GPT-5.5 vs Inkling
GPT-5.5 leads Inkling on coding, 71.3 to 31.5 on the Vibe Coding Index, and Inkling costs 7.4x less per output token ($4.05 vs $30.00 per million). Updated October 22, 2026; 95 benchmarks have a result for both.
GPT-5.5 or Inkling: which to pick
Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 31.5 for Inkling, though on 5 benchmarks against 6.
Pick Inkling for output tokens 7.4x cheaper ($4.05 vs $30.00 per million) and a lower cost per solved task ($0.76 against $1.65).
- Shared results
- 95
- GPT-5.5 only
- 39
- Inkling only
- 7
- 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
GPT-5.5
GPT-5.5 scores 71.3 against 31.5.
5 and 6 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.5
GPT-5.5 leads, 38.4 against 25.0.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.5
GPT-5.5 leads, 36.4 against 22.5.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.5
GPT-5.5 leads, 93.2% against 87.1%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5.5
GPT-5.5 leads, 88.1% against 86.3%.
Same board, both measured
Web design
Design Arena: websites
GPT-5.5
GPT-5.5 leads, 1256 against 1224.
Same board, both measured
General
Vals Index
No call
Only Inkling has a Vals Index result, 29.0%.
Directional only
Long documents
Listed context window
GPT-5.5
GPT-5.5 takes 1.05M tokens against 524K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Inkling
GPT-5.5 $0.020, Inkling $0.0030 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Inkling
GPT-5.5 $1.65, Inkling $0.76.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.5 71.3 from 5 benchmarks, Inkling 31.5 from 6 benchmarks.
- Widest category
- Math, 30.2 points apart on average over 6 shared benchmarks.
- Widest single gap
- FrontierMath, tier 4: GPT-5.5 72.5% against Inkling 4.9%, 67.6 points apart on a 0 to 100 scale.
- Output price
- GPT-5.5 $30.00 against Inkling $4.05 per million output tokens, 7.4x apart.
- Context window
- GPT-5.5 takes 1.05M tokens, Inkling 524K.
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-5.5 | Bars | Inkling | Ties |
|---|---|---|---|---|
| Coding | 17 | 1 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 10 | 1 | ||
| Reasoning | 13 | 0 | ||
| Math | 5 | 1 | ||
| Knowledge | 9 | 2 | ||
| Web design | 9 | 0 | ||
| General | 25 | 0 | ||
| All shared boards | 90 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index171
| Benchmark | GPT-5.5 | Inkling | Leader |
|---|---|---|---|
| LiveBench coding | 85.1% | 64.0% | GPT-5.5 |
| LMArena WebDev | 1513 | 1414 | GPT-5.5 |
| AA Coding Index | 74.9 | 52.1 | GPT-5.5 |
| LiveCodeBench (Vals AI) | 85.3% | 85.5% | Inkling |
| SWE-bench Verified (Vals AI) | 82.6% | 77.6% | GPT-5.5 |
| Terminal-Bench 4 (Vals AI) | Not measured | 0.5% | Only Inkling measured |
| Vibe Code Bench (Vals AI) | 69.8% | 19.2% | GPT-5.5 |
| Code migration (Vals AI) | 45.2% | 11.8% | GPT-5.5 |
| ProgramBench (Vals AI) | 0.5% | 0.0% | GPT-5.5 |
| IOI (Vals AI) | Not measured | 14.9% | Only Inkling measured |
| Terminal-Bench 2.1 (Vals AI) | 76.4% | 47.6% | GPT-5.5 |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 7.3% | Only Inkling measured |
| SkillsBench (Vals AI) | 62.5% | 26.1% | GPT-5.5 |
| CyberBench (Vals AI) | Not measured | 66.8% | Only Inkling measured |
| SciCode | 56.1% | 47.0% | GPT-5.5 |
| Terminal-Bench Hard (Artificial Analysis run) | 60.6% | Not measured | Only GPT-5.5 measured |
| Terminal-Bench | 84.7% | Not measured | Only GPT-5.5 measured |
| FrontierCode | 43.0% | 14.0% | GPT-5.5 |
| FrontierSWE | Not measured | 4.1% | Only Inkling measured |
| GSO-Bench | 40.2% | Not measured | Only GPT-5.5 measured |
| WeirdML | 84.9% | 32.3% | GPT-5.5 |
| MirrorCode | 10.0% | Not measured | Only GPT-5.5 measured |
| ALE-Bench | 1943.0 | 946.0 | GPT-5.5 |
| LMArena Text: coding | 1494 | 1466 | GPT-5.5 |
| LMArena Text: software and IT | 1493 | 1465 | GPT-5.5 |
| LMArena WebDev: React | 1506 | 1404 | GPT-5.5 |
| LMArena WebDev: HTML | 1543 | 1399 | GPT-5.5 |
| LMArena WebDev: from an image | 1532 | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 11 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.5 | Inkling | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.4 | 25.0 | GPT-5.5 |
| Epoch Capabilities Index | 159.7 | 148.4 | GPT-5.5 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index101
| Benchmark | GPT-5.5 | Inkling | Leader |
|---|---|---|---|
| AA Agentic Index | 36.4 | 22.5 | GPT-5.5 |
