GLM 5V Turbo vs GPT-5 Mini
GLM 5V Turbo leads GPT-5 Mini on the Artificial Analysis Intelligence Index, 23.5 to 20.6, and GPT-5 Mini costs 2.0x less per output token ($2.00 vs $4.00 per million). Updated October 22, 2026; 52 benchmarks have a result for both.
GLM 5V Turbo or GPT-5 Mini: which to pick
Only GPT-5 Mini has a coding score, 34.2 on the Vibe Coding Index; GLM 5V Turbo has none, so the two cannot be ranked on coding.
Pick GLM 5V Turbo for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
- Shared results
- 52
- GLM 5V Turbo only
- 13
- GPT-5 Mini only
- 49
- 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
No call
Only GPT-5 Mini has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GLM 5V Turbo
GLM 5V Turbo leads, 23.5 against 20.6.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-5 Mini has a GPQA Diamond result, 80.3%.
Directional only
Math
AIME
No call
Only GPT-5 Mini has a AIME result, 91.5%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5 Mini has a MMLU Pro result, 82.2%.
Directional only
Web design
Design Arena: websites
GLM 5V Turbo
GLM 5V Turbo leads, 1230 against 1125.
Same board, both measured
Long documents
Listed context window
GPT-5 Mini
GPT-5 Mini takes 400K tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5 Mini
GLM 5V Turbo $0.0032, GPT-5 Mini $0.0013 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5 Mini has the number, $0.08.
Directional only
At a glance
- Coding index
- GLM 5V Turbo not benchmarked, GPT-5 Mini 34.2 from 2 benchmarks.
- Widest category
- Agentic work, 27.5 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: GLM 5V Turbo 98.5% against GPT-5 Mini 71.1%, 27.5 points apart on a 0 to 100 scale.
- Output price
- GLM 5V Turbo $4.00 against GPT-5 Mini $2.00 per million output tokens, 2.0x apart.
- Context window
- GLM 5V Turbo takes 203K tokens, GPT-5 Mini 400K.
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 | GPT-5 Mini | Ties |
|---|---|---|---|---|
| Coding | 2 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 5 | 2 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| Web design | 7 | 1 | ||
| General | 24 | 2 | ||
| All shared boards | 46 | 6 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index21
| Benchmark | GLM 5V Turbo | GPT-5 Mini | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 59.8% | Only GPT-5 Mini measured |
| SWE-bench Multilingual | Not measured | 39.7% | Only GPT-5 Mini measured |
| LMArena WebDev | 1402 | Not measured | Only GLM 5V Turbo measured |
| LiveCodeBench (Vals AI) | Not measured | 86.6% | Only GPT-5 Mini measured |
| SWE-bench Verified (Vals AI) | Not measured | 60.8% | Only GPT-5 Mini measured |
| Vibe Code Bench (Vals AI) | Not measured | 14.2% | Only GPT-5 Mini measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 83.8% | Only GPT-5 Mini measured |
| SciCode | Not measured | 39.0% | Only GPT-5 Mini measured |
| Terminal-Bench Hard (Artificial Analysis run) | 32.6% | 33.3% | GPT-5 Mini |
| Terminal-Bench | Not measured | 34.8% | Only GPT-5 Mini measured |
| WeirdML | Not measured | 52.7% | Only GPT-5 Mini measured |
| LMArena Text: coding | 1466 | 1406 | GLM 5V Turbo |
| LMArena Text: software and IT | 1460 | 1394 | GLM 5V Turbo |
| LMArena WebDev: React | 1386 | Not measured | Only GLM 5V Turbo measured |
| LMArena WebDev: HTML | 1356 | Not measured | Only GLM 5V Turbo measured |
| LMArena WebDev: from an image | 1425 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5V Turbo | GPT-5 Mini | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.5 | 20.6 | GLM 5V Turbo |
| Epoch Capabilities Index | Not measured | 145.3 | Only GPT-5 Mini measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5V Turbo | GPT-5 Mini | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1124 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building full-stack apps | 1149 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building mobile apps | 1134 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building Android apps | 1267 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building Godot games | 957 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: agents building games | 1102 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: HTML slides | 1070 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: PowerPoint slides | 1127 | Not measured | Only GLM 5V Turbo measured |
