GPT-4.1 Nano vs Qwen3.6 Plus
Qwen3.6 Plus leads GPT-4.1 Nano on the Artificial Analysis Intelligence Index, 27.0 to 7.8, and GPT-4.1 Nano costs 4.9x less per output token ($0.40 vs $1.95 per million). Updated October 22, 2026; 54 benchmarks have a result for both.
GPT-4.1 Nano or Qwen3.6 Plus: which to pick
Only Qwen3.6 Plus has a coding score, 44.1 on the Vibe Coding Index; GPT-4.1 Nano has none, so the two cannot be ranked on coding.
Pick GPT-4.1 Nano for output tokens 4.9x cheaper ($0.40 vs $1.95 per million) and a larger context window (1.05M against 1M tokens).
- Shared results
- 54
- GPT-4.1 Nano only
- 17
- Qwen3.6 Plus only
- 29
- Like-for-like categories
- 8 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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, six public coding benchmarks
No call
Only Qwen3.6 Plus has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.6 Plus
Qwen3.6 Plus leads, 27.0 against 7.8.
Same board, both measured
Reasoning
GPQA Diamond
Qwen3.6 Plus
Qwen3.6 Plus leads, 87.4% against 50.8%.
Same board, both measured
Math
AIME
Qwen3.6 Plus
Qwen3.6 Plus leads, 94.6% against 26.5%.
Same board, both measured
Knowledge
MMLU Pro
Qwen3.6 Plus
Qwen3.6 Plus leads, 87.7% against 63.5%.
Same board, both measured
Web design
Design Arena: websites
Qwen3.6 Plus
Qwen3.6 Plus leads, 1243 against 972.
Same board, both measured
Long documents
Listed context window
GPT-4.1 Nano
GPT-4.1 Nano takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4.1 Nano
GPT-4.1 Nano $0.0003, Qwen3.6 Plus $0.0013 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.6 Plus has the number, $1.19.
Directional only
At a glance
- Coding index
- GPT-4.1 Nano not benchmarked, Qwen3.6 Plus 44.1 from 3 benchmarks.
- Widest category
- Agentic work, 80.4 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: GPT-4.1 Nano 17.3% against Qwen3.6 Plus 97.7%, 80.4 points apart on a 0 to 100 scale.
- Output price
- GPT-4.1 Nano $0.40 against Qwen3.6 Plus $1.95 per million output tokens, 4.9x apart.
- Context window
- GPT-4.1 Nano takes 1.05M tokens, Qwen3.6 Plus 1M.
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 Nano | Bars | Qwen3.6 Plus | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 9 | ||
| Math | 0 | 4 | ||
| Knowledge | 0 | 10 | ||
| Web design | 0 | 6 | ||
| General | 0 | 17 | ||
| All shared boards | 0 | 54 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
| Benchmark | GPT-4.1 Nano | Qwen3.6 Plus | Leader |
|---|---|---|---|
| Aider polyglot | 8.9% | Not measured | Only GPT-4.1 Nano measured |
| LMArena WebDev | Not measured | 1461 | Only Qwen3.6 Plus measured |
| AA Coding Index | 11.1 | 54.5 | Qwen3.6 Plus |
| LiveCodeBench (Vals AI) | 42.7% | 86.0% | Qwen3.6 Plus |
| SWE-bench Verified (Vals AI) | Not measured | 73.4% | Only Qwen3.6 Plus measured |
| Vibe Code Bench (Vals AI) | Not measured | 25.6% | Only Qwen3.6 Plus measured |
| Code migration (Vals AI) | Not measured | 11.1% | Only Qwen3.6 Plus measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Qwen3.6 Plus measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 53.2% | Only Qwen3.6 Plus measured |
| LiveCodeBench (Artificial Analysis run) | 32.6% | Not measured | Only GPT-4.1 Nano measured |
| Terminal-Bench Hard (Artificial Analysis run) | 3.8% | 43.9% | Qwen3.6 Plus |
| WeirdML | 19.0% | Not measured | Only GPT-4.1 Nano measured |
| ALE-Bench | Not measured | 670.1 | Only Qwen3.6 Plus measured |
| LMArena Text: coding | 1306 | 1467 | Qwen3.6 Plus |
| LMArena Text: software and IT | 1305 | 1462 | Qwen3.6 Plus |
| LMArena WebDev: React | Not measured | 1454 | Only Qwen3.6 Plus measured |
| LMArena WebDev: HTML | Not measured | 1463 | Only Qwen3.6 Plus measured |
| LMArena WebDev: from an image | Not measured | 1472 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4.1 Nano | Qwen3.6 Plus | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.8 | 27.0 | Qwen3.6 Plus |
