GLM 5V Turbo vs MiniMax M3
Updated October 21, 2026. 63 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick MiniMax M3 for coding: it scores 57.8 on the Vibe Coding Index against 28.8 for GLM 5V Turbo.
Pick GLM 5V Turbo when what matters is Design Arena: agents building Android apps or τ²-Bench Telecom, where it leads.
- Shared results
- 63
- GLM 5V Turbo only
- 2
- MiniMax M3 only
- 53
- Like-for-like categories
- 8 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
MiniMax M3
MiniMax M3 scores 57.8 against 28.8.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
MiniMax M3
MiniMax M3 leads, 29.2 against 23.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only MiniMax M3 has a AA Agentic Index result, 29.5.
Directional only
Reasoning
GPQA Diamond
No call
Only MiniMax M3 has a GPQA Diamond result, 92.7%.
Directional only
Knowledge
MMLU Pro
No call
Only MiniMax M3 has a MMLU Pro result, 84.2%.
Directional only
Web design
Design Arena: websites
MiniMax M3
MiniMax M3 leads, 1257 against 1230.
Same board, both measured
Long documents
Listed context window
MiniMax M3
MiniMax M3 takes 1.05M tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M3
GLM 5V Turbo $0.0032, MiniMax M3 $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M3 has the number, $0.56.
Directional only
At a glance
- Coding index
- GLM 5V Turbo 28.8 from 1 benchmark, MiniMax M3 57.8 from 2 benchmarks.
- Widest category
- Coding, 8.9 points apart on average over 7 shared benchmarks.
- Widest single gap
- Humanity's Last Exam (Artificial Analysis run): GLM 5V Turbo 17.1% against MiniMax M3 39.0%, 21.9 points apart on a 0 to 100 scale.
- Output price
- GLM 5V Turbo $4.00 against MiniMax M3 $1.20 per million output tokens, 3.3x apart.
- Context window
- GLM 5V Turbo takes 203K tokens, MiniMax M3 1.05M.
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 5V Turbo | Bars | MiniMax M3 | Ties |
|---|---|---|---|---|
| Coding | 0 | 7 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 2 | 6 | ||
| Reasoning | 3 | 4 | ||
| Math | 1 | 1 | ||
| Knowledge | 1 | 3 | ||
| Web design | 1 | 6 | 1 tie | |
| General | 18 | 8 | ||
| All shared boards | 26 | 36 | 1 tie |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index07
| Benchmark | GLM 5V Turbo | MiniMax M3 | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 70.9% | Only MiniMax M3 measured |
| LMArena WebDev | 1402 | 1482 | MiniMax M3 |
| AA Coding Index | Not measured | 58.6 | Only MiniMax M3 measured |
| LiveCodeBench (Vals AI) | Not measured | 82.2% | Only MiniMax M3 measured |
| SWE-bench Verified (Vals AI) | Not measured | 75.0% | Only MiniMax M3 measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 1.0% | Only MiniMax M3 measured |
| Vibe Code Bench (Vals AI) | Not measured | 47.6% | Only MiniMax M3 measured |
| Code migration (Vals AI) | Not measured | 19.9% | Only MiniMax M3 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 53.6% | Only MiniMax M3 measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 33.3% | Only MiniMax M3 measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 9.2% | Only MiniMax M3 measured |
| SkillsBench (Vals AI) | Not measured | 51.5% | Only MiniMax M3 measured |
| CyberBench (Vals AI) | Not measured | 65.0% | Only MiniMax M3 measured |
| SciCode | Not measured | 47.1% | Only MiniMax M3 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 32.6% | 42.4% | MiniMax M3 |
| FrontierCode | Not measured | 14.7% | Only MiniMax M3 measured |
| ALE-Bench | Not measured | 640.0 | Only MiniMax M3 measured |
| LMArena Text: coding | 1466 | 1470 | MiniMax M3 |
| LMArena Text: software and IT | 1460 | 1466 | MiniMax M3 |
| LMArena WebDev: React | 1386 | 1478 | MiniMax M3 |
| LMArena WebDev: HTML | 1356 | 1455 | MiniMax M3 |
| LMArena WebDev: from an image | 1425 | 1470 | MiniMax M3 |
| Neither model has a result on the other 16 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 5V Turbo | MiniMax M3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.5 | 29.2 | MiniMax M3 |
| Epoch Capabilities Index | Not measured | 146.9 | Only MiniMax M3 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index26
