# GPT-5 Mini vs Qwen3.8 Max

> Qwen3.8 Max is the stronger model overall, scoring 56.0 to 41.7 on the Noometry Index. GPT-5 Mini costs 4.4× less per token, which makes it the better buy when Qwen3.8 Max's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-5-mini-vs-qwen3-8-max
- Last updated: 2026-10-10
- Shared benchmarks: 31

## Summary

- They share 31 benchmarks with published results for both. GPT-5 Mini scores higher in 0 categories and Qwen3.8 Max in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.8 Max leads 53.4 to 24.1.
- The biggest single-benchmark swing is ProofBench: 9% for GPT-5 Mini and 58% for Qwen3.8 Max.
- GPT-5 Mini is cheaper at $0.25 / $2 per million input/output tokens, against $2 / $6 for Qwen3.8 Max.
- Qwen3.8 Max accepts more context: 1M tokens versus 400K.

## Snapshot

| | GPT-5 Mini | Qwen3.8 Max |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 41.7 | 56.0 |
| Rank | 115 | 21 |
| Context | 400K | 1M |
| Input $/M | $0.25 | $2 |
| Output $/M | $2 | $6 |
| Weights | Proprietary | Proprietary |

## Coding

- GPT-5 Mini: 40.0 (#134)
- Qwen3.8 Max: 52.3 (#30)

| Benchmark | GPT-5 Mini | Qwen3.8 Max |
|---|---|---|
| SciCode | 39.2% | 52.9% |
| LMArena Coding | 1406 | 1499 |
| SWE-bench Verified | 64.7% | — |
| DeepSWE | — | 57.5% |
| SWE-bench Verified (bash only) | 59.8% | — |
| LMArena WebDev | — | 1671 |
| SWE-bench Multilingual | 39.7% | — |
| FrontierSWE | — | 15.8% |
| WeirdML | 52.7% | — |
| ALE-Bench | 799.77 | — |
| AlgoTune | 1.38 | — |

## Agentic & Tool Use

- GPT-5 Mini: 31.0 (#64)
- Qwen3.8 Max: 42.6 (#17)

| Benchmark | GPT-5 Mini | Qwen3.8 Max |
|---|---|---|
| Terminal-Bench | 34.8% | — |
| Berkeley Function Calling Leaderboard | 55.5% | — |
| τ²-bench Banking | — | 55.1% |
| GDP.pdf | — | 23.2% |
| Vending-Bench 2 | -31.18 | — |

## Reasoning

- GPT-5 Mini: 24.1 (#153)
- Qwen3.8 Max: 53.4 (#26)

| Benchmark | GPT-5 Mini | Qwen3.8 Max |
|---|---|---|
| CritPt | 0% | 20% |
| Chess Puzzles | 30% | 40% |
| LMArena Hard Prompts | 1380 | 1493 |
| Mystery Game Puzzles | 10% | 38% |
| DTBench | 80.5% | 92% |
| LMCA | 34.2% | 46.2% |
| Epoch Capabilities Index | 145.51 | 156.69 |
| ARC-AGI-2 | 4.4% | — |
| Kagi LLM Benchmark | 70.3% | — |
| NYT Connections (extended) | — | 88.3% |
| ARC-AGI-1 | 54.3% | — |
| EnigmaEval | 8.2% | — |
| ForecastBench | 61 | — |

## Math

- GPT-5 Mini: 46.3 (#59)
- Qwen3.8 Max: 73.1 (#15)

| Benchmark | GPT-5 Mini | Qwen3.8 Max |
|---|---|---|
| FrontierMath (Tiers 1-3) | 46.7% | 74.7% |
| FrontierMath Tier 4 | 12.2% | 46.3% |
| OTIS Mock AIME 2024-2025 | 86.7% | 100% |
| ProofBench | 9% | 58% |
| LMArena Math | 1377 | 1498 |
| Omni-MATH | 72.2% | — |
| MATH Level 5 | 97.8% | — |
| FrontierMath (Feb 2025 set) | 27.2% | — |
| FrontierMath Tier 4 (v1) | 6.3% | — |

