Model comparison
GPT-5 Mini vs Qwen2.5-VL 72B Instruct
GPT-5 Mini is the stronger model overall, scoring 41.7 to 29.4 on the Noometry Index.
Last verified . 2 shared benchmarks.
Alibaba (Qwen)Summary
- They share 2 benchmarks with published results for both. GPT-5 Mini scores higher in 3 categories and Qwen2.5-VL 72B Instruct in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where GPT-5 Mini leads 31.0 to 18.4.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 70.3% for GPT-5 Mini and 36% for Qwen2.5-VL 72B Instruct.
- GPT-5 Mini is cheaper at $0.25 / $2 per million input/output tokens, against $2.80 / $8.40 for Qwen2.5-VL 72B Instruct.
- GPT-5 Mini accepts more context: 400K tokens versus 131K.
- Qwen2.5-VL 72B Instruct has downloadable open weights; the other is API-only.
Side by side
| GPT-5 Mini | Qwen2.5-VL 72B Instruct | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 41.7 | 29.4 |
| Released | 2025-08-07 | 2024-09 |
| Weights | Proprietary | Open |
| Context window | 400K | 131K |
| Max output | 128K | 8K |
| Input $ / M tokens | $0.25 | $2.80 |
| Output $ / M tokens | $2 | $8.40 |
| Results tracked | 60 | 6 |
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Category by category
Coding Not comparable
GPT-5 Mini: 40.0 (#134), Qwen2.5-VL 72B Instruct: —
| Benchmark | GPT-5 Mini | Qwen2.5-VL 72B Instruct |
|---|---|---|
| SWE-bench Verified | 64.7% | — |
| SWE-bench Verified (bash only) | 59.8% | — |
| SWE-bench Multilingual | 39.7% | — |
| SciCode | 39.2% | — |
| WeirdML | 52.7% | — |
| LMArena Coding | 1406 | — |
| ALE-Bench | 799.77 | — |
| AlgoTune | 1.38 | — |
Agentic & Tool Use GPT-5 Mini leads
GPT-5 Mini: 31.0 (#64), Qwen2.5-VL 72B Instruct: 18.4 (#136)
| Benchmark | GPT-5 Mini | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Terminal-Bench | 34.8% | — |
| Berkeley Function Calling Leaderboard | 55.5% | — |
| OSWorld | — | 5% |
| Vending-Bench 2 | -31.18 | — |
Reasoning GPT-5 Mini leads
GPT-5 Mini: 24.1 (#153), Qwen2.5-VL 72B Instruct: 20.0 (#228)
| Benchmark | GPT-5 Mini | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 70.3% | 36% |
| ARC-AGI-2 | 4.4% | — |
| ARC-AGI-1 | 54.3% | — |
| CritPt | 0% | — |
| Chess Puzzles | 30% | — |
| EnigmaEval | 8.2% | — |
| LMArena Hard Prompts | 1380 | — |
| Mystery Game Puzzles | 10% | — |
| DTBench | 80.5% | — |
| LMCA | 34.2% | — |
| Epoch Capabilities Index | 145.51 | — |
| ForecastBench | 61 | — |
Math Not comparable
GPT-5 Mini: 46.3 (#59), Qwen2.5-VL 72B Instruct: —
| Benchmark | GPT-5 Mini | Qwen2.5-VL 72B Instruct |
|---|---|---|
| FrontierMath (Tiers 1-3) | 46.7% | — |
| FrontierMath Tier 4 | 12.2% | — |
| OTIS Mock AIME 2024-2025 | 86.7% | — |
| ProofBench | 9% | — |
| Omni-MATH | 72.2% | — |
| LMArena Math | 1377 | — |
| MATH Level 5 | 97.8% | — |
| FrontierMath (Feb 2025 set) | 27.2% | — |
| FrontierMath Tier 4 (v1) | 6.3% | — |
Knowledge Not comparable
GPT-5 Mini: 45.5 (#80), Qwen2.5-VL 72B Instruct: —
| Benchmark | GPT-5 Mini | Qwen2.5-VL 72B Instruct |
|---|---|---|
| GPQA Diamond | 75% | — |
| Humanity's Last Exam | 19.4% | — |
| SimpleQA Verified | 21.6% | — |
| MMLU-Pro | 83.5% | — |
| Confabulations | 13.3% | — |
| Vectara Hallucination Rate | 12.9% | — |
| GPQA (HELM) | 75.6% | — |
| LMArena Expert | 1377 | — |
Multimodal GPT-5 Mini leads
GPT-5 Mini: 35.0 (#80), Qwen2.5-VL 72B Instruct: 32.9 (#92)
| Benchmark | GPT-5 Mini | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Vision | 1202 | 1107 |
| Video-MME | — | 73.5% |
| GeoBench | — | 62% |
| VPCT | 40.2% | — |
| SpatialViz-Bench | — | 33.3% |
Multilingual Not comparable
GPT-5 Mini: 49.1 (#131), Qwen2.5-VL 72B Instruct: —
| Benchmark | GPT-5 Mini | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Non-English | 1363 | — |
| LMArena Chinese | 1387 | — |
| LMArena French | 1385 | — |
| LMArena German | 1366 | — |
| LMArena Japanese | 1342 | — |
| LMArena Korean | 1306 | — |
| LMArena Russian | 1362 | — |
| LMArena Spanish | 1355 | — |
Instruction Following Not comparable
GPT-5 Mini: 76.4 (#43), Qwen2.5-VL 72B Instruct: —
| Benchmark | GPT-5 Mini | Qwen2.5-VL 72B Instruct |
|---|---|---|
| IFEval | 92.7% | — |
| LMArena Instruction Following | 1357 | — |
Long Context Not comparable
GPT-5 Mini: 41.9 (#127), Qwen2.5-VL 72B Instruct: —
| Benchmark | GPT-5 Mini | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Fiction.LiveBench | 69.4% | — |
| LMArena Longer Query | 1355 | — |
Writing & Preference Not comparable
GPT-5 Mini: 55.4 (#143), Qwen2.5-VL 72B Instruct: —
| Benchmark | GPT-5 Mini | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Text | 1373 | — |
| LMArena Creative Writing | 1325 | — |
| Short-Story Creative Writing | 83.1% | — |
| EQ-Bench Creative Writing | 1313 | — |
| WildBench | 85.5% | — |
| LMArena Multi-Turn | 1363 | — |
Frequently asked questions
Is GPT-5 Mini better than Qwen2.5-VL 72B Instruct?
GPT-5 Mini is the stronger model overall, scoring 41.7 to 29.4 on the Noometry Index.
Which is cheaper, GPT-5 Mini or Qwen2.5-VL 72B Instruct?
GPT-5 Mini is cheaper. It lists at $0.25 per million input tokens and $2 per million output tokens; Qwen2.5-VL 72B Instruct lists at $2.80 and $8.40.
Which has the bigger context window?
GPT-5 Mini does, with 400K tokens against 131K.
How many benchmarks do GPT-5 Mini and Qwen2.5-VL 72B Instruct share?
2 benchmarks have published results for both models. GPT-5 Mini has 60 scored results on Noometry and Qwen2.5-VL 72B Instruct has 6.