# Claude Opus 4.8 vs GPT-5.3 Chat

> Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 42.8 on the Noometry Index. GPT-5.3 Chat costs 2.1× less per token, which makes it the better buy when Claude Opus 4.8's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-opus-4-8-vs-gpt-5-3-chat
- Last updated: 2026-10-12
- Shared benchmarks: 18

## Summary

- They share 18 benchmarks with published results for both. Claude Opus 4.8 scores higher in 8 categories and GPT-5.3 Chat in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Opus 4.8 leads 78.4 to 38.2.
- GPT-5.3 Chat is cheaper at $1.75 / $14 per million input/output tokens, against $5 / $25 for Claude Opus 4.8.
- Claude Opus 4.8 accepts more context: 1M tokens versus 128K.

## Snapshot

| | Claude Opus 4.8 | GPT-5.3 Chat |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 60.7 | 42.8 |
| Rank | 13 | 109 |
| Context | 1M | 128K |
| Input $/M | $5 | $1.75 |
| Output $/M | $25 | $14 |
| Weights | Proprietary | Proprietary |

## Coding

- Claude Opus 4.8: 59.9 (#12)
- GPT-5.3 Chat: 41.4 (#124)

| Benchmark | Claude Opus 4.8 | GPT-5.3 Chat |
|---|---|---|
| LMArena Coding | 1490 | 1408 |
| DeepSWE | 59% | — |
| FrontierCode | 46.5% | — |
| LMArena WebDev | 1556 | — |
| SciCode | 53.5% | — |
| GSO | 47.1% | — |
| WeirdML | 82.9% | — |
| ALE-Bench | 1,564 | — |

## Agentic & Tool Use

- Claude Opus 4.8: 47.6 (#11)
- GPT-5.3 Chat: —

| Benchmark | Claude Opus 4.8 | GPT-5.3 Chat |
|---|---|---|
| APEX-Agents | 48.9% | — |
| OSWorld 2.0 | 20.6% | — |
| Remote Labor Index | 8.3% | — |
| τ²-bench Banking | 39.7% | — |
| DeepResearch Bench | 50.2% | — |
| PostTrainBench | 33.8% | — |
| GBAEval | 70.9% | — |
| GDP.pdf | 24% | — |
| LMArena Search | 1204 | — |
| Vending-Bench 2 | 5,787 | — |

## Reasoning

- Claude Opus 4.8: 64.7 (#16)
- GPT-5.3 Chat: 28.5 (#102)

| Benchmark | Claude Opus 4.8 | GPT-5.3 Chat |
|---|---|---|
| LMArena Hard Prompts | 1482 | 1399 |
| ARC-AGI-2 | 72.1% | — |
| SimpleBench | 64.8% | — |
| Kagi LLM Benchmark | 88.8% | — |
| NYT Connections (extended) | 91.1% | — |
| ARC-AGI-1 | 92.5% | — |
| CritPt | 20.9% | — |
| Chess Puzzles | 34% | — |
| EnigmaEval | 23.5% | — |
| EBR-Bench | 28.6% | — |
| Mystery Game Puzzles | 36% | — |
| DTBench | 94.9% | — |
| LMCA | 57.5% | — |
| Surface Evolver Bench | 87.5% | — |
| Bench to the Future 3 | 0.14 | — |
| Epoch Capabilities Index | 158.21 | — |
| ForecastBench | 59.9 | — |

## Math

- Claude Opus 4.8: 78.4 (#13)
- GPT-5.3 Chat: 38.2 (#142)

| Benchmark | Claude Opus 4.8 | GPT-5.3 Chat |
|---|---|---|
| LMArena Math | 1487 | 1389 |
| FrontierMath (Tiers 1-3) | 80% | — |
| FrontierMath Tier 4 | 56.1% | — |
| MathArena Final-Answer Competitions | 91.8% | — |
| OTIS Mock AIME 2024-2025 | 98.3% | — |
| ProofBench | 69% | — |
| FrontierMath (Feb 2025 set) | 47.2% | — |
| FrontierMath Tier 4 (v1) | 31.3% | — |

## Knowledge

- Claude Opus 4.8: 61.3 (#29)
- GPT-5.3 Chat: 38.8 (#140)

| Benchmark | Claude Opus 4.8 | GPT-5.3 Chat |
|---|---|---|
| LMArena Expert | 1502 | 1397 |
| GPQA Diamond | 91% | — |
| SimpleQA Verified | 53% | — |

## Multimodal

- Claude Opus 4.8: 42.9 (#26)
- GPT-5.3 Chat: —

| Benchmark | Claude Opus 4.8 | GPT-5.3 Chat |
|---|---|---|
| LMArena Vision | 1294 | — |
| Blueprint-Bench 2 | 14.5% | — |
| Furniture Assembly | 42.5% | — |
| LMArena Document | 1475 | — |

## Multilingual

- Claude Opus 4.8: 55.2 (#33)
- GPT-5.3 Chat: 50.3 (#124)

| Benchmark | Claude Opus 4.8 | GPT-5.3 Chat |
|---|---|---|
| LMArena Non-English | 1450 | 1382 |
| LMArena Chinese | 1507 | 1432 |
| LMArena French | 1481 | 1397 |
| LMArena German | 1472 | 1384 |
| LMArena Japanese | 1440 | 1352 |
| LMArena Korean | 1432 | 1346 |
| LMArena Russian | 1474 | 1400 |
| LMArena Spanish | 1466 | 1371 |

## Instruction Following

- Claude Opus 4.8: 77.4 (#24)
- GPT-5.3 Chat: 72.8 (#129)

| Benchmark | Claude Opus 4.8 | GPT-5.3 Chat |
|---|---|---|
| LMArena Instruction Following | 1476 | 1378 |

## Long Context

- Claude Opus 4.8: 45.4 (#35)
- GPT-5.3 Chat: 42.6 (#120)

| Benchmark | Claude Opus 4.8 | GPT-5.3 Chat |
|---|---|---|
| LMArena Longer Query | 1483 | 1396 |

## Writing & Preference

- Claude Opus 4.8: 72.0 (#16)
- GPT-5.3 Chat: 63.1 (#68)

| Benchmark | Claude Opus 4.8 | GPT-5.3 Chat |
|---|---|---|
| LMArena Text | 1461 | 1389 |
| LMArena Creative Writing | 1454 | 1355 |
| EQ-Bench Creative Writing | 1840 | 1690 |
| LMArena Multi-Turn | 1476 | 1412 |
| EQ-Bench 4 | 1281 | — |

## FAQ

### Is Claude Opus 4.8 better than GPT-5.3 Chat?

Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 42.8 on the Noometry Index. GPT-5.3 Chat costs 2.1× less per token, which makes it the better buy when Claude Opus 4.8's lead doesn't matter for your workload.

### Which is cheaper, Claude Opus 4.8 or GPT-5.3 Chat?

GPT-5.3 Chat is cheaper. It lists at $1.75 per million input tokens and $14 per million output tokens; Claude Opus 4.8 lists at $5 and $25.

### Is Claude Opus 4.8 or GPT-5.3 Chat better for coding?

Claude Opus 4.8 scores higher on coding benchmarks: 59.9 versus 41.4 in the Noometry coding category.

### Which has the bigger context window?

Claude Opus 4.8 does, with 1M tokens against 128K.

### How many benchmarks do Claude Opus 4.8 and GPT-5.3 Chat share?

18 benchmarks have published results for both models. Claude Opus 4.8 has 65 scored results on Noometry and GPT-5.3 Chat has 18.