GLM 5 Turbo vs Step 3.7 Flash
GLM 5 Turbo leads Step 3.7 Flash on the Artificial Analysis Intelligence Index, 26.6 to 19.5, and Step 3.7 Flash costs 3.5x less per output token ($1.15 vs $4.00 per million). Updated October 21, 2026; 16 benchmarks have a result for both.
GLM 5 Turbo or Step 3.7 Flash: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GLM 5 Turbo for work measured by Terminal-Bench Hard (Artificial Analysis run) or ALE-Bench, where it leads.
- Shared results
- 16
- GLM 5 Turbo only
- 0
- Step 3.7 Flash only
- 2
- Like-for-like categories
- 6 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 5 Turbo
GLM 5 Turbo leads, 26.6 against 19.5.
Same board, both measured
Web design
Design Arena: websites
GLM 5 Turbo
GLM 5 Turbo leads, 1262 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 5 Turbo $0.0032, Step 3.7 Flash $0.0008 per turn.
List prices
At a glance
- Coding index
- GLM 5 Turbo not benchmarked, Step 3.7 Flash not benchmarked.
- Widest category
- Web design, 10.3 points apart on average over 8 shared benchmarks.
- Widest single gap
- Design Arena: SVG: GLM 5 Turbo 1206 against Step 3.7 Flash 1085, 15.1 points apart on a 0 to 100 scale.
- Output price
- GLM 5 Turbo $4.00 against Step 3.7 Flash $1.15 per million output tokens, 3.5x apart.
- Context window
- GLM 5 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 5 Turbo | Bars | Step 3.7 Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 0 | 0 | 1 tie | |
| Reasoning | 2 | 0 | ||
| Web design | 8 | 0 | ||
| General | 1 | 1 | ||
| All shared boards | 12 | 3 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | GLM 5 Turbo | Step 3.7 Flash | Leader |
|---|---|---|---|
| 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) | 33.3% | 35.6% | Step 3.7 Flash |
| ALE-Bench | 634.0 | 694.1 | Step 3.7 Flash |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GLM 5 Turbo | Step 3.7 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 26.6 | 19.5 | GLM 5 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 5 Turbo | Step 3.7 Flash | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 98.5% | 98.5% | Tie |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GLM 5 Turbo | Step 3.7 Flash | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 84.7% | 80.9% | GLM 5 Turbo |
| Humanity's Last Exam (Artificial Analysis run) | 27.8% | 21.4% | GLM 5 Turbo |
| Neither model has a result on the other 19 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5 Turbo | Step 3.7 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5 Turbo | Step 3.7 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 17 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | GLM 5 Turbo | Step 3.7 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1262 | 1196 | GLM 5 Turbo |
| Design Arena: UI components | 1263 | 1179 | GLM 5 Turbo |
| Design Arena: game dev | 1248 | 1158 | GLM 5 Turbo |
| Design Arena: data viz | 1264 | 1172 | GLM 5 Turbo |
| Design Arena: 3D | 1248 | 1129 | GLM 5 Turbo |
| Design Arena: all code categories | 1262 | 1182 | GLM 5 Turbo |
| Design Arena: SVG | 1206 | 1085 | GLM 5 Turbo |
| Design Arena: ASCII art | 1160 | 1152 | GLM 5 Turbo |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GLM 5 Turbo | Step 3.7 Flash | Leader |
|---|---|---|---|
| IFBench | 73.2% | 67.3% | GLM 5 Turbo |
| Long context reasoning (AA-LCR) | 71.7% | 73.7% | Step 3.7 Flash |
| Neither model has a result on the other 44 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 5 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 5 Turbo | StepFun Step 3.7 Flash |
|---|---|---|
| Maker | Z.ai | StepFun |
| Weights | No public weights listed | Open weights |
| Released | March 15, 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 | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5 Turbo better than Step 3.7 Flash for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 5 Turbo for work measured by Terminal-Bench Hard (Artificial Analysis run) or ALE-Bench, where it leads.
Which is cheaper, GLM 5 Turbo or Step 3.7 Flash?
GLM 5 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 5 Turbo or Step 3.7 Flash?
Step 3.7 Flash, with 262K tokens against 203K.
How many benchmarks is the GLM 5 Turbo vs Step 3.7 Flash comparison based on?
16 benchmarks have a result for both models as of October 21, 2026. GLM 5 Turbo's coding index rests on 0 independent benchmarks and Step 3.7 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.