| Epoch Capabilities Index | 129.5 | 147.3 | Qwen3.6 Plus |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4.1 Nano | Qwen3.6 Plus | Leader |
|---|---|---|---|
| Finance Agent (Vals AI) | Not measured | 40.9% | Only Qwen3.6 Plus measured |
| Tax Agent Bench (Vals AI) | Not measured | 7.7% | Only Qwen3.6 Plus measured |
| Legal Research Bench (Vals AI) | Not measured | 14.9% | Only Qwen3.6 Plus measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 32.9% | Only Qwen3.6 Plus measured |
| τ²-Bench Telecom | 17.3% | 97.7% | Qwen3.6 Plus |
| Vending-Bench 2 | Not measured | $5,115 | Only Qwen3.6 Plus measured |
| Berkeley Function Calling Leaderboard (BFCL) | 33.1% | Not measured | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index09
| Benchmark | GPT-4.1 Nano | Qwen3.6 Plus | Leader |
|---|---|---|---|
| GPQA Diamond | 50.8% | 87.4% | Qwen3.6 Plus |
| MMMU Pro (Vals AI) | 55.0% | 84.2% | Qwen3.6 Plus |
| GPQA Diamond (Artificial Analysis run) | 51.2% | 88.2% | Qwen3.6 Plus |
| Humanity's Last Exam (Artificial Analysis run) | 3.8% | 27.8% | Qwen3.6 Plus |
| GPQA Diamond (Epoch AI run) | 48.9% | 88.4% | Qwen3.6 Plus |
| ARC-AGI | 0.0% | Not measured | Only GPT-4.1 Nano measured |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4.1 Nano measured |
| Chess puzzles | 0.0% | 14.0% | Qwen3.6 Plus |
| Mystery game puzzles | Not measured | 12.0% | Only Qwen3.6 Plus measured |
| LMArena Text: hard prompts | 1286 | 1448 | Qwen3.6 Plus |
| LMArena Text: expert | 1271 | 1454 | Qwen3.6 Plus |
| LMArena Text: hard prompts in English | 1293 | 1455 | Qwen3.6 Plus |
| Kagi LLM Benchmark | 33.3% | Not measured | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-4.1 Nano | Qwen3.6 Plus | Leader |
|---|---|---|---|
| AIME | 26.5% | 94.6% | Qwen3.6 Plus |
| MATH 500 (Vals AI) | 80.2% | Not measured | Only GPT-4.1 Nano measured |
| MGSM (Vals AI) | 69.3% | Not measured | Only GPT-4.1 Nano measured |
| AA Math Index | 24.0 | Not measured | Only GPT-4.1 Nano measured |
| AIME 2025 (Artificial Analysis run) | 24.0% | Not measured | Only GPT-4.1 Nano measured |
| OTIS Mock AIME | 28.9% | 93.3% | Qwen3.6 Plus |
| FrontierMath, tiers 1 to 3 | Not measured | 38.2% | Only Qwen3.6 Plus measured |
| MATH level 5 | 70.0% | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: math | 1274 | 1449 | Qwen3.6 Plus |
| LMArena Text: mathematical work | 1274 | 1448 | Qwen3.6 Plus |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index010
| Benchmark | GPT-4.1 Nano | Qwen3.6 Plus | Leader |
|---|---|---|---|
| MMLU Pro | 63.5% | 87.7% | Qwen3.6 Plus |
| LegalBench (Vals AI) | 61.1% | 84.2% | Qwen3.6 Plus |
| CaseLaw (Vals AI) | Not measured | 51.5% | Only Qwen3.6 Plus measured |
| CorpFin (Vals AI) | 42.1% | 61.9% | Qwen3.6 Plus |
| TaxEval (Vals AI) | 60.8% | 74.7% | Qwen3.6 Plus |
| MortgageTax (Vals AI) | 52.8% | 68.0% | Qwen3.6 Plus |
| MedQA (Vals AI) | 68.2% | Not measured | Only GPT-4.1 Nano measured |
| MedCode (Vals AI) | Not measured | 36.9% | Only Qwen3.6 Plus measured |
| MMLU Pro (Artificial Analysis run) | 65.7% | Not measured | Only GPT-4.1 Nano measured |
| SimpleQA Verified | 6.0% | 44.1% | Qwen3.6 Plus |
| LMArena Text: science | 1297 | 1439 | Qwen3.6 Plus |
| LMArena Text: medicine and healthcare | 1276 | 1442 | Qwen3.6 Plus |
| LMArena Text: legal and government | 1300 | 1437 | Qwen3.6 Plus |
| LMArena Text: business and finance | 1267 | 1430 | Qwen3.6 Plus |
| Neither model has a result on the other 4 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | GPT-4.1 Nano | Qwen3.6 Plus | Leader |
|---|---|---|---|
| Design Arena: websites | 972 | 1243 | Qwen3.6 Plus |
| Design Arena: UI components | 913 | 1230 | Qwen3.6 Plus |
| Design Arena: game dev | 970 | 1211 | Qwen3.6 Plus |
| Design Arena: data viz | 891 | 1228 | Qwen3.6 Plus |
