GPT-4.1 Mini vs Qwen2.5 Coder 32B Instruct
Updated October 21, 2026. 30 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Qwen2.5 Coder 32B Instruct for coding: it scores 30.5 on the Vibe Coding Index against 28.5 for GPT-4.1 Mini.
Pick GPT-4.1 Mini when the context window is larger, 1.05M against 33K tokens, or when what matters is Aider polyglot or LiveCodeBench (Artificial Analysis run), where it leads.
- Shared results
- 30
- GPT-4.1 Mini only
- 54
- Qwen2.5 Coder 32B Instruct only
- 5
- Like-for-like categories
- 6 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, four public coding benchmarks
Qwen2.5 Coder 32B Instruct
Qwen2.5 Coder 32B Instruct scores 30.5 against 28.5.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
GPT-4.1 Mini
GPT-4.1 Mini leads, 10.2 against 6.7.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-4.1 Mini has a GPQA Diamond result, 67.9%.
Directional only
Math
AIME
No call
Only GPT-4.1 Mini has a AIME result, 49.4%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4.1 Mini has a MMLU Pro result, 77.2%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-4.1 Mini has a Design Arena: websites result, 997.
Directional only
Long documents
Listed context window
GPT-4.1 Mini
GPT-4.1 Mini takes 1.05M tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 Coder 32B Instruct
GPT-4.1 Mini $0.0012, Qwen2.5 Coder 32B Instruct $0.0012 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-4.1 Mini has the number, $1.818.
Directional only
At a glance
- Coding index
- GPT-4.1 Mini 28.5 from 2 benchmarks, Qwen2.5 Coder 32B Instruct 30.5 from 2 benchmarks.
- Widest category
- General, 19.3 points apart on average over 11 shared benchmarks.
- Widest single gap
- LMArena Text: entertainment and media: GPT-4.1 Mini 1300 against Qwen2.5 Coder 32B Instruct 1150, 25.0 points apart on a 0 to 100 scale.
- Output price
- GPT-4.1 Mini $1.60 against Qwen2.5 Coder 32B Instruct $1.00 per million output tokens, 1.6x apart.
- Context window
- GPT-4.1 Mini takes 1.05M tokens, Qwen2.5 Coder 32B Instruct 33K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | GPT-4.1 Mini | Bars | Qwen2.5 Coder 32B Instruct | Ties |
|---|---|---|---|---|
| Coding | 4 | 1 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 5 | 0 | ||
| General | 11 | 0 | ||
| All shared boards | 29 | 1 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index41
| Benchmark | GPT-4.1 Mini | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| Aider polyglot | 32.4% | 16.4% | GPT-4.1 Mini |
| SWE-bench Verified | 23.9% | 47.0% | Qwen2.5 Coder 32B Instruct |
| AA Coding Index | 20.2 | Not measured | Only GPT-4.1 Mini measured |
| LiveCodeBench (Vals AI) | 58.2% | Not measured | Only GPT-4.1 Mini measured |
| LiveCodeBench (Artificial Analysis run) | 48.3% | 29.5% | GPT-4.1 Mini |
| Terminal-Bench Hard (Artificial Analysis run) | 7.6% | Not measured | Only GPT-4.1 Mini measured |
| WeirdML | 37.6% | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: coding | 1367 | 1276 | GPT-4.1 Mini |
| LMArena Text: software and IT | 1360 | 1261 | GPT-4.1 Mini |
| Neither model has a result on the other 29 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-4.1 Mini | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.2 | 6.7 | GPT-4.1 Mini |
| Epoch Capabilities Index | 134.9 | 119.5 | GPT-4.1 Mini |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-4.1 Mini | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 52.9% | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GPT-4.1 Mini | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond | 67.9% | Not measured | Only GPT-4.1 Mini measured |
| MMMU Pro (Vals AI) | 70.5% | Not measured | Only GPT-4.1 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 66.4% | 41.7% | GPT-4.1 Mini |
