# Claude Opus 4.8 vs GPT-4.1 mini

> Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 33.6 on the Noometry Index. GPT-4.1 mini costs 14× 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-4-1-mini
- Last updated: 2026-10-12
- Shared benchmarks: 35

## Summary

- They share 35 benchmarks with published results for both. Claude Opus 4.8 scores higher in 10 categories and GPT-4.1 mini in 0 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Opus 4.8 leads 78.4 to 24.1.
- The biggest single-benchmark swing is ARC-AGI-1: 92.5% for Claude Opus 4.8 and 3.5% for GPT-4.1 mini.
- GPT-4.1 mini is cheaper at $0.40 / $1.60 per million input/output tokens, against $5 / $25 for Claude Opus 4.8.
- GPT-4.1 mini accepts more context: 1.05M tokens versus 1M.

## Snapshot

| | Claude Opus 4.8 | GPT-4.1 mini |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 60.7 | 33.6 |
| Rank | 13 | 240 |
| Context | 1M | 1.05M |
| Input $/M | $5 | $0.40 |
| Output $/M | $25 | $1.60 |
| Weights | Proprietary | Proprietary |

## Coding

- Claude Opus 4.8: 59.9 (#12)
- GPT-4.1 mini: 30.6 (#293)

| Benchmark | Claude Opus 4.8 | GPT-4.1 mini |
|---|---|---|
| SciCode | 53.5% | 40.4% |
| WeirdML | 82.9% | 37.6% |
| LMArena Coding | 1490 | 1367 |
| DeepSWE | 59% | — |
| FrontierCode | 46.5% | — |
| SWE-bench Verified (bash only) | — | 23.9% |
| Aider Polyglot | — | 32.4% |
| LMArena WebDev | 1556 | — |
| GSO | 47.1% | — |
| BigCodeBench Instruct | — | 48.9% |
| CadEval | — | 16% |
| ALE-Bench | 1,564 | — |

## Agentic & Tool Use

- Claude Opus 4.8: 47.6 (#11)
- GPT-4.1 mini: 33.3 (#55)

| Benchmark | Claude Opus 4.8 | GPT-4.1 mini |
|---|---|---|
| APEX-Agents | 48.9% | — |
| Berkeley Function Calling Leaderboard | — | 50.5% |
| 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-4.1 mini: 10.8 (#340)

| Benchmark | Claude Opus 4.8 | GPT-4.1 mini |
|---|---|---|
| ARC-AGI-2 | 72.1% | 0% |
| Kagi LLM Benchmark | 88.8% | 48.6% |
| ARC-AGI-1 | 92.5% | 3.5% |
| CritPt | 20.9% | 0% |
| Chess Puzzles | 34% | 7% |
| LMArena Hard Prompts | 1482 | 1349 |
| Mystery Game Puzzles | 36% | 7% |
| DTBench | 94.9% | 68.8% |
| LMCA | 57.5% | 21.1% |
| Epoch Capabilities Index | 158.21 | 135.01 |
| SimpleBench | 64.8% | — |
| NYT Connections (extended) | 91.1% | — |
| EnigmaEval | 23.5% | — |
| EBR-Bench | 28.6% | — |
| Surface Evolver Bench | 87.5% | — |
| Bench to the Future 3 | 0.14 | — |
| ForecastBench | 59.9 | — |

## Math

- Claude Opus 4.8: 78.4 (#13)
- GPT-4.1 mini: 24.1 (#270)

| Benchmark | Claude Opus 4.8 | GPT-4.1 mini |
|---|---|---|
| FrontierMath (Tiers 1-3) | 80% | 6.7% |
| OTIS Mock AIME 2024-2025 | 98.3% | 44.7% |
| LMArena Math | 1487 | 1343 |
| FrontierMath (Feb 2025 set) | 47.2% | 4.5% |
| FrontierMath Tier 4 | 56.1% | — |
| MathArena Final-Answer Competitions | 91.8% | — |
| ProofBench | 69% | — |
| Omni-MATH | — | 49.1% |
| MATH Level 5 | — | 87.3% |
| FrontierMath Tier 4 (v1) | 31.3% | — |

## Knowledge

- Claude Opus 4.8: 61.3 (#29)
- GPT-4.1 mini: 34.7 (#194)

| Benchmark | Claude Opus 4.8 | GPT-4.1 mini |
|---|---|---|
| GPQA Diamond | 91% | 65.8% |
| SimpleQA Verified | 53% | 12.7% |
| LMArena Expert | 1502 | 1338 |
| MMLU-Pro | — | 78.3% |
| GPQA (HELM) | — | 61.4% |

## Multimodal

- Claude Opus 4.8: 42.9 (#26)
- GPT-4.1 mini: 35.8 (#82)

| Benchmark | Claude Opus 4.8 | GPT-4.1 mini |
|---|---|---|
| LMArena Vision | 1294 | 1181 |
| Blueprint-Bench 2 | 14.5% | — |
| Furniture Assembly | 42.5% | — |
| LMArena Document | 1475 | — |

## Multilingual

- Claude Opus 4.8: 55.2 (#33)
- GPT-4.1 mini: 45.7 (#166)

| Benchmark | Claude Opus 4.8 | GPT-4.1 mini |
|---|---|---|
| LMArena Non-English | 1450 | 1318 |
| LMArena Chinese | 1507 | 1329 |
| LMArena French | 1481 | 1358 |
| LMArena German | 1472 | 1351 |
| LMArena Japanese | 1440 | 1290 |
| LMArena Korean | 1432 | 1298 |
| LMArena Russian | 1474 | 1324 |
| LMArena Spanish | 1466 | 1319 |

## Instruction Following

- Claude Opus 4.8: 77.4 (#24)
- GPT-4.1 mini: 73.7 (#118)

| Benchmark | Claude Opus 4.8 | GPT-4.1 mini |
|---|---|---|
| LMArena Instruction Following | 1476 | 1333 |
| IFEval | — | 90.4% |

## Long Context

- Claude Opus 4.8: 45.4 (#35)
- GPT-4.1 mini: 31.8 (#275)

| Benchmark | Claude Opus 4.8 | GPT-4.1 mini |
|---|---|---|
| LMArena Longer Query | 1483 | 1344 |
| Fiction.LiveBench | — | 44.4% |

## Writing & Preference

- Claude Opus 4.8: 72.0 (#16)
- GPT-4.1 mini: 48.6 (#199)

| Benchmark | Claude Opus 4.8 | GPT-4.1 mini |
|---|---|---|
| LMArena Text | 1461 | 1340 |
| LMArena Creative Writing | 1454 | 1300 |
| EQ-Bench Creative Writing | 1840 | 1147 |
| LMArena Multi-Turn | 1476 | 1354 |
| WildBench | — | 83.8% |
| EQ-Bench 4 | 1281 | — |

## FAQ

### Is Claude Opus 4.8 better than GPT-4.1 mini?

Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 33.6 on the Noometry Index. GPT-4.1 mini costs 14× 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-4.1 mini?

GPT-4.1 mini is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; Claude Opus 4.8 lists at $5 and $25.

### Is Claude Opus 4.8 or GPT-4.1 mini better for coding?

Claude Opus 4.8 scores higher on coding benchmarks: 59.9 versus 30.6 in the Noometry coding category.

### Which has the bigger context window?

GPT-4.1 mini does, with 1.05M tokens against 1M.

### How many benchmarks do Claude Opus 4.8 and GPT-4.1 mini share?

35 benchmarks have published results for both models. Claude Opus 4.8 has 65 scored results on Noometry and GPT-4.1 mini has 47.