Model comparison
GPT-4.1 mini vs Qwen3.8 Max
Qwen3.8 Max is the stronger model overall, scoring 56.8 to 33.6 on the Noometry Index. GPT-4.1 mini costs 4.3× less per token, which makes it the better buy when Qwen3.8 Max's lead doesn't matter for your workload.
Last verified . 29 shared benchmarks.
Alibaba (Qwen)Summary
- They share 29 benchmarks with published results for both. GPT-4.1 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 math, where Qwen3.8 Max leads 73.2 to 24.1.
- The biggest single-benchmark swing is FrontierMath (Tiers 1-3): 6.7% for GPT-4.1 mini and 74.7% for Qwen3.8 Max.
- GPT-4.1 mini is cheaper at $0.40 / $1.60 per million input/output tokens, against $2 / $6 for Qwen3.8 Max.
- GPT-4.1 mini accepts more context: 1.05M tokens versus 1M.
Side by side
| GPT-4.1 mini | Qwen3.8 Max | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 33.6 | 56.8 |
| Released | 2025-04-14 | 2026-08-02 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1M |
| Max output | 33K | 131K |
| Input $ / M tokens | $0.40 | $2 |
| Output $ / M tokens | $1.60 | $6 |
| Results tracked | 47 | 39 |
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Category by category
Coding Qwen3.8 Max leads
GPT-4.1 mini: 30.6 (#293), Qwen3.8 Max: 53.5 (#29)
| Benchmark | GPT-4.1 mini | Qwen3.8 Max |
|---|---|---|
| SciCode | 40.4% | 53.2% |
| LMArena Coding | 1367 | 1502 |
| DeepSWE | — | 57.5% |
| SWE-bench Verified (bash only) | 23.9% | — |
| Aider Polyglot | 32.4% | — |
| LMArena WebDev | — | 1674 |
| FrontierSWE | — | 17.8% |
| WeirdML | 37.6% | — |
| BigCodeBench Instruct | 48.9% | — |
| CadEval | 16% | — |
Agentic & Tool Use Qwen3.8 Max leads
GPT-4.1 mini: 33.3 (#55), Qwen3.8 Max: 45.4 (#14)
| Benchmark | GPT-4.1 mini | Qwen3.8 Max |
|---|---|---|
| APEX-Agents | — | 63.3% |
| Berkeley Function Calling Leaderboard | 50.5% | — |
| τ²-bench Banking | — | 55.1% |
| GDP.pdf | — | 23.2% |
Reasoning Qwen3.8 Max leads
GPT-4.1 mini: 10.8 (#340), Qwen3.8 Max: 54.4 (#26)
| Benchmark | GPT-4.1 mini | Qwen3.8 Max |
|---|---|---|
| CritPt | 0% | 20% |
| Chess Puzzles | 7% | 40% |
| LMArena Hard Prompts | 1349 | 1496 |
| Mystery Game Puzzles | 7% | 38% |
| DTBench | 68.8% | 92% |
| LMCA | 21.1% | 46.2% |
| Epoch Capabilities Index | 135.01 | 156.41 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 48.6% | — |
| NYT Connections (extended) | — | 88.3% |
| ARC-AGI-1 | 3.5% | — |
Math Qwen3.8 Max leads
GPT-4.1 mini: 24.1 (#270), Qwen3.8 Max: 73.2 (#20)
| Benchmark | GPT-4.1 mini | Qwen3.8 Max |
|---|---|---|
| FrontierMath (Tiers 1-3) | 6.7% | 74.7% |
| OTIS Mock AIME 2024-2025 | 44.7% | 100% |
| LMArena Math | 1343 | 1499 |
| FrontierMath Tier 4 | — | 46.3% |
| ProofBench | — | 58% |
| Omni-MATH | 49.1% | — |
| MATH Level 5 | 87.3% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
Knowledge Qwen3.8 Max leads
GPT-4.1 mini: 34.7 (#194), Qwen3.8 Max: 61.7 (#27)
| Benchmark | GPT-4.1 mini | Qwen3.8 Max |
|---|---|---|
| GPQA Diamond | 65.8% | 92.7% |
| SimpleQA Verified | 12.7% | 47.3% |
| LMArena Expert | 1338 | 1507 |
| MMLU-Pro | 78.3% | — |
| GPQA (HELM) | 61.4% | — |
Multimodal Qwen3.8 Max leads
GPT-4.1 mini: 35.8 (#82), Qwen3.8 Max: 37.2 (#75)
| Benchmark | GPT-4.1 mini | Qwen3.8 Max |
|---|---|---|
| LMArena Vision | 1181 | 1314 |
| Furniture Assembly | — | 20% |
Multilingual Qwen3.8 Max leads
GPT-4.1 mini: 45.7 (#166), Qwen3.8 Max: 56.7 (#18)
| Benchmark | GPT-4.1 mini | Qwen3.8 Max |
|---|---|---|
| LMArena Non-English | 1318 | 1472 |
| LMArena Chinese | 1329 | 1538 |
| LMArena French | 1358 | 1503 |
| LMArena German | 1351 | 1483 |
| LMArena Japanese | 1290 | 1467 |
| LMArena Korean | 1298 | 1461 |
| LMArena Russian | 1324 | 1481 |
| LMArena Spanish | 1319 | 1492 |
Instruction Following Qwen3.8 Max leads
GPT-4.1 mini: 73.7 (#118), Qwen3.8 Max: 77.6 (#17)
| Benchmark | GPT-4.1 mini | Qwen3.8 Max |
|---|---|---|
| LMArena Instruction Following | 1333 | 1479 |
| IFEval | 90.4% | — |
Long Context Qwen3.8 Max leads
GPT-4.1 mini: 31.8 (#275), Qwen3.8 Max: 45.6 (#31)
| Benchmark | GPT-4.1 mini | Qwen3.8 Max |
|---|---|---|
| LMArena Longer Query | 1344 | 1489 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference Qwen3.8 Max leads
GPT-4.1 mini: 48.6 (#199), Qwen3.8 Max: 67.1 (#30)
| Benchmark | GPT-4.1 mini | Qwen3.8 Max |
|---|---|---|
| LMArena Text | 1340 | 1483 |
| LMArena Creative Writing | 1300 | 1479 |
| LMArena Multi-Turn | 1354 | 1489 |
| EQ-Bench Creative Writing | 1147 | — |
| WildBench | 83.8% | — |
Frequently asked questions
Is GPT-4.1 mini better than Qwen3.8 Max?
Qwen3.8 Max is the stronger model overall, scoring 56.8 to 33.6 on the Noometry Index. GPT-4.1 mini costs 4.3× 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-4.1 mini or Qwen3.8 Max?
GPT-4.1 mini is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; Qwen3.8 Max lists at $2 and $6.
Is GPT-4.1 mini or Qwen3.8 Max better for coding?
Qwen3.8 Max scores higher on coding benchmarks: 53.5 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 GPT-4.1 mini and Qwen3.8 Max share?
29 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and Qwen3.8 Max has 39.