GPT-4.1 vs GPT-5.5 Pro
GPT-4.1 costs 22.5x less per output token than GPT-5.5 Pro ($8.00 vs $180.00 per million). Updated October 21, 2026; 8 benchmarks have a result for both.
GPT-4.1 or GPT-5.5 Pro: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4.1 for output tokens 22.5x cheaper ($8.00 vs $180.00 per million) and work measured by Epoch Capabilities Index or ARC-AGI, where it leads.
- Shared results
- 8
- GPT-4.1 only
- 84
- GPT-5.5 Pro only
- 1
- Like-for-like categories
- 4 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only GPT-4.1 has a AA Intelligence Index result, 12.7.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-4.1 has a GPQA Diamond result, 65.4%.
Directional only
Math
AIME
No call
Only GPT-4.1 has a AIME result, 39.6%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4.1 has a MMLU Pro result, 80.5%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-4.1 has a Design Arena: websites result, 1039.
Directional only
Long documents
Listed context window
GPT-5.5 Pro
GPT-5.5 Pro takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4.1
GPT-4.1 $0.0060, GPT-5.5 Pro $0.120 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-4.1 has the number, $0.37.
Directional only
At a glance
- Coding index
- GPT-4.1 not benchmarked, GPT-5.5 Pro not benchmarked.
- Widest category
- Math, 81.8 points apart on average over 1 shared benchmark.
- Widest single gap
- ARC-AGI: GPT-4.1 5.5% against GPT-5.5 Pro 96.5%, 91.0 points apart on a 0 to 100 scale.
- Output price
- GPT-4.1 $8.00 against GPT-5.5 Pro $180.00 per million output tokens, 22.5x apart.
- Context window
- GPT-4.1 takes 1.05M tokens, GPT-5.5 Pro 1.05M.
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 | Bars | GPT-5.5 Pro | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 4 | ||
| Math | 0 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 8 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index11 boards, none shared
| Benchmark | GPT-4.1 | GPT-5.5 Pro | Leader |
|---|---|---|---|
| Aider polyglot | 52.4% | Not measured | Only GPT-4.1 measured |
| SWE-bench Verified | 39.6% | Not measured | Only GPT-4.1 measured |
| SWE-bench Multimodal | 31.1% | Not measured | Only GPT-4.1 measured |
| LiveCodeBench (Vals AI) | 54.7% | Not measured | Only GPT-4.1 measured |
| LiveCodeBench (Artificial Analysis run) | 45.7% | Not measured | Only GPT-4.1 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 13.6% | Not measured | Only GPT-4.1 measured |
| WeirdML | 39.0% | Not measured | Only GPT-4.1 measured |
| ALE-Bench | 558.1 | Not measured | Only GPT-4.1 measured |
| LMArena Text: coding | 1390 | Not measured | Only GPT-4.1 measured |
| LMArena Text: software and IT | 1391 | Not measured | Only GPT-4.1 measured |
| SciCode | 4.6% | Not measured | Only GPT-4.1 measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4.1 | GPT-5.5 Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.7 | Not measured | Only GPT-4.1 measured |
| Epoch Capabilities Index | 136.7 | 162.9 | GPT-5.5 Pro |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-4.1 | GPT-5.5 Pro | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 47.1% | Not measured | Only GPT-4.1 measured |
| Berkeley Function Calling Leaderboard (BFCL) | 54.0% | Not measured | Only GPT-4.1 measured |
| BrowseComp-Plus | 36.4% | Not measured | Only GPT-4.1 measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-4.1 | GPT-5.5 Pro | Leader |
|---|---|---|---|
| GPQA Diamond | 65.4% | Not measured | Only GPT-4.1 measured |
| MMMU Pro (Vals AI) | 72.4% | Not measured | Only GPT-4.1 measured |