| τ²-Bench Telecom | 98.5% | 71.1% | GLM 5V Turbo |
| Vending-Bench 2 | Not measured | -$31 | Only GPT-5 Mini measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 55.5% | Only GPT-5 Mini measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index52
| Benchmark | GLM 5V Turbo | GPT-5 Mini | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 80.3% | Only GPT-5 Mini measured |
| MMMU Pro (Vals AI) | Not measured | 78.9% | Only GPT-5 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 80.9% | 82.8% | GPT-5 Mini |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | 21.5% | GPT-5 Mini |
| GPQA Diamond (Epoch AI run) | Not measured | 75.0% | Only GPT-5 Mini measured |
| ARC-AGI | Not measured | 54.3% | Only GPT-5 Mini measured |
| ARC-AGI-2 | Not measured | 4.4% | Only GPT-5 Mini measured |
| Chess puzzles | Not measured | 24.0% | Only GPT-5 Mini measured |
| Mystery game puzzles | Not measured | 10.0% | Only GPT-5 Mini measured |
| VPCT | Not measured | 40.2% | Only GPT-5 Mini measured |
| LMArena Text: hard prompts | 1443 | 1380 | GLM 5V Turbo |
| LMArena Text: expert | 1453 | 1379 | GLM 5V Turbo |
| LMArena Text: hard prompts in English | 1456 | 1383 | GLM 5V Turbo |
| LMArena Vision: diagrams | 1286 | 1202 | GLM 5V Turbo |
| LMArena Vision: homework | 1273 | 1210 | GLM 5V Turbo |
| Kagi LLM Benchmark | Not measured | 70.3% | Only GPT-5 Mini measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GLM 5V Turbo | GPT-5 Mini | Leader |
|---|---|---|---|
| AIME | Not measured | 91.5% | Only GPT-5 Mini measured |
| MATH 500 (Vals AI) | Not measured | 94.8% | Only GPT-5 Mini measured |
| MGSM (Vals AI) | Not measured | 92.6% | Only GPT-5 Mini measured |
| AA Math Index | Not measured | 90.7 | Only GPT-5 Mini measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 90.7% | Only GPT-5 Mini measured |
| OTIS Mock AIME | Not measured | 86.7% | Only GPT-5 Mini measured |
| FrontierMath, tiers 1 to 3 | Not measured | 46.7% | Only GPT-5 Mini measured |
| FrontierMath, tier 4 | Not measured | 12.2% | Only GPT-5 Mini measured |
| ProofBench | Not measured | 9.0% | Only GPT-5 Mini measured |
| MATH level 5 | Not measured | 97.8% | Only GPT-5 Mini measured |
| LMArena Text: math | 1442 | 1378 | GLM 5V Turbo |
| LMArena Text: mathematical work | 1447 | 1380 | GLM 5V Turbo |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GLM 5V Turbo | GPT-5 Mini | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 82.2% | Only GPT-5 Mini measured |
| LegalBench (Vals AI) | Not measured | 81.8% | Only GPT-5 Mini measured |
| CaseLaw (Vals AI) | Not measured | 68.5% | Only GPT-5 Mini measured |
| CorpFin (Vals AI) | Not measured | 60.2% | Only GPT-5 Mini measured |
| TaxEval (Vals AI) | Not measured | 75.2% | Only GPT-5 Mini measured |
| MortgageTax (Vals AI) | Not measured | 66.9% | Only GPT-5 Mini measured |
| MedQA (Vals AI) | Not measured | 96.1% | Only GPT-5 Mini measured |
| MedCode (Vals AI) | Not measured | 43.0% | Only GPT-5 Mini measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 83.7% | Only GPT-5 Mini measured |
| SimpleQA Verified | Not measured | 21.6% | Only GPT-5 Mini measured |
| LMArena Text: science | 1448 | 1371 | GLM 5V Turbo |
| LMArena Text: medicine and healthcare | 1433 | 1380 | GLM 5V Turbo |
| LMArena Text: legal and government | 1436 | 1375 | GLM 5V Turbo |
| LMArena Text: business and finance | 1435 | 1358 | GLM 5V Turbo |
| FACTS Benchmark Suite | Not measured | 38.6% | Only GPT-5 Mini measured |
| Neither model has a result on the other 3 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index71
| Benchmark | GLM 5V Turbo | GPT-5 Mini | Leader |
|---|---|---|---|
| Design Arena: websites | 1230 | 1125 | GLM 5V Turbo |
| Design Arena: UI components | 1210 | 1103 | GLM 5V Turbo |
