GLM 5V Turbo vs GPT-5 Nano
Updated October 21, 2026. 46 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GPT-5 Nano for coding: it scores 34.8 on the Vibe Coding Index against 28.8 for GLM 5V Turbo.
Pick GLM 5V Turbo when what matters is Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.
- Shared results
- 46
- GLM 5V Turbo only
- 19
- GPT-5 Nano only
- 39
- 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
GPT-5 Nano
GPT-5 Nano scores 34.8 against 28.8.
One benchmark behind each score
Intelligence
AA Intelligence Index
GLM 5V Turbo
GLM 5V Turbo leads, 23.5 against 13.0.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-5 Nano has a GPQA Diamond result, 63.4%.
Directional only
Math
AIME
No call
Only GPT-5 Nano has a AIME result, 81.2%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5 Nano has a MMLU Pro result, 76.1%.
Directional only
Web design
Design Arena: websites
GLM 5V Turbo
GLM 5V Turbo leads, 1230 against 1101.
Same board, both measured
Long documents
Listed context window
GPT-5 Nano
GPT-5 Nano takes 400K tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5 Nano
GLM 5V Turbo $0.0032, GPT-5 Nano $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5 Nano has the number, $0.109.
Directional only
At a glance
- Coding index
- GLM 5V Turbo 28.8 from 1 benchmark, GPT-5 Nano 34.8 from 1 benchmark.
- Widest category
- Agentic work, 62.0 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: GLM 5V Turbo 98.5% against GPT-5 Nano 36.5%, 62.0 points apart on a 0 to 100 scale.
- Output price
- GLM 5V Turbo $4.00 against GPT-5 Nano $0.40 per million output tokens, 10.0x apart.
- Context window
- GLM 5V Turbo takes 203K tokens, GPT-5 Nano 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 Nano | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 7 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| Web design | 6 | 0 | ||
| General | 21 | 1 | ||
| All shared boards | 45 | 1 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index30
| Benchmark | GLM 5V Turbo | GPT-5 Nano | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 34.8% | Only GPT-5 Nano measured |
| LMArena WebDev | 1402 | Not measured | Only GLM 5V Turbo measured |
| LiveCodeBench (Vals AI) | Not measured | 70.2% | Only GPT-5 Nano measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 78.9% | Only GPT-5 Nano measured |
| Terminal-Bench Hard (Artificial Analysis run) | 32.6% | 17.4% | GLM 5V Turbo |
| Terminal-Bench | Not measured | 21.8% | Only GPT-5 Nano measured |
| WeirdML | Not measured | 38.1% | Only GPT-5 Nano measured |
| LMArena Text: coding | 1466 | 1351 | GLM 5V Turbo |
| LMArena Text: software and IT | 1460 | 1345 | 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 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5V Turbo | GPT-5 Nano | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.5 | 13.0 | GLM 5V Turbo |
| Epoch Capabilities Index | Not measured | 139.2 | Only GPT-5 Nano measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5V Turbo | GPT-5 Nano | 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 | 1120 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: PowerPoint slides | 1152 | Not measured | Only GLM 5V Turbo measured |
| τ²-Bench Telecom | 98.5% | 36.5% | GLM 5V Turbo |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | GLM 5V Turbo | GPT-5 Nano | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 63.4% | Only GPT-5 Nano measured |
| MMMU Pro (Vals AI) | Not measured | 70.9% | Only GPT-5 Nano measured |
| GPQA Diamond (Artificial Analysis run) | 80.9% | 67.6% | GLM 5V Turbo |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | 9.5% | GLM 5V Turbo |
| GPQA Diamond (Epoch AI run) | Not measured | 69.4% | Only GPT-5 Nano measured |
| ARC-AGI | Not measured | 20.7% | Only GPT-5 Nano measured |
| ARC-AGI-2 | Not measured | 2.6% | Only GPT-5 Nano measured |
| Chess puzzles | Not measured | 22.0% | Only GPT-5 Nano measured |
| Mystery game puzzles | Not measured | 9.0% | Only GPT-5 Nano measured |
| VPCT | Not measured | 37.2% | Only GPT-5 Nano measured |
| LMArena Text: hard prompts | 1443 | 1328 | GLM 5V Turbo |
| LMArena Text: expert | 1453 | 1321 | GLM 5V Turbo |
| LMArena Text: hard prompts in English | 1456 | 1338 | GLM 5V Turbo |
| LMArena Vision: diagrams | 1286 | 1141 | GLM 5V Turbo |
| LMArena Vision: homework | 1273 | 1157 | GLM 5V Turbo |
| 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 Nano | Leader |
|---|---|---|---|
| AIME | Not measured | 81.2% | Only GPT-5 Nano measured |
| MATH 500 (Vals AI) | Not measured | 93.8% | Only GPT-5 Nano measured |
| MGSM (Vals AI) | Not measured | 89.3% | Only GPT-5 Nano measured |
| AA Math Index | Not measured | 83.7 | Only GPT-5 Nano measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 83.7% | Only GPT-5 Nano measured |
| OTIS Mock AIME | Not measured | 81.1% | Only GPT-5 Nano measured |
| FrontierMath, tiers 1 to 3 | Not measured | 20.0% | Only GPT-5 Nano measured |
| FrontierMath, tier 4 | Not measured | 2.4% | Only GPT-5 Nano measured |
| ProofBench | Not measured | 12.0% | Only GPT-5 Nano measured |
| MATH level 5 | Not measured | 95.2% | Only GPT-5 Nano measured |
| LMArena Text: math | 1442 | 1317 | GLM 5V Turbo |
