLM 5.3 measured
SciCode59.0%54.2%GLM 5.3
FrontierCode40.1%39.4%GLM 5.3
FrontierSWE30.2%Not measuredOnly GLM 5.3 measured
WeirdML75.4%Not measuredOnly GLM 5.3 measured
ALE-Bench1317.41213.2GLM 5.3
LMArena Text: coding14971478GLM 5.3
LMArena Text: software and IT14931467GLM 5.3
LMArena WebDev: React16411559GLM 5.3
LMArena WebDev: HTML15951487GLM 5.3
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for GLM 5.3 and Mistral Large 4
BenchmarkGLM 5.3Mistral Large 4Leader
AA Intelligence Index44.838.4GLM 5.3
Epoch Capabilities Index156.0150.0GLM 5.3
Agentic workLike-for-likePublic boards, shown as published, kept out of the index62
Agentic work benchmarks for GLM 5.3 and Mistral Large 4
BenchmarkGLM 5.3Mistral Large 4Leader
AA Agentic Index53.1Not measuredOnly GLM 5.3 measured
Design Arena: agents building mobile apps1194Not measuredOnly GLM 5.3 measured
Design Arena: HTML slides1189Not measuredOnly GLM 5.3 measured
Design Arena: PowerPoint slides1254Not measuredOnly GLM 5.3 measured
LiveBench research73.2%28.1%GLM 5.3
LiveBench browser0.0%8.0%Mistral Large 4
LiveBench long agentic35.9%11.8%GLM 5.3
SREBench (Vals AI)9.2%Not measuredOnly GLM 5.3 measured
Finance Agent (Vals AI)55.8%54.7%GLM 5.3
Tax Agent Bench (Vals AI)39.7%30.4%GLM 5.3
Legal Research Bench (Vals AI)49.0%31.7%GLM 5.3
Harvey's Legal Agent Benchmark (Vals AI)14.6%17.5%Mistral Large 4
Excel Modeling Benchmark (Vals AI)56.3%56.2%GLM 5.3
BioMysteryBench (Vals AI)Not measured67.0%Only Mistral Large 4 measured
Terminal-Bench-Science (Vals AI)5.7%Not measuredOnly GLM 5.3 measured
APEX-Agents56.6%Not measuredOnly GLM 5.3 measured
Vending-Bench 2$8,164Not measuredOnly GLM 5.3 measured
Neither model has a result on the other 24 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index90
Reasoning benchmarks for GLM 5.3 and Mistral Large 4
BenchmarkGLM 5.3Mistral Large 4Leader
GPQA Diamond88.1%Not measuredOnly GLM 5.3 measured
LiveBench reasoning85.8%83.9%GLM 5.3
MysteryMechanism (Vals AI)23.0%12.2%GLM 5.3
GPQA Diamond (Artificial Analysis run)91.7%Not measuredOnly GLM 5.3 measured
Humanity's Last Exam (Artificial Analysis run)42.3%35.0%GLM 5.3
GPQA Diamond (Epoch AI run)90.9%88.1%GLM 5.3
Chess puzzles37.0%33.0%GLM 5.3
Mystery game puzzles33.0%17.0%GLM 5.3
LMArena Text: hard prompts14901444GLM 5.3
LMArena Text: expert15141444GLM 5.3
LMArena Text: hard prompts in English14961442GLM 5.3
LMArena Vision: diagramsNot measured1288Only Mistral Large 4 measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index51
Math benchmarks for GLM 5.3 and Mistral Large 4
BenchmarkGLM 5.3Mistral Large 4Leader
OTIS Mock AIME91.1%98.3%Mistral Large 4
FrontierMath, tiers 1 to 368.8%58.6%GLM 5.3
FrontierMath, tier 429.3%26.8%GLM 5.3
ProofBench49.0%10.0%GLM 5.3
LMArena Text: math14951469GLM 5.3
LMArena Text: mathematical work14971462GLM 5.3
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index60
Knowledge benchmarks for GLM 5.3 and Mistral Large 4
BenchmarkGLM 5.3Mistral Large 4Leader
MMLU Pro86.8%Not measuredOnly GLM 5.3 measured
LegalBench (Vals AI)84.8%Not measuredOnly GLM 5.3 measured
TaxEval (Vals AI)72.4%Not measuredOnly GLM 5.3 measured
MedCode (Vals AI)42.9%40.7%GLM 5.3
SimpleQA Verified41.0%20.0%GLM 5.3
LMArena Text: science14981448GLM 5.3
LMArena Text: medicine and healthcare14811433GLM 5.3
LMArena Text: legal and government14731425GLM 5.3
LMArena Text: business and finance14591439GLM 5.3
Neither model has a result on the other 9 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index81
Web design benchmarks for GLM 5.3 and Mistral Large 4
BenchmarkGLM 5.3Mistral Large 4Leader
Design Arena: websites12951258GLM 5.3
Design Arena: UI components13141275GLM 5.3
Design Arena: game dev13111226GLM 5.3
Design Arena: data viz12591274Mistral Large 4
Design Arena: 3D13321253GLM 5.3
Design Arena: all code categories13041259GLM 5.3
Design Arena: SVG12931233GLM 5.3
Design Arena: ASCII art12131202GLM 5.3
LiveBench design77.3%65.6%GLM 5.3
GeneralLike-for-likePublic boards, shown as published, kept out of the index163
General benchmarks for GLM 5.3 and Mistral Large 4
BenchmarkGLM 5.3Mistral Large 4Leader
Vals Index59.7%Not measuredOnly GLM 5.3 measured
LiveBench data analysis70.2%76.5%Mistral Large 4
Public Benefits Bench (Vals AI)68.5%Not measuredOnly GLM 5.3 measured
MedScribe (Vals AI)88.8%80.4%GLM 5.3
Long context reasoning (AA-LCR)79.7%81.3%Mistral Large 4
DTBench87.7%88.2%Mistral Large 4
LMCA55.5%35.8%GLM 5.3
Surface Evolver BenchNot measured28.1%Only Mistral Large 4 measured
Furniture assemblyNot measured20.8%Only Mistral Large 4 measured
LMArena Text14741431GLM 5.3
LMArena Text: instruction following14791422GLM 5.3
LMArena Text: creative writing14581363GLM 5.3
LMArena VisionNot measured1272Only Mistral Large 4 measured
LMArena Text: English14821433GLM 5.3
LMArena Text: non-English14591422GLM 5.3
LMArena Text: Chinese15321492GLM 5.3
LMArena Text: German1488Not measuredOnly GLM 5.3 measured
LMArena Text: Japanese14601415GLM 5.3
LMArena Text: Korean1460Not measuredOnly GLM 5.3 measured
LMArena Text: French15031492GLM 5.3
LMArena Text: Spanish14621455GLM 5.3
LMArena Text: Russian14691417GLM 5.3
LMArena Text: Polish1466Not measuredOnly GLM 5.3 measured
LMArena Text: multi-turn14721435GLM 5.3
LMArena Text: longer queries14831428GLM 5.3
LMArena Text: writing and language14691386GLM 5.3
LMArena Text: entertainment and media14471378GLM 5.3
LMArena Vision: EnglishNot measured1283Only Mistral Large 4 measured
LMArena Vision: reading textNot measured1284Only Mistral Large 4 measured
Neither model has a result on the other 17 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 5.3 and Mistral Large 4
BenchmarkGLM 5.3Mistral Large 4Leader
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$0.0036Fits in one request
Mistral Large 4$0.0034Fits in one request