| Design Arena: game dev | 1218 | 1129 | GLM 5V Turbo |
| Design Arena: data viz | 1202 | 1131 | GLM 5V Turbo |
| Design Arena: 3D | 1208 | 1036 | GLM 5V Turbo |
| Design Arena: all code categories | 1228 | 1114 | GLM 5V Turbo |
| Design Arena: SVG | 1151 | 1091 | GLM 5V Turbo |
| Design Arena: ASCII art | 1117 | 1125 | GPT-5 Mini |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index242
| Benchmark | GLM 5V Turbo | GPT-5 Mini | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 43.0% | Only GPT-5 Mini measured |
| MedScribe (Vals AI) | Not measured | 80.6% | Only GPT-5 Mini measured |
| IFBench | 61.1% | 75.4% | GPT-5 Mini |
| Long context reasoning (AA-LCR) | 70.3% | 72.3% | GPT-5 Mini |
| DTBench | Not measured | 80.5% | Only GPT-5 Mini measured |
| LMCA | Not measured | 34.2% | Only GPT-5 Mini measured |
| Fiction.LiveBench | Not measured | 69.4% | Only GPT-5 Mini measured |
| Creative writing (Lech Mazur) | Not measured | 83.1% | Only GPT-5 Mini measured |
| LMArena Text | 1437 | 1373 | GLM 5V Turbo |
| LMArena Text: instruction following | 1423 | 1357 | GLM 5V Turbo |
| LMArena Text: creative writing | 1417 | 1325 | GLM 5V Turbo |
| LMArena Vision | 1264 | 1202 | GLM 5V Turbo |
| LMArena Text: English | 1454 | 1379 | GLM 5V Turbo |
| LMArena Text: non-English | 1420 | 1363 | GLM 5V Turbo |
| LMArena Text: Chinese | 1491 | 1386 | GLM 5V Turbo |
| LMArena Text: German | 1422 | 1366 | GLM 5V Turbo |
| LMArena Text: Japanese | Not measured | 1341 | Only GPT-5 Mini measured |
| LMArena Text: Korean | 1397 | 1308 | GLM 5V Turbo |
| LMArena Text: French | 1443 | 1386 | GLM 5V Turbo |
| LMArena Text: Spanish | 1452 | 1354 | GLM 5V Turbo |
| LMArena Text: Russian | 1432 | 1362 | GLM 5V Turbo |
| LMArena Text: Polish | 1432 | 1378 | GLM 5V Turbo |
| LMArena Text: multi-turn | 1431 | 1363 | GLM 5V Turbo |
| LMArena Text: longer queries | 1438 | 1355 | GLM 5V Turbo |
| LMArena Text: writing and language | 1420 | 1344 | GLM 5V Turbo |
| LMArena Text: entertainment and media | 1407 | 1340 | GLM 5V Turbo |
| LMArena Vision: English | 1274 | 1216 | GLM 5V Turbo |
| LMArena Vision: Chinese | 1329 | 1214 | GLM 5V Turbo |
| LMArena Vision: reading text | 1270 | 1199 | GLM 5V Turbo |
| LMArena Vision: humor | 1268 | 1205 | GLM 5V Turbo |
| LMArena Vision: captioning | 1264 | 1217 | GLM 5V Turbo |
| LMArena Vision: recognizing things | 1241 | 1226 | GLM 5V Turbo |
| LMArena Vision: creative writing | 1252 | 1181 | GLM 5V Turbo |
| LMArena Document | 1416 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5V Turbo | GPT-5 Mini | 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
GPT-5 Mini costs less
Repository review
50K input + 3K output tokens
GPT-5 Mini costs less
Agent loop
200K input + 10K output tokens
GPT-5 Mini 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 | OpenAI GPT-5 Mini |
|---|---|---|
| Maker | Z.ai | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | April 1, 2026 | August 7, 2025 |
| Context window | 203K | 400K |
| Input $/Mtok | $1.20 | $0.25 |
| Output $/Mtok | $4.00 | $2.00 |
| Coding index | Not benchmarked | 34.2 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | Not computable | $0.08 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5V Turbo better than GPT-5 Mini for coding?
Only GPT-5 Mini has a coding score, 34.2 on the Vibe Coding Index; GLM 5V Turbo has none, so the two cannot be ranked on coding. Pick GLM 5V Turbo for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, GLM 5V Turbo or GPT-5 Mini?
GLM 5V Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; GPT-5 Mini costs $0.25 and $2.00. Cost per solved task is known for GPT-5 Mini only.
Which has the bigger context window, GLM 5V Turbo or GPT-5 Mini?
GPT-5 Mini, with 400K tokens against 203K.
How many benchmarks is the GLM 5V Turbo vs GPT-5 Mini comparison based on?
52 benchmarks have a result for both models as of October 22, 2026. GLM 5V Turbo's coding index rests on 1 independent benchmark and GPT-5 Mini's on 2. Where only one model has a result, the page says so instead of naming a winner.