Model comparison

GLM-5 vs Step 3.7 Flash

GLM-5 is the stronger model overall, scoring 46.1 to 37.3 on the Noometry Index. Step 3.7 Flash costs 3.7× less per token, which makes it the better buy when GLM-5's lead doesn't matter for your workload.

Last verified . 3 shared benchmarks.

GLM-5 Z.ai (Zhipu)

46.1

Rank #66 Confirmed

Step 3.7 Flash StepFun

37.3

Rank #207 Reported

Summary

  • They share 3 benchmarks with published results for both. GLM-5 scores higher in 3 categories and Step 3.7 Flash in 0 categories; 3 gaps are clear of the uncertainty.
  • The widest gap is in coding, where GLM-5 leads 49.0 to 40.0.
  • The biggest single-benchmark swing is NYT Connections (extended): 74.8% for GLM-5 and 39.7% for Step 3.7 Flash.
  • Step 3.7 Flash is cheaper at $0.18 / $1.11 per million input/output tokens, against $1 / $3.20 for GLM-5.
  • Step 3.7 Flash accepts more context: 256K tokens versus 205K.

Side by side

GLM-5 and Step 3.7 Flash specifications
GLM-5Step 3.7 Flash
ProviderZ.ai (Zhipu)StepFun
Noometry Index46.137.3
Released2026-02-112026-05-29
WeightsOpenOpen
Context window205K256K
Max output131K256K
Input $ / M tokens$1$0.18
Output $ / M tokens$3.20$1.11
Results tracked455

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Category by category

Coding GLM-5 leads

GLM-5: 49.0 (#52), Step 3.7 Flash: 40.0 (#150)

Coding benchmarks
BenchmarkGLM-5Step 3.7 Flash
ALE-Bench765.62694.12
SWE-bench Verified72.1%—
SWE-bench Verified (bash only)72.8%—
LMArena WebDev1434—
SWE-bench Multilingual69.7%—
SciCode—40%
WeirdML48.2%—
LMArena Coding1461—

Agentic & Tool Use Not comparable

GLM-5: 31.1 (#71), Step 3.7 Flash: —

Agentic & Tool Use benchmarks
BenchmarkGLM-5Step 3.7 Flash
Terminal-Bench52.4%—
τ²-bench Airline82.5%—
τ²-bench Banking9.8%—
τ²-bench Retail73.7%—
τ²-bench Telecom86.8%—
Vending-Bench 24,432—

Reasoning GLM-5 leads

GLM-5: 27.6 (#116), Step 3.7 Flash: 21.6 (#219)

Reasoning benchmarks
BenchmarkGLM-5Step 3.7 Flash
NYT Connections (extended)74.8%39.7%
ARC-AGI-24.9%—
SimpleBench53.2%—
Kagi LLM Benchmark75%—
ARC-AGI-144.7%—
CritPt—2.3%
Chess Puzzles10%—
LMArena Hard Prompts1452—
Epoch Capabilities Index145.83—
ForecastBench61—

Math GLM-5 leads

GLM-5: 46.4 (#71), Step 3.7 Flash: 42.9 (#82)

Knowledge Not comparable

GLM-5: 52.3 (#64), Step 3.7 Flash: —

Knowledge benchmarks
BenchmarkGLM-5Step 3.7 Flash
GPQA Diamond87.8%—
Vectara Hallucination Rate10.1%—
LMArena Expert1454—

Multilingual Not comparable

GLM-5: 53.7 (#58), Step 3.7 Flash: —

Multilingual benchmarks
BenchmarkGLM-5Step 3.7 Flash
LMArena Non-English1430—
LMArena Chinese1511—
LMArena French1455—
LMArena German1445—
LMArena Japanese1416—
LMArena Korean1423—
LMArena Russian1436—
LMArena Spanish1454—

Instruction Following Not comparable

GLM-5: 75.2 (#67), Step 3.7 Flash: —

Instruction Following benchmarks
BenchmarkGLM-5Step 3.7 Flash
LMArena Instruction Following1428—

Long Context Not comparable

GLM-5: 44.7 (#60), Step 3.7 Flash: —

Long Context benchmarks
BenchmarkGLM-5Step 3.7 Flash
CL-bench18.7%—
LMArena Longer Query1446—

Writing & Preference Not comparable

GLM-5: 66.0 (#38), Step 3.7 Flash: —

Writing & Preference benchmarks
BenchmarkGLM-5Step 3.7 Flash
LMArena Text1446—
LMArena Creative Writing1439—
EQ-Bench Creative Writing1601—
LMArena Multi-Turn1456—

Frequently asked questions

Is GLM-5 better than Step 3.7 Flash?

GLM-5 is the stronger model overall, scoring 46.1 to 37.3 on the Noometry Index. Step 3.7 Flash costs 3.7× less per token, which makes it the better buy when GLM-5's lead doesn't matter for your workload.

Which is cheaper, GLM-5 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-5 lists at $1 and $3.20.

Is GLM-5 or Step 3.7 Flash better for coding?

GLM-5 scores higher on coding benchmarks: 49.0 versus 40.0 in the Noometry coding category.

Which has the bigger context window?

Step 3.7 Flash does, with 256K tokens against 205K.

How many benchmarks do GLM-5 and Step 3.7 Flash share?

3 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Step 3.7 Flash has 5.

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