| Benchmark | GLM 5V Turbo | MiniMax M3 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 29.5 | Only MiniMax M3 measured |
| Design Arena: agents building web apps | 1124 | 1200 | MiniMax M3 |
| Design Arena: agents building full-stack apps | 1149 | 1197 | MiniMax M3 |
| Design Arena: agents building mobile apps | 1134 | 1169 | MiniMax M3 |
| Design Arena: agents building Android apps | 1267 | 1164 | GLM 5V Turbo |
| Design Arena: agents building Godot games | 957 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building games | 1102 | 1158 | MiniMax M3 |
| Design Arena: HTML slides | 1120 | 1180 | MiniMax M3 |
| Design Arena: PowerPoint slides | 1152 | 1205 | MiniMax M3 |
| Design Arena: spreadsheets | Not measured | 1021 | Only MiniMax M3 measured |
| LiveBench research | Not measured | 68.0% | Only MiniMax M3 measured |
| LiveBench browser | Not measured | 8.0% | Only MiniMax M3 measured |
| LiveBench long agentic | Not measured | 12.4% | Only MiniMax M3 measured |
| Finance Agent (Vals AI) | Not measured | 48.3% | Only MiniMax M3 measured |
| Tax Agent Bench (Vals AI) | Not measured | 20.6% | Only MiniMax M3 measured |
| Legal Research Bench (Vals AI) | Not measured | 29.8% | Only MiniMax M3 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 47.8% | Only MiniMax M3 measured |
| τ²-Bench Telecom | 98.5% | 88.9% | GLM 5V Turbo |
| APEX-Agents | Not measured | 37.7% | Only MiniMax M3 measured |
| OSWorld 2.0 | Not measured | 4.6% | Only MiniMax M3 measured |
| Vending-Bench 2 | Not measured | $2,158 | Only MiniMax M3 measured |
| Neither model has a result on the other 18 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index34
| Benchmark | GLM 5V Turbo | MiniMax M3 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 92.7% | Only MiniMax M3 measured |
| LiveBench reasoning | Not measured | 74.5% | Only MiniMax M3 measured |
| MMMU Pro (Vals AI) | Not measured | 81.2% | Only MiniMax M3 measured |
| GPQA Diamond (Artificial Analysis run) | 80.9% | 92.9% | MiniMax M3 |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | 39.0% | MiniMax M3 |
| GPQA Diamond (Epoch AI run) | Not measured | 90.9% | Only MiniMax M3 measured |
| SimpleBench | Not measured | 45.8% | Only MiniMax M3 measured |
| Chess puzzles | Not measured | 13.0% | Only MiniMax M3 measured |
| Mystery game puzzles | Not measured | 8.0% | Only MiniMax M3 measured |
| LMArena Text: hard prompts | 1443 | 1447 | MiniMax M3 |
| LMArena Text: expert | 1453 | 1461 | MiniMax M3 |
| LMArena Text: hard prompts in English | 1456 | 1455 | GLM 5V Turbo |
| LMArena Vision: diagrams | 1286 | 1266 | GLM 5V Turbo |
| LMArena Vision: homework | 1273 | 1268 | GLM 5V Turbo |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GLM 5V Turbo | MiniMax M3 | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 71.1% | Only MiniMax M3 measured |
| ProofBench | Not measured | 18.0% | Only MiniMax M3 measured |
| LMArena Text: math | 1442 | 1429 | GLM 5V Turbo |
| LMArena Text: mathematical work | 1447 | 1448 | MiniMax M3 |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | GLM 5V Turbo | MiniMax M3 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 84.2% | Only MiniMax M3 measured |
| LegalBench (Vals AI) | Not measured | 85.4% | Only MiniMax M3 measured |
| CorpFin (Vals AI) | Not measured | 68.1% | Only MiniMax M3 measured |
| TaxEval (Vals AI) | Not measured | 72.7% | Only MiniMax M3 measured |
| MortgageTax (Vals AI) | Not measured | 68.4% | Only MiniMax M3 measured |
| MedCode (Vals AI) | Not measured | 46.3% | Only MiniMax M3 measured |
| LMArena Text: science | 1448 | 1452 | MiniMax M3 |
| LMArena Text: medicine and healthcare | 1433 | 1441 | MiniMax M3 |
| LMArena Text: legal and government | 1436 | 1437 | MiniMax M3 |
| LMArena Text: business and finance | 1435 | 1434 | GLM 5V Turbo |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index16
| Benchmark | GLM 5V Turbo | MiniMax M3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1230 | 1257 | MiniMax M3 |
| Design Arena: UI components | 1213 | 1246 | MiniMax M3 |
| Design Arena: game dev | 1219 | 1210 | GLM 5V Turbo |
| Design Arena: data viz | 1202 | 1235 | MiniMax M3 |
| Design Arena: 3D | 1209 | 1209 | Tie |
