GLM 5 vs Grok 4.3
GLM 5 leads Grok 4.3 on coding, 41.7 to 37.4 on the Vibe Coding Index, and Grok 4.3 costs 1.3x less per output token ($2.50 vs $3.20 per million). Updated October 21, 2026; 65 benchmarks have a result for both.
GLM 5 or Grok 4.3: which to pick
Pick GLM 5 for coding: it scores 41.7 on the Vibe Coding Index against 37.4 for Grok 4.3.
Pick Grok 4.3 for output tokens 1.3x cheaper ($2.50 vs $3.20 per million) and a lower cost per solved task ($0.31 against $0.63).
- Shared results
- 65
- GLM 5 only
- 11
- Grok 4.3 only
- 39
- 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
GLM 5
GLM 5 scores 41.7 against 37.4.
3 benchmarks behind each score
Intelligence
AA Intelligence Index
GLM 5
GLM 5 leads, 27.9 against 24.9.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Grok 4.3 has a AA Agentic Index result, 15.5.
Directional only
Reasoning
GPQA Diamond
Grok 4.3
Grok 4.3 leads, 91.4% against 83.3%.
Same board, both measured
Math
AIME
No call
Only GLM 5 has a AIME result, 91.7%.
Directional only
Knowledge
MMLU Pro
GLM 5
GLM 5 leads, 86.0% against 85.8%.
Same board, both measured
Web design
Design Arena: websites
GLM 5
GLM 5 leads, 1247 against 1196.
Same board, both measured
Long documents
Listed context window
Grok 4.3
Grok 4.3 takes 1M tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Grok 4.3
GLM 5 $0.0026, Grok 4.3 $0.0025 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Grok 4.3
GLM 5 $0.63, Grok 4.3 $0.31.
Published attempt cost and pass rate
At a glance
- Coding index
- GLM 5 41.7 from 3 benchmarks, Grok 4.3 37.4 from 3 benchmarks.
- Widest category
- Agentic work, 17.4 points apart on average over 7 shared benchmarks.
- Widest single gap
- Design Arena: agents building Godot games: GLM 5 1144 against Grok 4.3 914, 28.8 points apart on a 0 to 100 scale.
- Output price
- GLM 5 $3.20 against Grok 4.3 $2.50 per million output tokens, 1.3x apart.
- Context window
- GLM 5 takes 205K tokens, Grok 4.3 1M.
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.
| Category | GLM 5 | Bars | Grok 4.3 | Ties |
|---|---|---|---|---|
| Coding | 7 | 3 | 1 tie | |
| Intelligence | 1 | 0 | ||
| Agentic work | 7 | 0 | ||
| Reasoning | 3 | 4 | ||
| Math | 2 | 1 | ||
| Knowledge | 5 | 4 | ||
| Web design | 8 | 0 | ||
| General | 18 | 1 | ||
| All shared boards | 51 | 13 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index73
| Benchmark | GLM 5 | Grok 4.3 | Leader |
|---|---|---|---|
| SWE-bench Verified | 72.8% | Not measured | Only GLM 5 measured |
| SWE-bench Multilingual | 69.7% | Not measured | Only GLM 5 measured |
| LMArena WebDev | 1435 | 1358 | GLM 5 |
| AA Coding Index | Not measured | 42.2 | Only Grok 4.3 measured |
| LiveCodeBench (Vals AI) | 81.9% | 84.5% | Grok 4.3 |
| SWE-bench Verified (Vals AI) | 71.4% | 71.4% | Tie |
| Vibe Code Bench (Vals AI) | 23.4% | 19.4% | GLM 5 |
| Code migration (Vals AI) | Not measured | 6.8% | Only Grok 4.3 measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Grok 4.3 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 42.0% | Only Grok 4.3 measured |
| SkillsBench (Vals AI) | Not measured | 40.6% | Only Grok 4.3 measured |
| SciCode | Not measured | 48.3% | Only Grok 4.3 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 43.2% | 37.9% | GLM 5 |
| Terminal-Bench | 52.4% | Not measured | Only GLM 5 measured |
| WeirdML | 48.2% | 49.9% | Grok 4.3 |
| ALE-Bench | 765.6 | 944.2 | Grok 4.3 |
| LMArena Text: coding | 1461 | 1415 | GLM 5 |
| LMArena Text: software and IT | 1460 | 1416 | GLM 5 |
| LMArena WebDev: React | 1424 | 1353 | GLM 5 |
| LMArena WebDev: HTML | 1450 | 1367 | GLM 5 |
| LMArena WebDev: from an image | Not measured | 1375 | Only Grok 4.3 measured |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5 | Grok 4.3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 27.9 | 24.9 | GLM 5 |
