GLM 5V Turbo vs Step 3.7 Flash
Updated October 21, 2026. 15 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
GLM 5V Turbo has the edge where what matters is Terminal-Bench Hard (Artificial Analysis run) or Humanity's Last Exam (Artificial Analysis run), where it leads.
- Shared results
- 15
- GLM 5V Turbo only
- 50
- Step 3.7 Flash only
- 3
- Like-for-like categories
- 6 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, 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 19.5.
Same board, both measured
Web design
Design Arena: websites
GLM 5V Turbo
GLM 5V Turbo leads, 1230 against 1196.
Same board, both measured
Long documents
Listed context window
Step 3.7 Flash
Step 3.7 Flash takes 262K tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Step 3.7 Flash
GLM 5V Turbo $0.0032, Step 3.7 Flash $0.0008 per turn.
List prices
At a glance
- Coding index
- GLM 5V Turbo not benchmarked, Step 3.7 Flash not benchmarked.
- Widest category
- Web design, 6.0 points apart on average over 8 shared benchmarks.
- Widest single gap
- Design Arena: 3D: GLM 5V Turbo 1209 against Step 3.7 Flash 1129, 10.0 points apart on a 0 to 100 scale.
- Output price
- GLM 5V Turbo $4.00 against Step 3.7 Flash $1.15 per million output tokens, 3.5x apart.
- Context window
- GLM 5V Turbo takes 203K tokens, Step 3.7 Flash 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 | Step 3.7 Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 0 | 0 | 1 tie | |
| Reasoning | 0 | 1 | 1 tie | |
| Web design | 7 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 8 | 5 | 2 ties |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | GLM 5V Turbo | Step 3.7 Flash | Leader |
|---|---|---|---|
| LMArena WebDev | 1402 | Not measured | Only GLM 5V Turbo measured |
| AA Coding Index | Not measured | 39.6 | Only Step 3.7 Flash measured |
| SciCode | Not measured | 43.9% | Only Step 3.7 Flash measured |
| Terminal-Bench Hard (Artificial Analysis run) | 32.6% | 35.6% | Step 3.7 Flash |
| ALE-Bench | Not measured | 694.1 | Only Step 3.7 Flash measured |
| LMArena Text: coding | 1466 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: software and IT | 1460 | Not measured | Only GLM 5V Turbo measured |
| 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 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5V Turbo | Step 3.7 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.5 | 19.5 | 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 index00
| Benchmark | GLM 5V Turbo | Step 3.7 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% | 98.5% | Tie |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 5V Turbo | Step 3.7 Flash | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 80.9% | 80.9% | Tie |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | 21.4% | Step 3.7 Flash |
| LMArena Text: hard prompts | 1443 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: expert | 1453 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: hard prompts in English | 1456 | Not measured | Only GLM 5V Turbo measured |
| 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 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GLM 5V Turbo | Step 3.7 Flash | Leader |
|---|---|---|---|
| LMArena Text: math | 1442 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: mathematical work | 1447 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GLM 5V Turbo | Step 3.7 Flash | Leader |
|---|---|---|---|
| LMArena Text: science | 1448 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: medicine and healthcare | 1433 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: legal and government | 1436 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: business and finance | 1435 | Not measured | Only GLM 5V Turbo measured |
| Neither model has a result on the other 13 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index71
| Benchmark | GLM 5V Turbo | Step 3.7 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1230 | 1196 | GLM 5V Turbo |
| Design Arena: UI components | 1213 | 1179 | GLM 5V Turbo |
| Design Arena: game dev | 1219 | 1158 | GLM 5V Turbo |
| Design Arena: data viz | 1202 | 1172 | GLM 5V Turbo |
| Design Arena: 3D | 1209 | 1129 | GLM 5V Turbo |
| Design Arena: all code categories | 1228 | 1182 | GLM 5V Turbo |
| Design Arena: SVG | 1151 | 1085 | GLM 5V Turbo |
| Design Arena: ASCII art | 1118 | 1152 | Step 3.7 Flash |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GLM 5V Turbo | Step 3.7 Flash | Leader |
|---|---|---|---|
| IFBench | 61.1% | 67.3% | Step 3.7 Flash |
| Long context reasoning (AA-LCR) | 70.3% | 73.7% | Step 3.7 Flash |
| LMArena Text | 1437 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: instruction following | 1423 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: creative writing | 1417 | Not measured | Only GLM 5V Turbo measured |
| LMArena Vision | 1264 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: English | 1454 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: non-English | 1420 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: Chinese | 1491 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: German | 1422 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: Korean | 1397 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: French | 1443 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: Spanish | 1452 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: Russian | 1432 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: Polish | 1432 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: multi-turn | 1431 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: longer queries | 1438 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: writing and language | 1420 | Not measured | Only GLM 5V Turbo measured |
| LMArena Text: entertainment and media | 1407 | Not measured | Only GLM 5V Turbo measured |
| 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 19 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5V Turbo | Step 3.7 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
Step 3.7 Flash costs less
Repository review
50K input + 3K output tokens
Step 3.7 Flash costs less
Agent loop
200K input + 10K output tokens
Step 3.7 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 5V Turbo | StepFun Step 3.7 Flash |
|---|---|---|
| Maker | Z.ai | StepFun |
| Weights | No public weights listed | Open weights |
| Released | April 1, 2026 | May 28, 2026 |
| Context window | 203K | 262K |
| Input $/Mtok | $1.20 | $0.20 |
| Output $/Mtok | $4.00 | $1.15 |
| 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 Step 3.7 Flash for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. GLM 5V Turbo has the edge where what matters is Terminal-Bench Hard (Artificial Analysis run) or Humanity's Last Exam (Artificial Analysis run), where it leads.
Which is cheaper, GLM 5V Turbo or Step 3.7 Flash?
GLM 5V Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; Step 3.7 Flash costs $0.20 and $1.15. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 5V Turbo or Step 3.7 Flash?
Step 3.7 Flash, with 262K tokens against 203K.
How many benchmarks is the GLM 5V Turbo vs Step 3.7 Flash comparison based on?
15 benchmarks have a result for both models as of October 21, 2026. GLM 5V Turbo's coding index rests on 1 independent benchmark and Step 3.7 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.