| Design Arena: all code categories | 1228 | 1247 | MiniMax M3 |
| Design Arena: SVG | 1151 | 1161 | MiniMax M3 |
| Design Arena: ASCII art | 1118 | 1161 | MiniMax M3 |
| LiveBench design | Not measured | 66.2% | Only MiniMax M3 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index188
| Benchmark | GLM 5V Turbo | MiniMax M3 | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 76.2% | Only MiniMax M3 measured |
| Public Benefits Bench (Vals AI) | Not measured | 64.1% | Only MiniMax M3 measured |
| SAGE (Vals AI) | Not measured | 50.6% | Only MiniMax M3 measured |
| MedScribe (Vals AI) | Not measured | 87.3% | Only MiniMax M3 measured |
| Vals Multimodal Index | Not measured | 60.0% | Only MiniMax M3 measured |
| IFBench | 61.1% | 82.9% | MiniMax M3 |
| Long context reasoning (AA-LCR) | 70.3% | 83.0% | MiniMax M3 |
| DTBench | Not measured | 78.9% | Only MiniMax M3 measured |
| LMCA | Not measured | 33.7% | Only MiniMax M3 measured |
| Surface Evolver Bench | Not measured | 55.0% | Only MiniMax M3 measured |
| LMArena Text | 1437 | 1433 | GLM 5V Turbo |
| LMArena Text: instruction following | 1423 | 1433 | MiniMax M3 |
| LMArena Text: creative writing | 1417 | 1404 | GLM 5V Turbo |
| LMArena Vision | 1264 | 1251 | GLM 5V Turbo |
| LMArena Text: English | 1454 | 1443 | GLM 5V Turbo |
| LMArena Text: non-English | 1420 | 1420 | GLM 5V Turbo |
| LMArena Text: Chinese | 1491 | 1466 | GLM 5V Turbo |
| LMArena Text: German | 1422 | 1428 | MiniMax M3 |
| LMArena Text: Japanese | Not measured | 1380 | Only MiniMax M3 measured |
| LMArena Text: Korean | 1397 | 1373 | GLM 5V Turbo |
| LMArena Text: French | 1443 | 1444 | MiniMax M3 |
| LMArena Text: Spanish | 1452 | 1433 | GLM 5V Turbo |
| LMArena Text: Russian | 1432 | 1426 | GLM 5V Turbo |
| LMArena Text: Polish | 1432 | 1423 | GLM 5V Turbo |
| LMArena Text: multi-turn | 1431 | 1443 | MiniMax M3 |
| LMArena Text: longer queries | 1438 | 1446 | MiniMax M3 |
| LMArena Text: writing and language | 1420 | 1419 | GLM 5V Turbo |
| LMArena Text: entertainment and media | 1407 | 1403 | GLM 5V Turbo |
| LMArena Vision: English | 1274 | 1263 | GLM 5V Turbo |
| LMArena Vision: Chinese | 1329 | 1311 | GLM 5V Turbo |
| LMArena Vision: reading text | 1270 | 1259 | GLM 5V Turbo |
| LMArena Vision: humor | 1268 | 1235 | GLM 5V Turbo |
| LMArena Vision: captioning | 1264 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: recognizing things | 1241 | 1197 | GLM 5V Turbo |
| LMArena Vision: creative writing | 1252 | 1234 | GLM 5V Turbo |
| LMArena Document | 1416 | 1435 | MiniMax M3 |
| Neither model has a result on the other 10 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5V Turbo | MiniMax M3 | 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
MiniMax M3 costs less
Repository review
50K input + 3K output tokens
MiniMax M3 costs less
Agent loop
200K input + 10K output tokens
MiniMax M3 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 5V Turbo | MiniMax M3 |
|---|---|---|
| Maker | Z.ai | MiniMax |
| Weights | No public weights listed | Open weights |
| Released | April 1, 2026 | May 31, 2026 |
| Context window | 203K | 1.05M |
| Input $/Mtok | $1.20 | $0.30 |
| Output $/Mtok | $4.00 | $1.20 |
| Coding index | 28.8 | 57.8 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | Not computable | $0.56 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5V Turbo better than MiniMax M3 for coding?
Pick MiniMax M3 for coding: it scores 57.8 on the Vibe Coding Index against 28.8 for GLM 5V Turbo. Pick GLM 5V Turbo when what matters is Design Arena: agents building Android apps or τ²-Bench Telecom, where it leads.
Which is cheaper, GLM 5V Turbo or MiniMax M3?
GLM 5V Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; MiniMax M3 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M3 only.
Which has the bigger context window, GLM 5V Turbo or MiniMax M3?
MiniMax M3, with 1.05M tokens against 203K.
How many benchmarks is the GLM 5V Turbo vs MiniMax M3 comparison based on?
63 benchmarks have a result for both models as of October 21, 2026. GLM 5V Turbo's coding index rests on 1 independent benchmark and MiniMax M3's on 2. Where only one model has a result, the page says so instead of naming a winner.