GLM 4.7 Flash vs GLM 5V Turbo
GLM 5V Turbo leads GLM 4.7 Flash on the Artificial Analysis Intelligence Index, 23.5 to 14.9, and GLM 4.7 Flash costs 10.0x less per output token ($0.40 vs $4.00 per million). Updated October 21, 2026; 41 benchmarks have a result for both.
GLM 4.7 Flash or GLM 5V Turbo: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GLM 4.7 Flash for output tokens 10.0x cheaper ($0.40 vs $4.00 per million) and work measured by Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.
- Shared results
- 41
- GLM 4.7 Flash only
- 2
- GLM 5V Turbo only
- 24
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
GLM 5V Turbo
GLM 5V Turbo leads, 23.5 against 14.9.
Same board, both measured
Web design
Design Arena: websites
GLM 5V Turbo
GLM 5V Turbo leads, 1230 against 1194.
Same board, both measured
Long documents
Listed context window
GLM 5V Turbo
GLM 5V Turbo takes 203K tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 4.7 Flash
GLM 4.7 Flash $0.0003, GLM 5V Turbo $0.0032 per turn.
List prices
At a glance
- Coding index
- GLM 4.7 Flash not benchmarked, GLM 5V Turbo not benchmarked.
- Widest category
- General, 16.5 points apart on average over 18 shared benchmarks.
- Widest single gap
- Long context reasoning (AA-LCR): GLM 4.7 Flash 41.7% against GLM 5V Turbo 70.3%, 28.7 points apart on a 0 to 100 scale.
- Output price
- GLM 4.7 Flash $0.40 against GLM 5V Turbo $4.00 per million output tokens, 10.0x apart.
- Context window
- GLM 4.7 Flash takes 200K tokens, GLM 5V Turbo 203K.
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 4.7 Flash | Bars | GLM 5V Turbo | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 7 | ||
| General | 0 | 18 | ||
| All shared boards | 1 | 40 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | GLM 4.7 Flash | GLM 5V Turbo | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1402 | Only GLM 5V Turbo measured |
| Terminal-Bench Hard (Artificial Analysis run) | 22.0% | 32.6% | GLM 5V Turbo |
| LMArena Text: coding | 1382 | 1466 | GLM 5V Turbo |
| LMArena Text: software and IT | 1389 | 1460 | GLM 5V Turbo |
| LMArena WebDev: React | Not measured | 1386 | Only GLM 5V Turbo measured |
| LMArena WebDev: HTML | Not measured | 1356 | Only GLM 5V Turbo measured |
| LMArena WebDev: from an image | Not measured | 1425 | Only GLM 5V Turbo measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 4.7 Flash | GLM 5V Turbo | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.9 | 23.5 | GLM 5V Turbo |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 4.7 Flash | GLM 5V Turbo | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1124 | Only GLM 5V Turbo measured |
| Design Arena: agents building full-stack apps | Not measured | 1149 | Only GLM 5V Turbo measured |
| Design Arena: agents building mobile apps | Not measured | 1134 | Only GLM 5V Turbo measured |
| Design Arena: agents building Android apps | Not measured | 1267 | Only GLM 5V Turbo measured |
| Design Arena: agents building Godot games | Not measured | 957 | Only GLM 5V Turbo measured |
| Design Arena: agents building games | Not measured | 1102 | Only GLM 5V Turbo measured |
| Design Arena: HTML slides | Not measured | 1120 | Only GLM 5V Turbo measured |
| Design Arena: PowerPoint slides | Not measured | 1152 | Only GLM 5V Turbo measured |
| τ²-Bench Telecom | 98.8% | 98.5% | GLM 4.7 Flash |
| Neither model has a result on the other 32 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | GLM 4.7 Flash | GLM 5V Turbo | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 58.1% | 80.9% | GLM 5V Turbo |
| Humanity's Last Exam (Artificial Analysis run) | 7.6% | 17.1% | GLM 5V Turbo |
| GPQA Diamond (Epoch AI run) | 60.5% | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: hard prompts | 1356 | 1443 | GLM 5V Turbo |
| LMArena Text: expert | 1357 | 1453 | GLM 5V Turbo |
| LMArena Text: hard prompts in English | 1369 | 1456 | GLM 5V Turbo |
| LMArena Vision: diagrams | Not measured | 1286 | Only GLM 5V Turbo measured |
| LMArena Vision: homework | Not measured | 1273 | Only GLM 5V Turbo measured |
| Neither model has a result on the other 14 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GLM 4.7 Flash | GLM 5V Turbo | Leader |
|---|---|---|---|
| OTIS Mock AIME | 58.3% | Not measured | Only GLM 4.7 Flash measured |
| LMArena Text: math | 1355 | 1442 | GLM 5V Turbo |
