Noometry

Model comparison

GLM-4.7-Flash vs GPT-6 Sol

GPT-6 Sol is the stronger model overall, scoring 49.2 to 38.4 on the Noometry Index. GLM-4.7-Flash costs 28× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.

Last verified . 15 shared benchmarks.

GLM-4.7-Flash Z.ai (Zhipu)

38.4

Rank #175 Confirmed

GPT-6 Sol OpenAI

49.2

Rank #46 Confirmed

Summary

  • They share 15 benchmarks with published results for both. GLM-4.7-Flash scores higher in 0 categories and GPT-6 Sol in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GPT-6 Sol leads 49.3 to 20.2.
  • GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $2 / $10 for GPT-6 Sol.
  • GPT-6 Sol accepts more context: 1.05M tokens versus 200K.
  • GLM-4.7-Flash has downloadable open weights; the other is API-only.

Side by side

GLM-4.7-FlashGPT-6 Sol
ProviderZ.ai (Zhipu)OpenAI
Noometry Index38.449.2
Released2026-01-192026-09-22
WeightsOpenProprietary
Context window200K1.05M
Max output131K128K
Input $ / M tokens$0.06$2
Output $ / M tokens$0.40$10
Results tracked2122

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Category by category

Coding GPT-6 Sol leads

GLM-4.7-Flash: 40.0 (#133), GPT-6 Sol: 59.6 (#11)

BenchmarkGLM-4.7-FlashGPT-6 Sol
LMArena Coding13831453
DeepSWE—68.8%
FrontierCode—49.3%
LMArena WebDev—1692

Agentic & Tool Use Not comparable

GLM-4.7-Flash: —, GPT-6 Sol: 33.5 (#49)

BenchmarkGLM-4.7-FlashGPT-6 Sol
GDP.pdf—28%

Reasoning GPT-6 Sol leads

GLM-4.7-Flash: 20.2 (#224), GPT-6 Sol: 49.3 (#34)

BenchmarkGLM-4.7-FlashGPT-6 Sol
LMArena Hard Prompts13561420
NYT Connections (extended)—90.1%
Chess Puzzles0%—
EBR-Bench—53.3%

Math GPT-6 Sol leads

GLM-4.7-Flash: 34.4 (#159), GPT-6 Sol: 35.8 (#135)

BenchmarkGLM-4.7-FlashGPT-6 Sol
LMArena Math13541404
OTIS Mock AIME 2024-202558.3%—

Knowledge GPT-6 Sol leads

GLM-4.7-Flash: 35.4 (#177), GPT-6 Sol: 43.0 (#87)

BenchmarkGLM-4.7-FlashGPT-6 Sol
Vectara Hallucination Rate9.3%6.5%
LMArena Expert13571449
GPQA Diamond60.5%—

Multimodal Not comparable

GLM-4.7-Flash: —, GPT-6 Sol: 47.6 (#9)

BenchmarkGLM-4.7-FlashGPT-6 Sol
Furniture Assembly—58.3%

Multilingual GPT-6 Sol leads

GLM-4.7-Flash: 46.8 (#152), GPT-6 Sol: 51.0 (#113)

BenchmarkGLM-4.7-FlashGPT-6 Sol
LMArena Non-English13311389
LMArena Chinese14031416
LMArena Russian13331407
LMArena Spanish13511377
LMArena French1332—
LMArena German1336—
LMArena Korean1284—

Instruction Following GPT-6 Sol leads

GLM-4.7-Flash: 70.3 (#162), GPT-6 Sol: 74.4 (#97)

BenchmarkGLM-4.7-FlashGPT-6 Sol
LMArena Instruction Following13271406

Long Context GPT-6 Sol leads

GLM-4.7-Flash: 40.9 (#143), GPT-6 Sol: 43.2 (#100)

BenchmarkGLM-4.7-FlashGPT-6 Sol
LMArena Longer Query13451415

Writing & Preference GPT-6 Sol leads

GLM-4.7-Flash: 47.7 (#206), GPT-6 Sol: 72.3 (#15)

BenchmarkGLM-4.7-FlashGPT-6 Sol
LMArena Text13511396
LMArena Creative Writing12971392
EQ-Bench Creative Writing11252125
LMArena Multi-Turn13421405

Frequently asked questions

Is GLM-4.7-Flash better than GPT-6 Sol?

GPT-6 Sol is the stronger model overall, scoring 49.2 to 38.4 on the Noometry Index. GLM-4.7-Flash costs 28× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.

Which is cheaper, GLM-4.7-Flash or GPT-6 Sol?

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; GPT-6 Sol lists at $2 and $10.

Is GLM-4.7-Flash or GPT-6 Sol better for coding?

GPT-6 Sol scores higher on coding benchmarks: 59.6 versus 40.0 in the Noometry coding category.

Which has the bigger context window?

GPT-6 Sol does, with 1.05M tokens against 200K.

How many benchmarks do GLM-4.7-Flash and GPT-6 Sol share?

15 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and GPT-6 Sol has 22.

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