| GPQA Diamond (Artificial Analysis run) | 66.6% | Not measured | Only GPT-4.1 measured |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | Not measured | Only GPT-4.1 measured |
| GPQA Diamond (Epoch AI run) | 66.9% | Not measured | Only GPT-4.1 measured |
| ARC-AGI | 5.5% | 96.5% | GPT-5.5 Pro |
| ARC-AGI-2 | 0.4% | 84.6% | GPT-5.5 Pro |
| SimpleBench | 27.0% | 76.9% | GPT-5.5 Pro |
| Chess puzzles | 3.0% | 62.0% | GPT-5.5 Pro |
| LMArena Text: hard prompts | 1384 | Not measured | Only GPT-4.1 measured |
| LMArena Text: expert | 1364 | Not measured | Only GPT-4.1 measured |
| LMArena Text: hard prompts in English | 1393 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: diagrams | 1215 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: homework | 1248 | Not measured | Only GPT-4.1 measured |
| Kagi LLM Benchmark | 52.3% | Not measured | Only GPT-4.1 measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4.1 | GPT-5.5 Pro | Leader |
|---|---|---|---|
| AIME | 39.6% | Not measured | Only GPT-4.1 measured |
| MATH 500 (Vals AI) | 87.2% | Not measured | Only GPT-4.1 measured |
| MGSM (Vals AI) | 87.7% | Not measured | Only GPT-4.1 measured |
| AA Math Index | 34.7 | Not measured | Only GPT-4.1 measured |
| AIME 2025 (Artificial Analysis run) | 34.7% | Not measured | Only GPT-4.1 measured |
| OTIS Mock AIME | 38.3% | Not measured | Only GPT-4.1 measured |
| FrontierMath, tiers 1 to 3 | 6.0% | 87.7% | GPT-5.5 Pro |
| FrontierMath, tier 4 | Not measured | 78.0% | Only GPT-5.5 Pro measured |
| MATH level 5 | 83.0% | Not measured | Only GPT-4.1 measured |
| LMArena Text: math | 1369 | Not measured | Only GPT-4.1 measured |
| LMArena Text: mathematical work | 1360 | Not measured | Only GPT-4.1 measured |
| Neither model has a result on the other 2 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index15 boards, none shared
| Benchmark | GPT-4.1 | GPT-5.5 Pro | Leader |
|---|---|---|---|
| MMLU Pro | 80.5% | Not measured | Only GPT-4.1 measured |
| LegalBench (Vals AI) | 83.1% | Not measured | Only GPT-4.1 measured |
| CaseLaw (Vals AI) | 69.9% | Not measured | Only GPT-4.1 measured |
| CorpFin (Vals AI) | 63.0% | Not measured | Only GPT-4.1 measured |
| TaxEval (Vals AI) | 75.1% | Not measured | Only GPT-4.1 measured |
| MortgageTax (Vals AI) | 65.9% | Not measured | Only GPT-4.1 measured |
| MedQA (Vals AI) | 91.2% | Not measured | Only GPT-4.1 measured |
| MMLU Pro (Artificial Analysis run) | 80.6% | Not measured | Only GPT-4.1 measured |
| SimpleQA Verified | 31.1% | Not measured | Only GPT-4.1 measured |
| GeoBench | 72.0% | Not measured | Only GPT-4.1 measured |
| LMArena Text: science | 1382 | Not measured | Only GPT-4.1 measured |
| LMArena Text: medicine and healthcare | 1379 | Not measured | Only GPT-4.1 measured |
| LMArena Text: legal and government | 1399 | Not measured | Only GPT-4.1 measured |
| LMArena Text: business and finance | 1369 | Not measured | Only GPT-4.1 measured |
| FACTS Benchmark Suite | 45.8% | Not measured | Only GPT-4.1 measured |
| 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 | GPT-5.5 Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1039 | Not measured | Only GPT-4.1 measured |
| Design Arena: UI components | 1000 | Not measured | Only GPT-4.1 measured |
| Design Arena: game dev | 1080 | Not measured | Only GPT-4.1 measured |
| Design Arena: data viz | 1104 | Not measured | Only GPT-4.1 measured |
| Design Arena: 3D | 850 | Not measured | Only GPT-4.1 measured |
| Design Arena: all code categories | 1026 | Not measured | Only GPT-4.1 measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4.1 | GPT-5.5 Pro | Leader |
|---|---|---|---|