| LMArena Text: mathematical work | 1369 | 1447 | GLM 5V Turbo |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GLM 4.7 Flash | GLM 5V Turbo | Leader |
|---|---|---|---|
| LMArena Text: science | 1358 | 1448 | GLM 5V Turbo |
| LMArena Text: medicine and healthcare | 1343 | 1433 | GLM 5V Turbo |
| LMArena Text: legal and government | 1357 | 1436 | GLM 5V Turbo |
| LMArena Text: business and finance | 1343 | 1435 | GLM 5V Turbo |
| Neither model has a result on the other 14 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | GLM 4.7 Flash | GLM 5V Turbo | Leader |
|---|---|---|---|
| Design Arena: websites | 1194 | 1230 | GLM 5V Turbo |
| Design Arena: UI components | 1208 | 1213 | GLM 5V Turbo |
| Design Arena: game dev | 1135 | 1219 | GLM 5V Turbo |
| Design Arena: data viz | 1123 | 1202 | GLM 5V Turbo |
| Design Arena: 3D | 1121 | 1209 | GLM 5V Turbo |
| Design Arena: all code categories | 1178 | 1228 | GLM 5V Turbo |
| Design Arena: SVG | 1038 | 1151 | GLM 5V Turbo |
| Design Arena: ASCII art | Not measured | 1117 | 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 index018
| Benchmark | GLM 4.7 Flash | GLM 5V Turbo | Leader |
|---|---|---|---|
| IFBench | 60.8% | 61.1% | GLM 5V Turbo |
| Long context reasoning (AA-LCR) | 41.7% | 70.3% | GLM 5V Turbo |
| LMArena Text | 1351 | 1437 | GLM 5V Turbo |
| LMArena Text: instruction following | 1327 | 1423 | GLM 5V Turbo |
| LMArena Text: creative writing | 1296 | 1417 | GLM 5V Turbo |
| LMArena Vision | Not measured | 1264 | Only GLM 5V Turbo measured |
| LMArena Text: English | 1373 | 1454 | GLM 5V Turbo |
| LMArena Text: non-English | 1330 | 1420 | GLM 5V Turbo |
| LMArena Text: Chinese | 1403 | 1491 | GLM 5V Turbo |
| LMArena Text: German | 1336 | 1422 | GLM 5V Turbo |
| LMArena Text: Korean | 1283 | 1397 | GLM 5V Turbo |
| LMArena Text: French | 1332 | 1443 | GLM 5V Turbo |
| LMArena Text: Spanish | 1350 | 1452 | GLM 5V Turbo |
| LMArena Text: Russian | 1333 | 1432 | GLM 5V Turbo |
| LMArena Text: Polish | 1291 | 1432 | GLM 5V Turbo |
| LMArena Text: multi-turn | 1342 | 1431 | GLM 5V Turbo |
| LMArena Text: longer queries | 1345 | 1438 | GLM 5V Turbo |
| LMArena Text: writing and language | 1320 | 1420 | GLM 5V Turbo |
| LMArena Text: entertainment and media | 1304 | 1407 | GLM 5V Turbo |
| LMArena Vision: English | Not measured | 1274 | Only GLM 5V Turbo measured |
| LMArena Vision: Chinese | Not measured | 1329 | Only GLM 5V Turbo measured |
| LMArena Vision: reading text | Not measured | 1270 | Only GLM 5V Turbo measured |
| LMArena Vision: humor | Not measured | 1268 | Only GLM 5V Turbo measured |
| LMArena Vision: captioning | Not measured | 1264 | Only GLM 5V Turbo measured |
| LMArena Vision: recognizing things | Not measured | 1241 | Only GLM 5V Turbo measured |
| LMArena Vision: creative writing | Not measured | 1252 | Only GLM 5V Turbo measured |
| LMArena Document | Not measured | 1416 | Only GLM 5V Turbo measured |
| Neither model has a result on the other 19 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 4.7 Flash | GLM 5V Turbo | 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
GLM 4.7 Flash costs less
Repository review
50K input + 3K output tokens
GLM 4.7 Flash costs less
Agent loop
200K input + 10K output tokens
GLM 4.7 Flash 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 4.7 Flash | Z.ai GLM 5V Turbo |
|---|---|---|
| Maker | Z.ai | Z.ai |
| Weights | Open weights | No public weights listed |
| Released | January 19, 2026 | April 1, 2026 |
| Context window | 200K | 203K |
| Input $/Mtok | $0.0653 | $1.20 |
| Output $/Mtok | $0.40 | $4.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 4.7 Flash better than GLM 5V Turbo for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.7 Flash for output tokens 10.0x cheaper ($0.40 vs $4.00 per million) and work measured by Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.
Which is cheaper, GLM 4.7 Flash or GLM 5V Turbo?
GLM 4.7 Flash costs $0.0653 per million input tokens and $0.40 per million output tokens; GLM 5V Turbo costs $1.20 and $4.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 4.7 Flash or GLM 5V Turbo?
GLM 5V Turbo, with 203K tokens against 200K.
How many benchmarks is the GLM 4.7 Flash vs GLM 5V Turbo comparison based on?
41 benchmarks have a result for both models as of October 21, 2026. GLM 4.7 Flash's coding index rests on 0 independent benchmarks and GLM 5V Turbo's on 1. Where only one model has a result, the page says so instead of naming a winner.