| LMArena Text: mathematical work | 1447 | 1326 | 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 Nano | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 76.1% | Only GPT-5 Nano measured |
| LegalBench (Vals AI) | Not measured | 50.1% | Only GPT-5 Nano measured |
| CaseLaw (Vals AI) | Not measured | 52.6% | Only GPT-5 Nano measured |
| TaxEval (Vals AI) | Not measured | 67.4% | Only GPT-5 Nano measured |
| MortgageTax (Vals AI) | Not measured | 53.6% | Only GPT-5 Nano measured |
| MedQA (Vals AI) | Not measured | 93.3% | Only GPT-5 Nano measured |
| MedCode (Vals AI) | Not measured | 30.4% | Only GPT-5 Nano measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 78.0% | Only GPT-5 Nano measured |
| SimpleQA Verified | Not measured | 11.7% | Only GPT-5 Nano measured |
| LMArena Text: science | 1448 | 1318 | GLM 5V Turbo |
| LMArena Text: medicine and healthcare | 1433 | 1335 | GLM 5V Turbo |
| LMArena Text: legal and government | 1436 | 1298 | GLM 5V Turbo |
| LMArena Text: business and finance | 1435 | 1311 | GLM 5V Turbo |
| Neither model has a result on the other 4 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | GLM 5V Turbo | GPT-5 Nano | Leader |
|---|---|---|---|
| Design Arena: websites | 1230 | 1101 | GLM 5V Turbo |
| Design Arena: UI components | 1213 | 1066 | GLM 5V Turbo |
| Design Arena: game dev | 1219 | 1045 | GLM 5V Turbo |
| Design Arena: data viz | 1202 | 1056 | GLM 5V Turbo |
| Design Arena: 3D | 1209 | 966 | GLM 5V Turbo |
| Design Arena: all code categories | 1228 | 1084 | GLM 5V Turbo |
| Design Arena: SVG | 1151 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: ASCII art | 1118 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index211
| Benchmark | GLM 5V Turbo | GPT-5 Nano | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 30.4% | Only GPT-5 Nano measured |
| MedScribe (Vals AI) | Not measured | 72.9% | Only GPT-5 Nano measured |
| IFBench | 61.1% | 67.6% | GPT-5 Nano |
| Long context reasoning (AA-LCR) | 70.3% | 45.0% | GLM 5V Turbo |
| DTBench | Not measured | 62.7% | Only GPT-5 Nano measured |
| LMCA | Not measured | 7.9% | Only GPT-5 Nano measured |
| Fiction.LiveBench | Not measured | 44.4% | Only GPT-5 Nano measured |
| LMArena Text | 1437 | 1320 | GLM 5V Turbo |
| LMArena Text: instruction following | 1423 | 1306 | GLM 5V Turbo |
| LMArena Text: creative writing | 1417 | 1249 | GLM 5V Turbo |
| LMArena Vision | 1264 | 1159 | GLM 5V Turbo |
| LMArena Text: English | 1454 | 1321 | GLM 5V Turbo |
| LMArena Text: non-English | 1420 | 1313 | GLM 5V Turbo |
| LMArena Text: Chinese | 1491 | 1356 | GLM 5V Turbo |
| LMArena Text: German | 1422 | 1327 | GLM 5V Turbo |
| LMArena Text: Japanese | Not measured | 1227 | Only GPT-5 Nano measured |
| LMArena Text: Korean | 1397 | 1269 | GLM 5V Turbo |
| LMArena Text: French | 1443 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: Spanish | 1452 | 1360 | GLM 5V Turbo |
| LMArena Text: Russian | 1432 | 1296 | GLM 5V Turbo |
| LMArena Text: Polish | 1432 | 1314 | GLM 5V Turbo |
| LMArena Text: multi-turn | 1431 | 1311 | GLM 5V Turbo |
| LMArena Text: longer queries | 1438 | 1312 | GLM 5V Turbo |
| LMArena Text: writing and language | 1420 | 1283 | GLM 5V Turbo |
| LMArena Text: entertainment and media | 1407 | 1268 | GLM 5V Turbo |
| LMArena Vision: English | 1274 | 1170 | GLM 5V Turbo |
| LMArena Vision: Chinese | 1329 | 1176 | GLM 5V Turbo |
| LMArena Vision: reading text | 1270 | 1152 | GLM 5V Turbo |
| LMArena Vision: humor | 1268 | 1110 | GLM 5V Turbo |
| LMArena Vision: captioning | 1264 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: recognizing things | 1241 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: creative writing | 1252 | Not measured | Only GLM 5V Turbo measured |
| LMArena Document | 1416 | Not measured | Only GLM 5V Turbo 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 5V Turbo | GPT-5 Nano | 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 Nano costs less
Repository review
50K input + 3K output tokens
GPT-5 Nano costs less
Agent loop
200K input + 10K output tokens
GPT-5 Nano 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 Nano |
|---|---|---|
| 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 | $0.05 |
| Output $/Mtok | $4.00 | $0.40 |
| Coding index | 28.8 | 34.8 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | $0.109 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5V Turbo better than GPT-5 Nano for coding?
Pick GPT-5 Nano for coding: it scores 34.8 on the Vibe Coding Index against 28.8 for GLM 5V Turbo. Pick GLM 5V Turbo when what matters is Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.
Which is cheaper, GLM 5V Turbo or GPT-5 Nano?
GLM 5V Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; GPT-5 Nano costs $0.05 and $0.40. Cost per solved task is known for GPT-5 Nano only.
Which has the bigger context window, GLM 5V Turbo or GPT-5 Nano?
GPT-5 Nano, with 400K tokens against 203K.
How many benchmarks is the GLM 5V Turbo vs GPT-5 Nano comparison based on?
46 benchmarks have a result for both models as of October 21, 2026. GLM 5V Turbo's coding index rests on 1 independent benchmark and GPT-5 Nano's on 1. Where only one model has a result, the page says so instead of naming a winner.