GLM 5V Turbo vs Qwen3 VL 235B A22B Instruct
GLM 5V Turbo leads Qwen3 VL 235B A22B Instruct on the Artificial Analysis Intelligence Index, 23.5 to 9.9, and Qwen3 VL 235B A22B Instruct costs 2.1x less per output token ($1.90 vs $4.00 per million). Updated October 22, 2026; 44 benchmarks have a result for both.
GLM 5V Turbo or Qwen3 VL 235B A22B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GLM 5V Turbo for work measured by LMArena Vision: homework or LMArena Text: legal and government, where it leads.
- Shared results
- 44
- GLM 5V Turbo only
- 21
- Qwen3 VL 235B A22B Instruct only
- 5
- Like-for-like categories
- 7 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 9.9.
Same board, both measured
Web design
Design Arena: websites
No call
Only GLM 5V Turbo has a Design Arena: websites result, 1230.
Directional only
Long documents
Listed context window
Qwen3 VL 235B A22B Instruct
Qwen3 VL 235B A22B Instruct takes 262K tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 VL 235B A22B Instruct
GLM 5V Turbo $0.0032, Qwen3 VL 235B A22B Instruct $0.0012 per turn.
List prices
At a glance
- Coding index
- GLM 5V Turbo not benchmarked, Qwen3 VL 235B A22B Instruct not benchmarked.
- Widest category
- Agentic work, 44.4 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: GLM 5V Turbo 98.5% against Qwen3 VL 235B A22B Instruct 54.1%, 44.4 points apart on a 0 to 100 scale.
- Output price
- GLM 5V Turbo $4.00 against Qwen3 VL 235B A22B Instruct $1.90 per million output tokens, 2.1x apart.
- Context window
- GLM 5V Turbo takes 203K tokens, Qwen3 VL 235B A22B Instruct 262K.
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 | Qwen3 VL 235B A22B Instruct | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 6 | 1 | ||
| Math | 2 | 0 | ||
| Knowledge | 3 | 1 | ||
| General | 22 | 4 | ||
| All shared boards | 38 | 6 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
| Benchmark | GLM 5V Turbo | Qwen3 VL 235B A22B Instruct | Leader |
|---|---|---|---|
| LMArena WebDev | 1402 | Not measured | Only GLM 5V Turbo measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 64.6% | Only Qwen3 VL 235B A22B Instruct measured |
| Terminal-Bench Hard (Artificial Analysis run) | 32.6% | 11.4% | GLM 5V Turbo |
| LMArena Text: coding | 1466 | 1438 | GLM 5V Turbo |
| LMArena Text: software and IT | 1460 | 1442 | 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 35 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5V Turbo | Qwen3 VL 235B A22B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.5 | 9.9 | 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 5V Turbo | Qwen3 VL 235B A22B Instruct | 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 | 1060 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: PowerPoint slides | 1126 | Not measured | Only GLM 5V Turbo measured |
| τ²-Bench Telecom | 98.5% | 54.1% | GLM 5V Turbo |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index61
| Benchmark | GLM 5V Turbo | Qwen3 VL 235B A22B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 80.9% | 77.2% | GLM 5V Turbo |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | 11.9% | GLM 5V Turbo |
| LMArena Text: hard prompts | 1443 | 1428 | GLM 5V Turbo |
| LMArena Text: expert | 1453 | 1442 | GLM 5V Turbo |
| LMArena Text: hard prompts in English | 1456 | 1439 | GLM 5V Turbo |
| LMArena Vision: diagrams | 1286 | 1255 | GLM 5V Turbo |
| LMArena Vision: homework | 1273 | 1277 | Qwen3 VL 235B A22B Instruct |
| Neither model has a result on the other 16 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GLM 5V Turbo | Qwen3 VL 235B A22B Instruct | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 88.3 | Only Qwen3 VL 235B A22B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 88.3% | Only Qwen3 VL 235B A22B Instruct measured |
| LMArena Text: math | 1442 | 1425 | GLM 5V Turbo |
| LMArena Text: mathematical work | 1447 | 1419 | 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 index31
| Benchmark | GLM 5V Turbo | Qwen3 VL 235B A22B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 83.6% | Only Qwen3 VL 235B A22B Instruct measured |
| LMArena Text: science | 1448 | 1444 | GLM 5V Turbo |
| LMArena Text: medicine and healthcare | 1433 | 1431 | GLM 5V Turbo |