| Epoch Capabilities Index | 145.8 | Not measured | Only GLM 5 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | GLM 5 | Grok 4.3 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 15.5 | Only Grok 4.3 measured |
| Design Arena: agents building web apps | Not measured | 1126 | Only Grok 4.3 measured |
| Design Arena: agents building full-stack apps | 1123 | 1006 | GLM 5 |
| Design Arena: agents building mobile apps | 1136 | 1059 | GLM 5 |
| Design Arena: agents building Android apps | 1146 | 961 | GLM 5 |
| Design Arena: agents building Godot games | 1144 | 914 | GLM 5 |
| Design Arena: agents building games | Not measured | 1007 | Only Grok 4.3 measured |
| Design Arena: HTML slides | 1148 | 1008 | GLM 5 |
| Design Arena: PowerPoint slides | Not measured | 1013 | Only Grok 4.3 measured |
| Finance Agent (Vals AI) | Not measured | 37.7% | Only Grok 4.3 measured |
| Tax Agent Bench (Vals AI) | Not measured | 6.2% | Only Grok 4.3 measured |
| Legal Research Bench (Vals AI) | Not measured | 15.4% | Only Grok 4.3 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 18.4% | Only Grok 4.3 measured |
| τ²-Bench Telecom | 98.2% | 97.7% | GLM 5 |
| Vending-Bench 2 | $4,432 | $35 | GLM 5 |
| LMArena Search | Not measured | 1166 | Only Grok 4.3 measured |
| Neither model has a result on the other 25 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index34
| Benchmark | GLM 5 | Grok 4.3 | Leader |
|---|---|---|---|
| GPQA Diamond | 83.3% | 91.4% | Grok 4.3 |
| MMMU Pro (Vals AI) | Not measured | 83.1% | Only Grok 4.3 measured |
| GPQA Diamond (Artificial Analysis run) | 82.0% | 90.1% | Grok 4.3 |
| Humanity's Last Exam (Artificial Analysis run) | 29.3% | 37.2% | Grok 4.3 |
| GPQA Diamond (Epoch AI run) | 87.8% | 88.8% | Grok 4.3 |
| ARC-AGI | 44.7% | Not measured | Only GLM 5 measured |
| ARC-AGI-2 | 4.9% | Not measured | Only GLM 5 measured |
| SimpleBench | 53.2% | Not measured | Only GLM 5 measured |
| Chess puzzles | Not measured | 18.0% | Only Grok 4.3 measured |
| LMArena Text: hard prompts | 1452 | 1396 | GLM 5 |
| LMArena Text: expert | 1454 | 1384 | GLM 5 |
| LMArena Text: hard prompts in English | 1460 | 1402 | GLM 5 |
| LMArena Vision: diagrams | Not measured | 1241 | Only Grok 4.3 measured |
| LMArena Vision: homework | Not measured | 1241 | Only Grok 4.3 measured |
| Kagi LLM Benchmark | 75.0% | Not measured | Only GLM 5 measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | GLM 5 | Grok 4.3 | Leader |
|---|---|---|---|
| AIME | 91.7% | Not measured | Only GLM 5 measured |
| OTIS Mock AIME | 80.0% | 93.3% | Grok 4.3 |
| FrontierMath, tiers 1 to 3 | Not measured | 42.8% | Only Grok 4.3 measured |
| FrontierMath, tier 4 | Not measured | 14.6% | Only Grok 4.3 measured |
| ProofBench | Not measured | 11.0% | Only Grok 4.3 measured |
| LMArena Text: math | 1440 | 1387 | GLM 5 |
| LMArena Text: mathematical work | 1451 | 1396 | GLM 5 |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index54
| Benchmark | GLM 5 | Grok 4.3 | Leader |
|---|---|---|---|
| MMLU Pro | 86.0% | 85.8% | GLM 5 |
| LegalBench (Vals AI) | 84.1% | 84.5% | Grok 4.3 |
| CaseLaw (Vals AI) | 52.5% | 79.3% | Grok 4.3 |
| CorpFin (Vals AI) | 62.9% | 68.5% | Grok 4.3 |
| TaxEval (Vals AI) | 70.0% | 70.8% | Grok 4.3 |
| MortgageTax (Vals AI) | Not measured | 48.3% | Only Grok 4.3 measured |
| MedQA (Vals AI) | 94.3% | Not measured | Only GLM 5 measured |
| MedCode (Vals AI) | Not measured | 38.1% | Only Grok 4.3 measured |
| SimpleQA Verified | Not measured | 33.2% | Only Grok 4.3 measured |
| LMArena Text: science | 1460 | 1399 | GLM 5 |
| LMArena Text: medicine and healthcare | 1455 | 1384 | GLM 5 |
| LMArena Text: legal and government | 1453 | 1386 | GLM 5 |
| LMArena Text: business and finance | 1430 | 1381 | GLM 5 |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | GLM 5 | Grok 4.3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1247 | 1196 | GLM 5 |
| Design Arena: UI components | 1230 | 1192 | GLM 5 |
| Design Arena: game dev | 1234 | 1174 | GLM 5 |
| Design Arena: data viz | 1228 | 1179 | GLM 5 |
