Model comparison
GLM-4.5V vs Step 3.7 Flash
GLM-4.5V is the stronger model overall, scoring 39.8 to 37.3 on the Noometry Index. Step 3.7 Flash costs 2.2× less per token, which makes it the better buy when GLM-4.5V's lead doesn't matter for your workload.
Last verified . 0 shared benchmarks.
StepFunSummary
- The widest gap is in reasoning, where GLM-4.5V leads 27.4 to 21.6.
- Step 3.7 Flash is cheaper at $0.18 / $1.11 per million input/output tokens, against $0.60 / $1.80 for GLM-4.5V.
- Step 3.7 Flash accepts more context: 256K tokens versus 64K.
Side by side
| GLM-4.5V | Step 3.7 Flash | |
|---|---|---|
| Provider | Z.ai (Zhipu) | StepFun |
| Noometry Index | 39.8 | 37.3 |
| Released | 2025-08-11 | 2026-05-29 |
| Weights | Open | Open |
| Context window | 64K | 256K |
| Max output | 16K | 256K |
| Input $ / M tokens | $0.60 | $0.18 |
| Output $ / M tokens | $1.80 | $1.11 |
| Results tracked | 15 | 5 |
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Category by category
Coding Too close to call
GLM-4.5V: 39.5 (#155), Step 3.7 Flash: 40.0 (#150)
| Benchmark | GLM-4.5V | Step 3.7 Flash |
|---|---|---|
| SciCode | — | 40% |
| LMArena Coding | 1347 | — |
| ALE-Bench | — | 694.12 |
Reasoning GLM-4.5V leads
GLM-4.5V: 27.4 (#119), Step 3.7 Flash: 21.6 (#219)
| Benchmark | GLM-4.5V | Step 3.7 Flash |
|---|---|---|
| Kagi LLM Benchmark | 59.8% | — |
| NYT Connections (extended) | — | 39.7% |
| CritPt | — | 2.3% |
| LMArena Hard Prompts | 1334 | — |
Math Step 3.7 Flash leads
GLM-4.5V: 37.4 (#159), Step 3.7 Flash: 42.9 (#82)
| Benchmark | GLM-4.5V | Step 3.7 Flash |
|---|---|---|
| MathArena Final-Answer Competitions | — | 68.5% |
| LMArena Math | 1354 | — |
Knowledge Not comparable
GLM-4.5V: 37.5 (#156), Step 3.7 Flash: —
| Benchmark | GLM-4.5V | Step 3.7 Flash |
|---|---|---|
| LMArena Expert | 1353 | — |
Multimodal Not comparable
GLM-4.5V: 34.3 (#92), Step 3.7 Flash: —
| Benchmark | GLM-4.5V | Step 3.7 Flash |
|---|---|---|
| LMArena Vision | 1154 | — |
Multilingual Not comparable
GLM-4.5V: 44.6 (#177), Step 3.7 Flash: —
| Benchmark | GLM-4.5V | Step 3.7 Flash |
|---|---|---|
| LMArena Non-English | 1303 | — |
| LMArena Chinese | 1337 | — |
| LMArena Russian | 1298 | — |
| LMArena Spanish | 1336 | — |
Instruction Following Not comparable
GLM-4.5V: 69.2 (#175), Step 3.7 Flash: —
| Benchmark | GLM-4.5V | Step 3.7 Flash |
|---|---|---|
| LMArena Instruction Following | 1311 | — |
Long Context Not comparable
GLM-4.5V: 39.6 (#171), Step 3.7 Flash: —
| Benchmark | GLM-4.5V | Step 3.7 Flash |
|---|---|---|
| LMArena Longer Query | 1304 | — |
Writing & Preference Not comparable
GLM-4.5V: 52.5 (#170), Step 3.7 Flash: —
| Benchmark | GLM-4.5V | Step 3.7 Flash |
|---|---|---|
| LMArena Text | 1333 | — |
| LMArena Creative Writing | 1295 | — |
| LMArena Multi-Turn | 1332 | — |
Frequently asked questions
Is GLM-4.5V better than Step 3.7 Flash?
GLM-4.5V is the stronger model overall, scoring 39.8 to 37.3 on the Noometry Index. Step 3.7 Flash costs 2.2× less per token, which makes it the better buy when GLM-4.5V's lead doesn't matter for your workload.
Which is cheaper, GLM-4.5V or Step 3.7 Flash?
Step 3.7 Flash is cheaper. It lists at $0.18 per million input tokens and $1.11 per million output tokens; GLM-4.5V lists at $0.60 and $1.80.
Is GLM-4.5V or Step 3.7 Flash better for coding?
They score almost the same on coding (39.5 vs 40.0); test both on your own repository before choosing.
Which has the bigger context window?
Step 3.7 Flash does, with 256K tokens against 64K.
How many benchmarks do GLM-4.5V and Step 3.7 Flash share?
0 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and Step 3.7 Flash has 5.