| Humanity's Last Exam (Artificial Analysis run) | 5.0% | 3.5% | GPT-4.1 Mini |
| GPQA Diamond (Epoch AI run) | 65.8% | Not measured | Only GPT-4.1 Mini measured |
| ARC-AGI | 3.5% | Not measured | Only GPT-4.1 Mini measured |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4.1 Mini measured |
| Chess puzzles | 1.0% | Not measured | Only GPT-4.1 Mini measured |
| Mystery game puzzles | 7.0% | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: hard prompts | 1349 | 1251 | GPT-4.1 Mini |
| LMArena Text: expert | 1338 | 1221 | GPT-4.1 Mini |
| LMArena Text: hard prompts in English | 1362 | 1269 | GPT-4.1 Mini |
| LMArena Vision: diagrams | 1182 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: homework | 1214 | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-4.1 Mini | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| AIME | 49.4% | Not measured | Only GPT-4.1 Mini measured |
| MATH 500 (Vals AI) | 88.0% | Not measured | Only GPT-4.1 Mini measured |
| MGSM (Vals AI) | 87.8% | Not measured | Only GPT-4.1 Mini measured |
| AA Math Index | 46.3 | Not measured | Only GPT-4.1 Mini measured |
| AIME 2025 (Artificial Analysis run) | 46.3% | Not measured | Only GPT-4.1 Mini measured |
| OTIS Mock AIME | 44.7% | Not measured | Only GPT-4.1 Mini measured |
| FrontierMath, tiers 1 to 3 | 6.7% | Not measured | Only GPT-4.1 Mini measured |
| MATH level 5 | 87.3% | Not measured | Only GPT-4.1 Mini measured |
| GSM8K | Not measured | 93.0% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: math | 1343 | 1251 | GPT-4.1 Mini |
| LMArena Text: mathematical work | 1347 | 1243 | GPT-4.1 Mini |
| Neither model has a result on the other 2 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GPT-4.1 Mini | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| MMLU Pro | 77.2% | Not measured | Only GPT-4.1 Mini measured |
| LegalBench (Vals AI) | 78.0% | Not measured | Only GPT-4.1 Mini measured |
| CorpFin (Vals AI) | 57.9% | Not measured | Only GPT-4.1 Mini measured |
| TaxEval (Vals AI) | 71.9% | Not measured | Only GPT-4.1 Mini measured |
| MortgageTax (Vals AI) | 65.5% | Not measured | Only GPT-4.1 Mini measured |
| MedQA (Vals AI) | 84.6% | Not measured | Only GPT-4.1 Mini measured |
| MMLU Pro (Artificial Analysis run) | 78.1% | 63.5% | GPT-4.1 Mini |
| SimpleQA Verified | 12.7% | Not measured | Only GPT-4.1 Mini measured |
| MMLU | Not measured | 79.1% | Only Qwen2.5 Coder 32B Instruct measured |
| AI2 Reasoning Challenge | Not measured | 70.5% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: science | 1328 | 1221 | GPT-4.1 Mini |
| LMArena Text: medicine and healthcare | 1324 | 1187 | GPT-4.1 Mini |
| LMArena Text: legal and government | 1343 | 1257 | GPT-4.1 Mini |
| LMArena Text: business and finance | 1322 | 1224 | GPT-4.1 Mini |
| Neither model has a result on the other 3 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-4.1 Mini | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 997 | Not measured | Only GPT-4.1 Mini measured |
| Design Arena: UI components | 961 | Not measured | Only GPT-4.1 Mini measured |
| Design Arena: game dev | 1071 | Not measured | Only GPT-4.1 Mini measured |
| Design Arena: data viz | 1034 | Not measured | Only GPT-4.1 Mini measured |
| Design Arena: 3D | 837 | Not measured | Only GPT-4.1 Mini measured |
| Design Arena: all code categories | 994 | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index110
| Benchmark | GPT-4.1 Mini | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| IFBench | 38.3% | Not measured | Only GPT-4.1 Mini measured |
| Long context reasoning (AA-LCR) | 44.0% | Not measured | Only GPT-4.1 Mini measured |