| IFBench | 43.0% | Not measured | Only GPT-4.1 measured |
| Long context reasoning (AA-LCR) | 68.3% | Not measured | Only GPT-4.1 measured |
| DTBench | 68.3% | 96.0% | GPT-5.5 Pro |
| LMCA | 25.6% | 53.9% | GPT-5.5 Pro |
| Fiction.LiveBench | 63.9% | Not measured | Only GPT-4.1 measured |
| LMArena Text | 1383 | Not measured | Only GPT-4.1 measured |
| LMArena Text: instruction following | 1367 | Not measured | Only GPT-4.1 measured |
| LMArena Text: creative writing | 1363 | Not measured | Only GPT-4.1 measured |
| LMArena Vision | 1210 | Not measured | Only GPT-4.1 measured |
| LMArena Text: English | 1392 | Not measured | Only GPT-4.1 measured |
| LMArena Text: non-English | 1370 | Not measured | Only GPT-4.1 measured |
| LMArena Text: Chinese | 1382 | Not measured | Only GPT-4.1 measured |
| LMArena Text: German | 1381 | Not measured | Only GPT-4.1 measured |
| LMArena Text: Japanese | 1319 | Not measured | Only GPT-4.1 measured |
| LMArena Text: Korean | 1338 | Not measured | Only GPT-4.1 measured |
| LMArena Text: French | 1382 | Not measured | Only GPT-4.1 measured |
| LMArena Text: Spanish | 1376 | Not measured | Only GPT-4.1 measured |
| LMArena Text: Russian | 1377 | Not measured | Only GPT-4.1 measured |
| LMArena Text: Polish | 1389 | Not measured | Only GPT-4.1 measured |
| LMArena Text: multi-turn | 1397 | Not measured | Only GPT-4.1 measured |
| LMArena Text: longer queries | 1385 | Not measured | Only GPT-4.1 measured |
| LMArena Text: writing and language | 1371 | Not measured | Only GPT-4.1 measured |
| LMArena Text: entertainment and media | 1365 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: English | 1209 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: Chinese | 1226 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: reading text | 1218 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: humor | 1196 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: captioning | 1207 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: recognizing things | 1208 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: creative writing | 1210 | Not measured | Only GPT-4.1 measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4.1 | GPT-5.5 Pro | 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 costs less
Repository review
50K input + 3K output tokens
GPT-4.1 costs less
Agent loop
200K input + 10K output tokens
GPT-4.1 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 | OpenAI GPT-5.5 Pro |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | April 14, 2025 | April 24, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $2.00 | $30.00 |
| Output $/Mtok | $8.00 | $180.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | $0.37 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4.1 better than GPT-5.5 Pro for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4.1 for output tokens 22.5x cheaper ($8.00 vs $180.00 per million) and work measured by Epoch Capabilities Index or ARC-AGI, where it leads.
Which is cheaper, GPT-4.1 or GPT-5.5 Pro?
GPT-4.1 costs $2.00 per million input tokens and $8.00 per million output tokens; GPT-5.5 Pro costs $30.00 and $180.00. Cost per solved task is known for GPT-4.1 only.
Which has the bigger context window, GPT-4.1 or GPT-5.5 Pro?
GPT-5.5 Pro, with 1.05M tokens against 1.05M.
How many benchmarks is the GPT-4.1 vs GPT-5.5 Pro comparison based on?
8 benchmarks have a result for both models as of October 21, 2026. GPT-4.1's coding index rests on 0 independent benchmarks and GPT-5.5 Pro's on 0. Where only one model has a result, the page says so instead of naming a winner.