Model comparison

GLM-5 vs Solar Pro4

GLM-5 is the stronger model overall, scoring 46.1 to 42.1 on the Noometry Index. Solar Pro4 costs 3.0× less per token, which makes it the better buy when GLM-5's lead doesn't matter for your workload.

Last verified . 18 shared benchmarks.

GLM-5 Z.ai (Zhipu)

46.1

Rank #66 Confirmed

Solar Pro4 Upstage

42.1

Rank #121 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GLM-5 scores higher in 7 categories and Solar Pro4 in 1 category; 7 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-5 leads 52.3 to 39.8.
  • Solar Pro4 is cheaper at $0.30 / $1.20 per million input/output tokens, against $1 / $3.20 for GLM-5.
  • Solar Pro4 accepts more context: 524K tokens versus 205K.
  • GLM-5 has downloadable open weights; the other is API-only.

Side by side

GLM-5 and Solar Pro4 specifications
GLM-5Solar Pro4
ProviderZ.ai (Zhipu)Upstage
Noometry Index46.142.1
Released2026-02-112026-08-06
WeightsOpenProprietary
Context window205K524K
Max output131K131K
Input $ / M tokens$1$0.30
Output $ / M tokens$3.20$1.20
Results tracked4518

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding GLM-5 leads

GLM-5: 49.0 (#52), Solar Pro4: 40.1 (#149)

Coding benchmarks
BenchmarkGLM-5Solar Pro4
LMArena WebDev14341371
LMArena Coding14611437
SWE-bench Verified72.1%—
SWE-bench Verified (bash only)72.8%—
SWE-bench Multilingual69.7%—
WeirdML48.2%—
ALE-Bench765.62—

Agentic & Tool Use Not comparable

GLM-5: 31.1 (#71), Solar Pro4: —

Agentic & Tool Use benchmarks
BenchmarkGLM-5Solar Pro4
Terminal-Bench52.4%—
τ²-bench Airline82.5%—
τ²-bench Banking9.8%—
τ²-bench Retail73.7%—
τ²-bench Telecom86.8%—
Vending-Bench 24,432—

Reasoning Too close to call

GLM-5: 27.6 (#116), Solar Pro4: 28.5 (#104)

Reasoning benchmarks
BenchmarkGLM-5Solar Pro4
LMArena Hard Prompts14521399
ARC-AGI-24.9%—
SimpleBench53.2%—
Kagi LLM Benchmark75%—
NYT Connections (extended)74.8%—
ARC-AGI-144.7%—
Chess Puzzles10%—
Epoch Capabilities Index145.83—
ForecastBench61—

Math GLM-5 leads

GLM-5: 46.4 (#71), Solar Pro4: 38.8 (#128)

Knowledge GLM-5 leads

GLM-5: 52.3 (#64), Solar Pro4: 39.8 (#129)

Knowledge benchmarks
BenchmarkGLM-5Solar Pro4
LMArena Expert14541427
GPQA Diamond87.8%—
Vectara Hallucination Rate10.1%—

Multilingual GLM-5 leads

GLM-5: 53.7 (#58), Solar Pro4: 48.7 (#139)

Multilingual benchmarks
BenchmarkGLM-5Solar Pro4
LMArena Non-English14301361
LMArena Chinese15111415
LMArena French14551397
LMArena German14451364
LMArena Japanese14161309
LMArena Korean14231382
LMArena Russian14361360
LMArena Spanish14541401

Instruction Following GLM-5 leads

GLM-5: 75.2 (#67), Solar Pro4: 72.7 (#132)

Instruction Following benchmarks
BenchmarkGLM-5Solar Pro4
LMArena Instruction Following14281377

Long Context GLM-5 leads

GLM-5: 44.7 (#60), Solar Pro4: 42.1 (#130)

Long Context benchmarks
BenchmarkGLM-5Solar Pro4
LMArena Longer Query14461381
CL-bench18.7%—

Writing & Preference GLM-5 leads

GLM-5: 66.0 (#38), Solar Pro4: 56.5 (#138)

Writing & Preference benchmarks
BenchmarkGLM-5Solar Pro4
LMArena Text14461386
LMArena Creative Writing14391316
LMArena Multi-Turn14561385
EQ-Bench Creative Writing1601—

Frequently asked questions

Is GLM-5 better than Solar Pro4?

GLM-5 is the stronger model overall, scoring 46.1 to 42.1 on the Noometry Index. Solar Pro4 costs 3.0× 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 Solar Pro4?

Solar Pro4 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; GLM-5 lists at $1 and $3.20.

Is GLM-5 or Solar Pro4 better for coding?

GLM-5 scores higher on coding benchmarks: 49.0 versus 40.1 in the Noometry coding category.

Which has the bigger context window?

Solar Pro4 does, with 524K tokens against 205K.

How many benchmarks do GLM-5 and Solar Pro4 share?

18 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Solar Pro4 has 18.

Related comparisons

Go deeper