GLM 5V Turbo vs Qwen3.5-Flash
Updated October 21, 2026. 30 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GLM 5V Turbo for coding: it scores 28.8 on the Vibe Coding Index against 6.2 for Qwen3.5-Flash.
Pick Qwen3.5-Flash when output tokens cost 15.4x less, or when the context window is larger, 1M against 203K tokens.
- Shared results
- 30
- GLM 5V Turbo only
- 35
- Qwen3.5-Flash only
- 25
- Like-for-like categories
- 5 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
GLM 5V Turbo
GLM 5V Turbo scores 28.8 against 6.2.
One benchmark behind each score
Intelligence
AA Intelligence Index
No call
Only GLM 5V Turbo has a AA Intelligence Index result, 23.5.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.5-Flash has a GPQA Diamond result, 82.8%.
Directional only
Math
AIME
No call
Only Qwen3.5-Flash has a AIME result, 92.5%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.5-Flash has a MMLU Pro result, 84.1%.
Directional only
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
Qwen3.5-Flash
Qwen3.5-Flash takes 1M tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5-Flash
GLM 5V Turbo $0.0032, Qwen3.5-Flash $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.5-Flash has the number, $0.40.
Directional only
At a glance
- Coding index
- GLM 5V Turbo 28.8 from 1 benchmark, Qwen3.5-Flash 6.2 from 1 benchmark.
- Widest category
- Coding, 15.2 points apart on average over 5 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: GLM 5V Turbo 1386 against Qwen3.5-Flash 1229, 26.2 points apart on a 0 to 100 scale.
- Output price
- GLM 5V Turbo $4.00 against Qwen3.5-Flash $0.26 per million output tokens, 15.4x apart.
- Context window
- GLM 5V Turbo takes 203K tokens, Qwen3.5-Flash 1M.
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 | Qwen3.5-Flash | Ties |
|---|---|---|---|---|
| Coding | 5 | 0 | ||
| Reasoning | 3 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 16 | 0 | ||
| All shared boards | 30 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index50
| Benchmark | GLM 5V Turbo | Qwen3.5-Flash | Leader |
|---|---|---|---|
| LMArena WebDev | 1402 | 1244 | GLM 5V Turbo |
| LiveCodeBench (Vals AI) | Not measured | 83.3% | Only Qwen3.5-Flash measured |
| SWE-bench Verified (Vals AI) | Not measured | 64.4% | Only Qwen3.5-Flash measured |
| Terminal-Bench Hard (Artificial Analysis run) | 32.6% | Not measured | Only GLM 5V Turbo measured |
| ALE-Bench | Not measured | 265.9 | Only Qwen3.5-Flash measured |
| LMArena Text: coding | 1466 | 1412 | GLM 5V Turbo |
| LMArena Text: software and IT | 1460 | 1416 | GLM 5V Turbo |
| LMArena WebDev: React | 1386 | 1229 | GLM 5V Turbo |
| LMArena WebDev: HTML | 1356 | 1291 | GLM 5V Turbo |
| LMArena WebDev: from an image | 1425 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GLM 5V Turbo | Qwen3.5-Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.5 | Not measured | Only GLM 5V Turbo measured |
| Epoch Capabilities Index | Not measured | 143.5 | Only Qwen3.5-Flash measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GLM 5V Turbo | Qwen3.5-Flash | 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% | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GLM 5V Turbo | Qwen3.5-Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 82.8% | Only Qwen3.5-Flash measured |
| MMMU Pro (Vals AI) | Not measured | 81.9% | Only Qwen3.5-Flash measured |
| GPQA Diamond (Artificial Analysis run) | 80.9% | Not measured | Only GLM 5V Turbo measured |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | Not measured | Only GLM 5V Turbo measured |
| GPQA Diamond (Epoch AI run) | Not measured | 82.3% | Only Qwen3.5-Flash measured |
| Chess puzzles | Not measured | 14.0% | Only Qwen3.5-Flash measured |
| Mystery game puzzles | Not measured | 20.0% | Only Qwen3.5-Flash measured |
| LMArena Text: hard prompts | 1443 | 1403 | GLM 5V Turbo |
| LMArena Text: expert | 1453 | 1407 | GLM 5V Turbo |
| LMArena Text: hard prompts in English | 1456 | 1409 | GLM 5V Turbo |
| LMArena Vision: diagrams | 1286 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: homework | 1273 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GLM 5V Turbo | Qwen3.5-Flash | Leader |
|---|---|---|---|
| AIME | Not measured | 92.5% | Only Qwen3.5-Flash measured |
| OTIS Mock AIME | Not measured | 84.4% | Only Qwen3.5-Flash measured |
| FrontierMath, tiers 1 to 3 | Not measured | 18.2% | Only Qwen3.5-Flash measured |
| LMArena Text: math | 1442 | 1407 | GLM 5V Turbo |
| LMArena Text: mathematical work | 1447 | 1413 | GLM 5V Turbo |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GLM 5V Turbo | Qwen3.5-Flash | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 84.1% | Only Qwen3.5-Flash measured |
| LegalBench (Vals AI) | Not measured | 84.3% | Only Qwen3.5-Flash measured |
| CaseLaw (Vals AI) | Not measured | 56.0% | Only Qwen3.5-Flash measured |
