# GLM-4.7 vs GPT-5-Codex

> GLM-4.7 is the stronger model overall, scoring 41.7 to 37.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-7-vs-gpt-5-codex
- Last updated: 2026-10-10
- Shared benchmarks: 1

## Summary

- They share 1 benchmark with published results for both. GLM-4.7 scores higher in 1 category and GPT-5-Codex in 2 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5-Codex leads 30.0 to 23.7.
- The biggest single-benchmark swing is Terminal-Bench: 33.4% for GLM-4.7 and 44.3% for GPT-5-Codex.
- GLM-4.7 is cheaper at $0.60 / $2.20 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
- GPT-5-Codex accepts more context: 400K tokens versus 205K.
- GLM-4.7 has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-4.7 | GPT-5-Codex |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 41.7 | 37.3 |
| Rank | 117 | 190 |
| Context | 205K | 400K |
| Input $/M | $0.60 | $1.25 |
| Output $/M | $2.20 | $10 |
| Weights | Open | Proprietary |

## Coding

- GLM-4.7: 43.6 (#74)
- GPT-5-Codex: 41.9 (#100)

| Benchmark | GLM-4.7 | GPT-5-Codex |
|---|---|---|
| LMArena WebDev | 1435 | — |
| SciCode | 45.1% | — |
| WeirdML | — | 54.5% |
| LMArena Coding | 1454 | — |
| ALE-Bench | 399.48 | — |

## Agentic & Tool Use

- GLM-4.7: 26.4 (#96)
- GPT-5-Codex: 30.8 (#66)

| Benchmark | GLM-4.7 | GPT-5-Codex |
|---|---|---|
| Terminal-Bench | 33.4% | 44.3% |
| Vending-Bench 2 | 2,377 | — |

## Reasoning

- GLM-4.7: 23.7 (#161)
- GPT-5-Codex: 30.0 (#80)

| Benchmark | GLM-4.7 | GPT-5-Codex |
|---|---|---|
| SimpleBench | 47.7% | — |
| Kagi LLM Benchmark | — | 70.3% |
| CritPt | 1.7% | — |
| Chess Puzzles | 6% | — |
| LMArena Hard Prompts | 1443 | — |
| Epoch Capabilities Index | 143.53 | — |

## Math

- GLM-4.7: 37.7 (#92)
- GPT-5-Codex: —

| Benchmark | GLM-4.7 | GPT-5-Codex |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 83.3% | — |
| ProofBench | 6% | — |
| LMArena Math | 1423 | — |
| FrontierMath (Feb 2025 set) | 2.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |

## Knowledge

- GLM-4.7: 47.0 (#74)
- GPT-5-Codex: —

| Benchmark | GLM-4.7 | GPT-5-Codex |
|---|---|---|
| GPQA Diamond | 83.3% | — |
| SimpleQA Verified | 32.2% | — |
| Vectara Hallucination Rate | 11.7% | — |
| LMArena Expert | 1424 | — |

## Multilingual

- GLM-4.7: 53.0 (#75)
- GPT-5-Codex: —

| Benchmark | GLM-4.7 | GPT-5-Codex |
|---|---|---|
| LMArena Non-English | 1417 | — |
| LMArena Chinese | 1495 | — |
| LMArena French | 1432 | — |
| LMArena German | 1426 | — |
| LMArena Japanese | 1439 | — |
| LMArena Korean | 1401 | — |
| LMArena Russian | 1423 | — |
| LMArena Spanish | 1433 | — |

## Instruction Following

- GLM-4.7: 74.6 (#90)
- GPT-5-Codex: —

| Benchmark | GLM-4.7 | GPT-5-Codex |
|---|---|---|
| LMArena Instruction Following | 1411 | — |

## Long Context

- GLM-4.7: 42.8 (#111)
- GPT-5-Codex: —

| Benchmark | GLM-4.7 | GPT-5-Codex |
|---|---|---|
| CL-bench | 15.9% | — |
| CL-bench Life | 10.9% | — |
| LMArena Longer Query | 1432 | — |

## Writing & Preference

- GLM-4.7: 61.1 (#89)
- GPT-5-Codex: —

| Benchmark | GLM-4.7 | GPT-5-Codex |
|---|---|---|
| LMArena Text | 1436 | — |
| LMArena Creative Writing | 1401 | — |
| EQ-Bench Creative Writing | 1413 | — |
| LMArena Multi-Turn | 1446 | — |

## FAQ

### Is GLM-4.7 better than GPT-5-Codex?

GLM-4.7 is the stronger model overall, scoring 41.7 to 37.3 on the Noometry Index.

### Which is cheaper, GLM-4.7 or GPT-5-Codex?

GLM-4.7 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; GPT-5-Codex lists at $1.25 and $10.

### Is GLM-4.7 or GPT-5-Codex better for coding?

GLM-4.7 scores higher on coding benchmarks: 43.6 versus 41.9 in the Noometry coding category.

### Which has the bigger context window?

GPT-5-Codex does, with 400K tokens against 205K.

### How many benchmarks do GLM-4.7 and GPT-5-Codex share?

1 benchmark has published results for both models. GLM-4.7 has 36 scored results on Noometry and GPT-5-Codex has 3.