# GPT-5.3 Codex vs Qwen1.5-72B

> GPT-5.3 Codex is the stronger model overall, scoring 45.5 to 30.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-5-3-codex-vs-qwen1-5-72b
- Last updated: 2026-10-10
- Shared benchmarks: 0

## Summary

- The widest gap is in coding, where GPT-5.3 Codex leads 48.5 to 31.4.
- Qwen1.5-72B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5.3 Codex | Qwen1.5-72B |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 45.5 | 30.3 |
| Rank | 61 | 282 |
| Context | 400K | — |
| Input $/M | $1.75 | — |
| Output $/M | $14 | — |
| Weights | Proprietary | Open |

## Coding

- GPT-5.3 Codex: 48.5 (#51)
- Qwen1.5-72B: 31.4 (#272)

| Benchmark | GPT-5.3 Codex | Qwen1.5-72B |
|---|---|---|
| SWE-bench Verified | 74.8% | — |
| LMArena WebDev | 1408 | — |
| WeirdML | 79.3% | — |
| BigCodeBench Instruct | — | 33.2% |
| LMArena Coding | — | 1166 |
| BigCodeBench Complete | — | 40.3% |
| ALE-Bench | 1,655 | — |
| HumanEval+ | — | 59.1% |
| MBPP+ | — | 61.6% |

## Agentic & Tool Use

- GPT-5.3 Codex: 47.8 (#9)
- Qwen1.5-72B: —

| Benchmark | GPT-5.3 Codex | Qwen1.5-72B |
|---|---|---|
| Terminal-Bench | 78.4% | — |
| METR Time Horizons | 74.5% | — |
| Vending-Bench 2 | 5,940 | — |

## Reasoning

- GPT-5.3 Codex: —
- Qwen1.5-72B: 21.2 (#201)

| Benchmark | GPT-5.3 Codex | Qwen1.5-72B |
|---|---|---|
| LMArena Hard Prompts | — | 1148 |
| Epoch Capabilities Index | 156.84 | — |

## Math

- GPT-5.3 Codex: —
- Qwen1.5-72B: 30.7 (#205)

| Benchmark | GPT-5.3 Codex | Qwen1.5-72B |
|---|---|---|
| LMArena Math | — | 1164 |

## Knowledge

- GPT-5.3 Codex: —
- Qwen1.5-72B: 11.5 (#295)

| Benchmark | GPT-5.3 Codex | Qwen1.5-72B |
|---|---|---|
| GPQA Diamond | — | 28.8% |
| LMArena Expert | — | 1136 |

## Multilingual

- GPT-5.3 Codex: —
- Qwen1.5-72B: 33.4 (#248)

| Benchmark | GPT-5.3 Codex | Qwen1.5-72B |
|---|---|---|
| LMArena Non-English | — | 1135 |
| LMArena Chinese | — | 1186 |
| LMArena French | — | 1158 |
| LMArena German | — | 1084 |
| LMArena Japanese | — | 1061 |
| LMArena Korean | — | 1049 |
| LMArena Russian | — | 1104 |
| LMArena Spanish | — | 1110 |

## Instruction Following

- GPT-5.3 Codex: —
- Qwen1.5-72B: 59.6 (#251)

| Benchmark | GPT-5.3 Codex | Qwen1.5-72B |
|---|---|---|
| LMArena Instruction Following | — | 1142 |

## Long Context

- GPT-5.3 Codex: —
- Qwen1.5-72B: 35.0 (#238)

| Benchmark | GPT-5.3 Codex | Qwen1.5-72B |
|---|---|---|
| LMArena Longer Query | — | 1157 |

## Writing & Preference

- GPT-5.3 Codex: —
- Qwen1.5-72B: 37.4 (#253)

| Benchmark | GPT-5.3 Codex | Qwen1.5-72B |
|---|---|---|
| LMArena Text | — | 1166 |
| LMArena Creative Writing | — | 1137 |
| LMArena Multi-Turn | — | 1160 |

## FAQ

### Is GPT-5.3 Codex better than Qwen1.5-72B?

GPT-5.3 Codex is the stronger model overall, scoring 45.5 to 30.3 on the Noometry Index.

### Is GPT-5.3 Codex or Qwen1.5-72B better for coding?

GPT-5.3 Codex scores higher on coding benchmarks: 48.5 versus 31.4 in the Noometry coding category.

### How many benchmarks do GPT-5.3 Codex and Qwen1.5-72B share?

0 benchmarks have published results for both models. GPT-5.3 Codex has 8 scored results on Noometry and Qwen1.5-72B has 22.