| CorpFin (Vals AI) | Not measured | 63.6% | Only Qwen3.5-Flash measured |
| TaxEval (Vals AI) | Not measured | 72.2% | Only Qwen3.5-Flash measured |
| MortgageTax (Vals AI) | Not measured | 67.4% | Only Qwen3.5-Flash measured |
| MedCode (Vals AI) | Not measured | 33.0% | Only Qwen3.5-Flash measured |
| SimpleQA Verified | Not measured | 20.3% | Only Qwen3.5-Flash measured |
| LMArena Text: science | 1448 | 1415 | GLM 5V Turbo |
| LMArena Text: medicine and healthcare | 1433 | 1407 | GLM 5V Turbo |
| LMArena Text: legal and government | 1436 | 1398 | GLM 5V Turbo |
| LMArena Text: business and finance | 1435 | 1394 | GLM 5V Turbo |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GLM 5V Turbo | Qwen3.5-Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1230 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: UI components | 1213 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: game dev | 1219 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: data viz | 1202 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: 3D | 1209 | Not measured | Only GLM 5V Turbo measured |
| Design Arena: all code categories | 1228 | Not measured | Only GLM 5V Turbo measured |
| 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 index160
| Benchmark | GLM 5V Turbo | Qwen3.5-Flash | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 42.5% | Only Qwen3.5-Flash measured |
| MedScribe (Vals AI) | Not measured | 70.6% | Only Qwen3.5-Flash measured |
| IFBench | 61.1% | Not measured | Only GLM 5V Turbo measured |
| Long context reasoning (AA-LCR) | 70.3% | Not measured | Only GLM 5V Turbo measured |
| DTBench | Not measured | 82.9% | Only Qwen3.5-Flash measured |
| LMCA | Not measured | 29.1% | Only Qwen3.5-Flash measured |
| LMArena Text | 1437 | 1397 | GLM 5V Turbo |
| LMArena Text: instruction following | 1423 | 1374 | GLM 5V Turbo |
| LMArena Text: creative writing | 1417 | 1343 | GLM 5V Turbo |
| LMArena Vision | 1264 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: English | 1454 | 1404 | GLM 5V Turbo |
| LMArena Text: non-English | 1420 | 1385 | GLM 5V Turbo |
| LMArena Text: Chinese | 1491 | 1445 | GLM 5V Turbo |
| LMArena Text: German | 1422 | 1390 | GLM 5V Turbo |
| LMArena Text: Japanese | Not measured | 1369 | Only Qwen3.5-Flash measured |
| LMArena Text: Korean | 1397 | 1344 | GLM 5V Turbo |
| LMArena Text: French | 1443 | 1413 | GLM 5V Turbo |
| LMArena Text: Spanish | 1452 | 1400 | GLM 5V Turbo |
| LMArena Text: Russian | 1432 | 1380 | GLM 5V Turbo |
| LMArena Text: Polish | 1432 | 1376 | GLM 5V Turbo |
| LMArena Text: multi-turn | 1431 | 1393 | GLM 5V Turbo |
| LMArena Text: longer queries | 1438 | 1392 | GLM 5V Turbo |
| LMArena Text: writing and language | 1420 | 1369 | GLM 5V Turbo |
| LMArena Text: entertainment and media | 1407 | 1347 | GLM 5V Turbo |
| LMArena Vision: English | 1274 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: Chinese | 1329 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: reading text | 1270 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision: humor | 1268 | Not measured | Only GLM 5V Turbo measured |
| 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 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5V Turbo | Qwen3.5-Flash | 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
Qwen3.5-Flash costs less
Repository review
50K input + 3K output tokens
Qwen3.5-Flash costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-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 5V Turbo | Qwen3.5-Flash |
|---|---|---|
| Maker | Z.ai | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | April 1, 2026 | February 25, 2026 |
| Context window | 203K | 1M |
| Input $/Mtok | $1.20 | $0.065 |
| Output $/Mtok | $4.00 | $0.26 |
| Coding index | 28.8 | 6.2 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | $0.40 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5V Turbo better than Qwen3.5-Flash for coding?
Pick GLM 5V Turbo for coding: it scores 28.8 on the Vibe Coding Index against 6.2 for Qwen3.5-Flash. Pick Qwen3.5-Flash when output tokens cost 15.4x less, or when the context window is larger, 1M against 203K tokens.
Which is cheaper, GLM 5V Turbo or Qwen3.5-Flash?
GLM 5V Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; Qwen3.5-Flash costs $0.065 and $0.26. Cost per solved task is known for Qwen3.5-Flash only.
Which has the bigger context window, GLM 5V Turbo or Qwen3.5-Flash?
Qwen3.5-Flash, with 1M tokens against 203K.
How many benchmarks is the GLM 5V Turbo vs Qwen3.5-Flash comparison based on?
30 benchmarks have a result for both models as of October 21, 2026. GLM 5V Turbo's coding index rests on 1 independent benchmark and Qwen3.5-Flash's on 1. Where only one model has a result, the page says so instead of naming a winner.