| Design Arena: 3D | 1229 | 1125 | GLM 5 |
| Design Arena: all code categories | 1246 | 1187 | GLM 5 |
| Design Arena: SVG | 1168 | 1081 | GLM 5 |
| Design Arena: ASCII art | 1147 | 1125 | GLM 5 |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index181
| Benchmark | GLM 5 | Grok 4.3 | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | Not measured | 51.7% | Only Grok 4.3 measured |
| SAGE (Vals AI) | Not measured | 19.7% | Only Grok 4.3 measured |
| MedScribe (Vals AI) | Not measured | 74.4% | Only Grok 4.3 measured |
| Vals Multimodal Index | Not measured | 43.3% | Only Grok 4.3 measured |
| IFBench | 72.3% | 83.3% | Grok 4.3 |
| Long context reasoning (AA-LCR) | 75.7% | 75.0% | GLM 5 |
| DTBench | Not measured | 90.7% | Only Grok 4.3 measured |
| LMCA | Not measured | 38.3% | Only Grok 4.3 measured |
| CL-bench | 18.7% | Not measured | Only GLM 5 measured |
| LMArena Text | 1446 | 1397 | GLM 5 |
| LMArena Text: instruction following | 1428 | 1366 | GLM 5 |
| LMArena Text: creative writing | 1438 | 1380 | GLM 5 |
| LMArena Vision | Not measured | 1229 | Only Grok 4.3 measured |
| LMArena Text: English | 1458 | 1404 | GLM 5 |
| LMArena Text: non-English | 1430 | 1385 | GLM 5 |
| LMArena Text: Chinese | 1511 | 1422 | GLM 5 |
| LMArena Text: German | 1447 | 1395 | GLM 5 |
| LMArena Text: Japanese | 1416 | 1379 | GLM 5 |
| LMArena Text: Korean | 1423 | 1354 | GLM 5 |
| LMArena Text: French | 1456 | 1411 | GLM 5 |
| LMArena Text: Spanish | 1454 | 1399 | GLM 5 |
| LMArena Text: Russian | 1436 | 1399 | GLM 5 |
| LMArena Text: Polish | 1434 | 1398 | GLM 5 |
| LMArena Text: multi-turn | 1456 | 1406 | GLM 5 |
| LMArena Text: longer queries | 1446 | 1393 | GLM 5 |
| LMArena Text: writing and language | 1437 | 1385 | GLM 5 |
| LMArena Text: entertainment and media | 1426 | 1370 | GLM 5 |
| LMArena Vision: English | Not measured | 1235 | Only Grok 4.3 measured |
| LMArena Vision: Chinese | Not measured | 1257 | Only Grok 4.3 measured |
| LMArena Vision: reading text | Not measured | 1235 | Only Grok 4.3 measured |
| LMArena Vision: humor | Not measured | 1222 | Only Grok 4.3 measured |
| LMArena Vision: recognizing things | Not measured | 1217 | Only Grok 4.3 measured |
| LMArena Vision: creative writing | Not measured | 1237 | Only Grok 4.3 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
| Benchmark | GLM 5 | Grok 4.3 | 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
Grok 4.3 costs less
Repository review
50K input + 3K output tokens
GLM 5 costs less
Agent loop
200K input + 10K output tokens
GLM 5 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.
| Specification | Z.ai GLM 5 | SpaceXAI Grok 4.3 |
|---|---|---|
| Maker | Z.ai | xAI |
| Weights | Open weights | No public weights listed |
| Released | February 11, 2026 | April 30, 2026 |
| Context window | 205K | 1M |
| Input $/Mtok | $1.00 | $1.25 |
| Output $/Mtok | $3.20 | $2.50 |
| Coding index | 41.7 | 37.4 |
| Independent measurements behind it | 3 | 3 |
| Cost per solved task | $0.63 | $0.31 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5 better than Grok 4.3 for coding?
Pick GLM 5 for coding: it scores 41.7 on the Vibe Coding Index against 37.4 for Grok 4.3. Pick Grok 4.3 for output tokens 1.3x cheaper ($2.50 vs $3.20 per million) and a lower cost per solved task ($0.31 against $0.63).
Which is cheaper, GLM 5 or Grok 4.3?
GLM 5 costs $1.00 per million input tokens and $3.20 per million output tokens; Grok 4.3 costs $1.25 and $2.50. Per solved SWE-bench Verified task, GLM 5 costs $0.63 and Grok 4.3 $0.31.
Which has the bigger context window, GLM 5 or Grok 4.3?
Grok 4.3, with 1M tokens against 205K.
How many benchmarks is the GLM 5 vs Grok 4.3 comparison based on?
65 benchmarks have a result for both models as of October 21, 2026. GLM 5's coding index rests on 3 independent benchmarks and Grok 4.3's on 3. Where only one model has a result, the page says so instead of naming a winner.