| Design Arena: 3D | 924 | 1202 | Qwen3.6 Plus |
| Design Arena: all code categories | 962 | 1236 | Qwen3.6 Plus |
| Design Arena: SVG | Not measured | 1161 | Only Qwen3.6 Plus measured |
| Design Arena: ASCII art | Not measured | 1113 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index017
| Benchmark | GPT-4.1 Nano | Qwen3.6 Plus | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 44.9% | Only Qwen3.6 Plus measured |
| MedScribe (Vals AI) | Not measured | 77.0% | Only Qwen3.6 Plus measured |
| Vals Multimodal Index | Not measured | 51.5% | Only Qwen3.6 Plus measured |
| IFBench | 32.0% | 75.2% | Qwen3.6 Plus |
| Long context reasoning (AA-LCR) | 20.3% | 78.3% | Qwen3.6 Plus |
| DTBench | 52.5% | 81.9% | Qwen3.6 Plus |
| LMCA | 5.5% | 33.1% | Qwen3.6 Plus |
| Fiction.LiveBench | 25.0% | Not measured | Only GPT-4.1 Nano measured |
| CL-bench | Not measured | 20.3% | Only Qwen3.6 Plus measured |
| LMArena Text | 1285 | 1436 | Qwen3.6 Plus |
| LMArena Text: instruction following | 1266 | 1424 | Qwen3.6 Plus |
| LMArena Text: creative writing | 1260 | 1404 | Qwen3.6 Plus |
| LMArena Vision | 1063 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: English | 1303 | 1445 | Qwen3.6 Plus |
| LMArena Text: non-English | 1260 | 1424 | Qwen3.6 Plus |
| LMArena Text: Chinese | 1270 | 1477 | Qwen3.6 Plus |
| LMArena Text: German | 1288 | 1451 | Qwen3.6 Plus |
| LMArena Text: Japanese | 1198 | 1390 | Qwen3.6 Plus |
| LMArena Text: Korean | Not measured | 1379 | Only Qwen3.6 Plus measured |
| LMArena Text: French | Not measured | 1455 | Only Qwen3.6 Plus measured |
| LMArena Text: Spanish | Not measured | 1432 | Only Qwen3.6 Plus measured |
| LMArena Text: Russian | 1261 | 1434 | Qwen3.6 Plus |
| LMArena Text: Polish | Not measured | 1433 | Only Qwen3.6 Plus measured |
| LMArena Text: multi-turn | 1277 | 1438 | Qwen3.6 Plus |
| LMArena Text: longer queries | 1283 | 1439 | Qwen3.6 Plus |
| LMArena Text: writing and language | 1261 | 1418 | Qwen3.6 Plus |
| LMArena Text: entertainment and media | 1243 | 1402 | Qwen3.6 Plus |
| LMArena Vision: English | 1101 | Not measured | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 18 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4.1 Nano | Qwen3.6 Plus | 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
GPT-4.1 Nano costs less
Repository review
50K input + 3K output tokens
GPT-4.1 Nano costs less
Agent loop
200K input + 10K output tokens
GPT-4.1 Nano 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 Nano | Qwen3.6 Plus |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | April 14, 2025 | April 2, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $0.10 | $0.325 |
| Output $/Mtok | $0.40 | $1.95 |
| Coding index | Not benchmarked | 44.1 |
| Independent measurements behind it | 0 | 3 |
| Cost per solved task | Not computable | $1.19 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4.1 Nano better than Qwen3.6 Plus for coding?
Only Qwen3.6 Plus has a coding score, 44.1 on the Vibe Coding Index; GPT-4.1 Nano has none, so the two cannot be ranked on coding. Pick GPT-4.1 Nano for output tokens 4.9x cheaper ($0.40 vs $1.95 per million) and a larger context window (1.05M against 1M tokens).
Which is cheaper, GPT-4.1 Nano or Qwen3.6 Plus?
GPT-4.1 Nano costs $0.10 per million input tokens and $0.40 per million output tokens; Qwen3.6 Plus costs $0.325 and $1.95. Cost per solved task is known for Qwen3.6 Plus only.
Which has the bigger context window, GPT-4.1 Nano or Qwen3.6 Plus?
GPT-4.1 Nano, with 1.05M tokens against 1M.
How many benchmarks is the GPT-4.1 Nano vs Qwen3.6 Plus comparison based on?
54 benchmarks have a result for both models as of October 22, 2026. GPT-4.1 Nano's coding index rests on 0 independent benchmarks and Qwen3.6 Plus's on 3. Where only one model has a result, the page says so instead of naming a winner.