# GLM-4.7-Flash vs GPT-5.3 Codex

> GPT-5.3 Codex is the stronger model overall, scoring 45.5 to 38.4 on the Noometry Index. GLM-4.7-Flash costs 33× less per token, which makes it the better buy when GPT-5.3 Codex's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-4-7-flash-vs-gpt-5-3-codex
- Last updated: 2026-10-10
- Shared benchmarks: 0

## Summary

- The widest gap is in coding, where GPT-5.3 Codex leads 48.5 to 40.0.
- GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- GPT-5.3 Codex accepts more context: 400K tokens versus 200K.
- GLM-4.7-Flash has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-4.7-Flash | GPT-5.3 Codex |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 38.4 | 45.5 |
| Rank | 175 | 61 |
| Context | 200K | 400K |
| Input $/M | $0.06 | $1.75 |
| Output $/M | $0.40 | $14 |
| Weights | Open | Proprietary |

## Coding

- GLM-4.7-Flash: 40.0 (#133)
- GPT-5.3 Codex: 48.5 (#51)

| Benchmark | GLM-4.7-Flash | GPT-5.3 Codex |
|---|---|---|
| SWE-bench Verified | — | 74.8% |
| LMArena WebDev | — | 1408 |
| WeirdML | — | 79.3% |
| LMArena Coding | 1383 | — |
| ALE-Bench | — | 1,655 |

## Agentic & Tool Use

- GLM-4.7-Flash: —
- GPT-5.3 Codex: 47.8 (#9)

| Benchmark | GLM-4.7-Flash | GPT-5.3 Codex |
|---|---|---|
| Terminal-Bench | — | 78.4% |
| METR Time Horizons | — | 74.5% |
| Vending-Bench 2 | — | 5,940 |

## Reasoning

- GLM-4.7-Flash: 20.2 (#224)
- GPT-5.3 Codex: —

| Benchmark | GLM-4.7-Flash | GPT-5.3 Codex |
|---|---|---|
| Chess Puzzles | 0% | — |
| LMArena Hard Prompts | 1356 | — |
| Epoch Capabilities Index | — | 156.84 |

## Math

- GLM-4.7-Flash: 34.4 (#159)
- GPT-5.3 Codex: —

| Benchmark | GLM-4.7-Flash | GPT-5.3 Codex |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 58.3% | — |
| LMArena Math | 1354 | — |

## Knowledge

- GLM-4.7-Flash: 35.4 (#177)
- GPT-5.3 Codex: —

| Benchmark | GLM-4.7-Flash | GPT-5.3 Codex |
|---|---|---|
| GPQA Diamond | 60.5% | — |
| Vectara Hallucination Rate | 9.3% | — |
| LMArena Expert | 1357 | — |

## Multilingual

- GLM-4.7-Flash: 46.8 (#152)
- GPT-5.3 Codex: —

| Benchmark | GLM-4.7-Flash | GPT-5.3 Codex |
|---|---|---|
| LMArena Non-English | 1331 | — |
| LMArena Chinese | 1403 | — |
| LMArena French | 1332 | — |
| LMArena German | 1336 | — |
| LMArena Korean | 1284 | — |
| LMArena Russian | 1333 | — |
| LMArena Spanish | 1351 | — |

## Instruction Following

- GLM-4.7-Flash: 70.3 (#162)
- GPT-5.3 Codex: —

| Benchmark | GLM-4.7-Flash | GPT-5.3 Codex |
|---|---|---|
| LMArena Instruction Following | 1327 | — |

## Long Context

- GLM-4.7-Flash: 40.9 (#143)
- GPT-5.3 Codex: —

| Benchmark | GLM-4.7-Flash | GPT-5.3 Codex |
|---|---|---|
| LMArena Longer Query | 1345 | — |

## Writing & Preference

- GLM-4.7-Flash: 47.7 (#206)
- GPT-5.3 Codex: —

| Benchmark | GLM-4.7-Flash | GPT-5.3 Codex |
|---|---|---|
| LMArena Text | 1351 | — |
| LMArena Creative Writing | 1297 | — |
| EQ-Bench Creative Writing | 1125 | — |
| LMArena Multi-Turn | 1342 | — |

## FAQ

### Is GLM-4.7-Flash better than GPT-5.3 Codex?

GPT-5.3 Codex is the stronger model overall, scoring 45.5 to 38.4 on the Noometry Index. GLM-4.7-Flash costs 33× less per token, which makes it the better buy when GPT-5.3 Codex's lead doesn't matter for your workload.

### Which is cheaper, GLM-4.7-Flash or GPT-5.3 Codex?

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.

### Is GLM-4.7-Flash or GPT-5.3 Codex better for coding?

GPT-5.3 Codex scores higher on coding benchmarks: 48.5 versus 40.0 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.3 Codex does, with 400K tokens against 200K.

### How many benchmarks do GLM-4.7-Flash and GPT-5.3 Codex share?

0 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and GPT-5.3 Codex has 8.