Mistral Large 4 costs less

Repository review

50K input + 3K output tokens

GLM 5.3$0.083Fits in one request
Mistral Large 4$0.081Fits in one request

Mistral Large 4 costs less

Agent loop

200K input + 10K output tokens

GLM 5.3$0.324Fits in one request
Mistral Large 4$0.314Fits in one request

Mistral Large 4 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 and Mistral Large 4
SpecificationZ.ai GLM 5.3Mistral Large 4
MakerZ.aiMistral AI
WeightsOpen weightsNo public weights listed
ReleasedAugust 18, 2026October 6, 2026
Context window1.05M1.05M
Input $/Mtok$1.40$1.36
Output $/Mtok$4.40$4.18
Coding index70.656.4
Independent measurements behind it65
Cost per solved task$0.36Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.3 better than Mistral Large 4 for coding?

Pick GLM 5.3 for coding: it scores 70.6 on the Vibe Coding Index against 56.4 for Mistral Large 4. Pick Mistral Large 4 for output tokens 1.1x cheaper ($4.18 vs $4.40 per million) and work measured by Vibe Code Bench (Vals AI) or LiveBench browser, where it leads.

Which is cheaper, GLM 5.3 or Mistral Large 4?

GLM 5.3 costs $1.40 per million input tokens and $4.40 per million output tokens; Mistral Large 4 costs $1.36 and $4.18. Cost per solved task is known for GLM 5.3 only.

Which has the bigger context window, GLM 5.3 or Mistral Large 4?

Neither: both take 1.05M tokens.

How many benchmarks is the GLM 5.3 vs Mistral Large 4 comparison based on?

73 benchmarks have a result for both models as of October 21, 2026. GLM 5.3's coding index rests on 6 independent benchmarks and Mistral Large 4's on 5. Where only one model has a result, the page says so instead of naming a winner.

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