## Knowledge

- GPT-5 Mini: 45.5 (#80)
- Qwen3.8 Max: 61.7 (#25)

| Benchmark | GPT-5 Mini | Qwen3.8 Max |
|---|---|---|
| GPQA Diamond | 75% | 92.7% |
| SimpleQA Verified | 21.6% | 47.3% |
| LMArena Expert | 1377 | 1504 |
| Humanity's Last Exam | 19.4% | — |
| MMLU-Pro | 83.5% | — |
| Confabulations | 13.3% | — |
| Vectara Hallucination Rate | 12.9% | — |
| GPQA (HELM) | 75.6% | — |

## Multimodal

- GPT-5 Mini: 35.0 (#80)
- Qwen3.8 Max: 36.9 (#70)

| Benchmark | GPT-5 Mini | Qwen3.8 Max |
|---|---|---|
| LMArena Vision | 1202 | 1314 |
| VPCT | 40.2% | — |
| Furniture Assembly | — | 20% |

## Multilingual

- GPT-5 Mini: 49.1 (#131)
- Qwen3.8 Max: 56.6 (#18)

| Benchmark | GPT-5 Mini | Qwen3.8 Max |
|---|---|---|
| LMArena Non-English | 1363 | 1468 |
| LMArena Chinese | 1387 | 1537 |
| LMArena French | 1385 | 1502 |
| LMArena German | 1366 | 1489 |
| LMArena Japanese | 1342 | 1466 |
| LMArena Korean | 1306 | 1467 |
| LMArena Russian | 1362 | 1478 |
| LMArena Spanish | 1355 | 1495 |

## Instruction Following

- GPT-5 Mini: 76.4 (#43)
- Qwen3.8 Max: 77.7 (#19)

| Benchmark | GPT-5 Mini | Qwen3.8 Max |
|---|---|---|
| LMArena Instruction Following | 1357 | 1478 |
| IFEval | 92.7% | — |

## Long Context

- GPT-5 Mini: 41.9 (#127)
- Qwen3.8 Max: 45.5 (#30)

| Benchmark | GPT-5 Mini | Qwen3.8 Max |
|---|---|---|
| LMArena Longer Query | 1355 | 1486 |
| Fiction.LiveBench | 69.4% | — |

## Writing & Preference

- GPT-5 Mini: 55.4 (#143)
- Qwen3.8 Max: 67.0 (#31)

| Benchmark | GPT-5 Mini | Qwen3.8 Max |
|---|---|---|
| LMArena Text | 1373 | 1480 |
| LMArena Creative Writing | 1325 | 1478 |
| LMArena Multi-Turn | 1363 | 1487 |
| Short-Story Creative Writing | 83.1% | — |
| EQ-Bench Creative Writing | 1313 | — |
| WildBench | 85.5% | — |

## FAQ

### Is GPT-5 Mini better than Qwen3.8 Max?

Qwen3.8 Max is the stronger model overall, scoring 56.0 to 41.7 on the Noometry Index. GPT-5 Mini costs 4.4× less per token, which makes it the better buy when Qwen3.8 Max's lead doesn't matter for your workload.

### Which is cheaper, GPT-5 Mini or Qwen3.8 Max?

GPT-5 Mini is cheaper. It lists at $0.25 per million input tokens and $2 per million output tokens; Qwen3.8 Max lists at $2 and $6.

### Is GPT-5 Mini or Qwen3.8 Max better for coding?

Qwen3.8 Max scores higher on coding benchmarks: 52.3 versus 40.0 in the Noometry coding category.

### Which has the bigger context window?

Qwen3.8 Max does, with 1M tokens against 400K.

### How many benchmarks do GPT-5 Mini and Qwen3.8 Max share?

31 benchmarks have published results for both models. GPT-5 Mini has 60 scored results on Noometry and Qwen3.8 Max has 38.