| LMArena Text: legal and government | 1436 | 1438 | Qwen3 VL 235B A22B Instruct |
| LMArena Text: business and finance | 1435 | 1433 | GLM 5V Turbo |
| Neither model has a result on the other 15 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GLM 5V Turbo | Qwen3 VL 235B A22B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 1230 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: UI components | 1210 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: game dev | 1218 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: data viz | 1202 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: 3D | 1208 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: all code categories | 1227 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: SVG | 1150 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: ASCII art | 1116 | 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 index224
| Benchmark | GLM 5V Turbo | Qwen3 VL 235B A22B Instruct | Leader |
|---|---|---|---|
| IFBench | 61.1% | 56.5% | GLM 5V Turbo |
| Long context reasoning (AA-LCR) | 70.3% | 63.7% | GLM 5V Turbo |
| LMArena Text | 1437 | 1420 | GLM 5V Turbo |
| LMArena Text: instruction following | 1423 | 1406 | GLM 5V Turbo |
| LMArena Text: creative writing | 1417 | 1366 | GLM 5V Turbo |
| LMArena Vision | 1264 | 1247 | GLM 5V Turbo |
| LMArena Text: English | 1454 | 1429 | GLM 5V Turbo |
| LMArena Text: non-English | 1420 | 1405 | GLM 5V Turbo |
| LMArena Text: Chinese | 1491 | 1463 | GLM 5V Turbo |
| LMArena Text: German | 1422 | 1424 | Qwen3 VL 235B A22B Instruct |
| LMArena Text: Japanese | Not measured | 1385 | Only Qwen3 VL 235B A22B Instruct measured |
| LMArena Text: Korean | 1397 | 1394 | GLM 5V Turbo |
| LMArena Text: French | 1443 | 1452 | Qwen3 VL 235B A22B Instruct |
| LMArena Text: Spanish | 1452 | 1428 | GLM 5V Turbo |
| LMArena Text: Russian | 1432 | 1408 | GLM 5V Turbo |
| LMArena Text: Polish | 1432 | 1419 | GLM 5V Turbo |
| LMArena Text: multi-turn | 1431 | 1428 | GLM 5V Turbo |
| LMArena Text: longer queries | 1438 | 1419 | GLM 5V Turbo |
| LMArena Text: writing and language | 1420 | 1392 | GLM 5V Turbo |
| LMArena Text: entertainment and media | 1407 | 1368 | GLM 5V Turbo |
| LMArena Vision: English | 1274 | 1256 | GLM 5V Turbo |
| LMArena Vision: Chinese | 1329 | 1283 | GLM 5V Turbo |
| LMArena Vision: reading text | 1270 | 1253 | GLM 5V Turbo |
| LMArena Vision: humor | 1268 | 1209 | GLM 5V Turbo |
| LMArena Vision: captioning | 1264 | 1281 | Qwen3 VL 235B A22B Instruct |
| LMArena Vision: recognizing things | 1241 | 1249 | Qwen3 VL 235B A22B Instruct |
| LMArena Vision: creative writing | 1252 | 1220 | GLM 5V Turbo |
| LMArena Document | 1416 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5V Turbo | Qwen3 VL 235B A22B Instruct | 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
Qwen3 VL 235B A22B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen3 VL 235B A22B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen3 VL 235B A22B Instruct 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 | Qwen3 VL 235B A22B Instruct |
|---|---|---|
| Maker | Z.ai | Qwen |
| Weights | No public weights listed | Open weights |
| Released | April 1, 2026 | September 23, 2025 |
| Context window | 203K | 262K |
| Input $/Mtok | $1.20 | $0.21 |
| Output $/Mtok | $4.00 | $1.90 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5V Turbo better than Qwen3 VL 235B A22B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 5V Turbo for work measured by LMArena Vision: homework or LMArena Text: legal and government, where it leads.
Which is cheaper, GLM 5V Turbo or Qwen3 VL 235B A22B Instruct?
GLM 5V Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; Qwen3 VL 235B A22B Instruct costs $0.21 and $1.90. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 5V Turbo or Qwen3 VL 235B A22B Instruct?
Qwen3 VL 235B A22B Instruct, with 262K tokens against 203K.
How many benchmarks is the GLM 5V Turbo vs Qwen3 VL 235B A22B Instruct comparison based on?
44 benchmarks have a result for both models as of October 22, 2026. GLM 5V Turbo's coding index rests on 1 independent benchmark and Qwen3 VL 235B A22B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.