| DTBench | 68.8% | Not measured | Only GPT-4.1 Mini measured |
| LMCA | 21.1% | Not measured | Only GPT-4.1 Mini measured |
| Fiction.LiveBench | 44.4% | Not measured | Only GPT-4.1 Mini measured |
| HellaSwag | Not measured | 83.0% | Only Qwen2.5 Coder 32B Instruct measured |
| WinoGrande | Not measured | 80.8% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text | 1341 | 1230 | GPT-4.1 Mini |
| LMArena Text: instruction following | 1333 | 1223 | GPT-4.1 Mini |
| LMArena Text: creative writing | 1299 | 1174 | GPT-4.1 Mini |
| LMArena Vision | 1181 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: English | 1356 | 1248 | GPT-4.1 Mini |
| LMArena Text: non-English | 1318 | 1205 | GPT-4.1 Mini |
| LMArena Text: Chinese | 1329 | 1222 | GPT-4.1 Mini |
| LMArena Text: German | 1350 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: Japanese | 1290 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: Korean | 1298 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: French | 1358 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: Spanish | 1319 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: Russian | 1324 | 1228 | GPT-4.1 Mini |
| LMArena Text: Polish | 1326 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: multi-turn | 1354 | 1222 | GPT-4.1 Mini |
| LMArena Text: longer queries | 1344 | 1251 | GPT-4.1 Mini |
| LMArena Text: writing and language | 1319 | 1191 | GPT-4.1 Mini |
| LMArena Text: entertainment and media | 1300 | 1150 | GPT-4.1 Mini |
| LMArena Vision: English | 1191 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: Chinese | 1186 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: reading text | 1188 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: humor | 1182 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: captioning | 1174 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: recognizing things | 1187 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: creative writing | 1182 | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4.1 Mini | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Qwen2.5 Coder 32B Instruct costs less
Repository review
50K input + 3K output tokens
GPT-4.1 Mini costs less
Agent loop
200K input + 10K output tokens
GPT-4.1 Mini costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-4.1 Mini | Qwen2.5 Coder 32B Instruct |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | April 14, 2025 | November 11, 2024 |
| Context window | 1.05M | 33K |
| Input $/Mtok | $0.40 | $0.66 |
| Output $/Mtok | $1.60 | $1.00 |
| Coding index | 28.5 | 30.5 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $1.818 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4.1 Mini better than Qwen2.5 Coder 32B Instruct for coding?
Pick Qwen2.5 Coder 32B Instruct for coding: it scores 30.5 on the Vibe Coding Index against 28.5 for GPT-4.1 Mini. Pick GPT-4.1 Mini when the context window is larger, 1.05M against 33K tokens, or when what matters is Aider polyglot or LiveCodeBench (Artificial Analysis run), where it leads.
Which is cheaper, GPT-4.1 Mini or Qwen2.5 Coder 32B Instruct?
GPT-4.1 Mini costs $0.40 per million input tokens and $1.60 per million output tokens; Qwen2.5 Coder 32B Instruct costs $0.66 and $1.00. Cost per solved task is known for GPT-4.1 Mini only.
Which has the bigger context window, GPT-4.1 Mini or Qwen2.5 Coder 32B Instruct?
GPT-4.1 Mini, with 1.05M tokens against 33K.
How many benchmarks is the GPT-4.1 Mini vs Qwen2.5 Coder 32B Instruct comparison based on?
30 benchmarks have a result for both models as of October 21, 2026. GPT-4.1 Mini's coding index rests on 2 independent benchmarks and Qwen2.5 Coder 32B Instruct's on 2. Where only one model has a result, the page says so instead of naming a winner.