| Design Arena: agents building web apps | 1117 | 1196 | Inkling |
| Design Arena: agents building full-stack apps | 1089 | Not measured | Only GPT-5.5 measured |
| Design Arena: agents building mobile apps | 1142 | Not measured | Only GPT-5.5 measured |
| Design Arena: agents building Android apps | 1164 | Not measured | Only GPT-5.5 measured |
| Design Arena: agents building Godot games | 1173 | Not measured | Only GPT-5.5 measured |
| Design Arena: agents building games | 1179 | Not measured | Only GPT-5.5 measured |
| Design Arena: HTML slides | 1017 | Not measured | Only GPT-5.5 measured |
| Design Arena: PowerPoint slides | 1084 | Not measured | Only GPT-5.5 measured |
| LiveBench research | 61.6% | 59.9% | GPT-5.5 |
| LiveBench browser | 48.0% | 16.0% | GPT-5.5 |
| LiveBench long agentic | 44.6% | 14.1% | GPT-5.5 |
| SREBench (Vals AI) | 3.8% | 0.0% | GPT-5.5 |
| Finance Agent (Vals AI) | 51.8% | 46.6% | GPT-5.5 |
| Tax Agent Bench (Vals AI) | 21.8% | 15.3% | GPT-5.5 |
| Legal Research Bench (Vals AI) | 40.4% | 28.4% | GPT-5.5 |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 3.8% | Only Inkling measured |
| Excel Modeling Benchmark (Vals AI) | 64.5% | 38.4% | GPT-5.5 |
| Time Horizon Index (Vals AI) | 8.3% | Not measured | Only GPT-5.5 measured |
| τ²-Bench Telecom | 93.9% | Not measured | Only GPT-5.5 measured |
| APEX-Agents | 55.1% | 33.8% | GPT-5.5 |
| Remote Labor Index | 6.3% | Not measured | Only GPT-5.5 measured |
| OSWorld 2.0 | 13.0% | Not measured | Only GPT-5.5 measured |
| DeepResearch Bench | 54.0% | Not measured | Only GPT-5.5 measured |
| PostTrainBench | 27.2% | Not measured | Only GPT-5.5 measured |
| Vending-Bench 2 | $7,524 | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 15 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index130
| Benchmark | GPT-5.5 | Inkling | Leader |
|---|---|---|---|
| GPQA Diamond | 93.2% | 87.1% | GPT-5.5 |
| LiveBench reasoning | 89.7% | 78.3% | GPT-5.5 |
| MMMU Pro (Vals AI) | 88.3% | 78.5% | GPT-5.5 |
| GPQA Diamond (Artificial Analysis run) | 93.5% | 87.2% | GPT-5.5 |
| Humanity's Last Exam (Artificial Analysis run) | 45.8% | 31.9% | GPT-5.5 |
| GPQA Diamond (Epoch AI run) | 90.7% | 88.3% | GPT-5.5 |
| ARC-AGI | 95.0% | 79.5% | GPT-5.5 |
| ARC-AGI-2 | 85.0% | 36.5% | GPT-5.5 |
| SimpleBench | 69.0% | 50.0% | GPT-5.5 |
| Chess puzzles | 63.0% | 21.0% | GPT-5.5 |
| Mystery game puzzles | 56.0% | Not measured | Only GPT-5.5 measured |
| EBR-bench | 34.3% | Not measured | Only GPT-5.5 measured |
| LMArena Text: hard prompts | 1489 | 1451 | GPT-5.5 |
| LMArena Text: expert | 1507 | 1466 | GPT-5.5 |
| LMArena Text: hard prompts in English | 1483 | 1448 | GPT-5.5 |
| LMArena Vision: diagrams | 1325 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: homework | 1332 | Not measured | Only GPT-5.5 measured |
| Kagi LLM Benchmark | 88.8% | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index51
| Benchmark | GPT-5.5 | Inkling | Leader |
|---|---|---|---|
| OTIS Mock AIME | 84.4% | 88.9% | Inkling |
| FrontierMath, tiers 1 to 3 | 85.3% | 33.3% | GPT-5.5 |
| FrontierMath, tier 4 | 72.5% | 4.9% | GPT-5.5 |
| ProofBench | 50.0% | 0.0% | GPT-5.5 |
| LMArena Text: math | 1487 | 1479 | GPT-5.5 |
| LMArena Text: mathematical work | 1496 | 1460 | GPT-5.5 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index92
| Benchmark | GPT-5.5 | Inkling | Leader |
|---|---|---|---|
| MMLU Pro | 88.1% | 86.3% | GPT-5.5 |
| LegalBench (Vals AI) | 86.5% | 83.0% | GPT-5.5 |
| CaseLaw (Vals AI) | 66.2% | Not measured | Only GPT-5.5 measured |
| CorpFin (Vals AI) | 68.4% | 68.6% | Inkling |
| TaxEval (Vals AI) | 75.0% | 75.3% | Inkling |
| MortgageTax (Vals AI) | 68.8% | 64.0% | GPT-5.5 |
| MedCode (Vals AI) | 49.1% | 41.2% | GPT-5.5 |
| SimpleQA Verified | 63.0% | 40.3% | GPT-5.5 |
| LMArena Text: science | 1485 | 1455 | GPT-5.5 |
| LMArena Text: medicine and healthcare | 1465 | 1447 | GPT-5.5 |
| LMArena Text: legal and government | 1491 | 1448 | GPT-5.5 |
| LMArena Text: business and finance | 1478 | 1438 | GPT-5.5 |
| FACTS Benchmark Suite | 66.7% | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index90
| Benchmark | GPT-5.5 | Inkling | Leader |
|---|---|---|---|
| Design Arena: websites | 1256 | 1224 | GPT-5.5 |
| Design Arena: UI components | 1257 | 1198 | GPT-5.5 |
| Design Arena: game dev | 1293 | 1165 | GPT-5.5 |
| Design Arena: data viz | 1264 | 1156 | GPT-5.5 |
| Design Arena: 3D | 1197 | 1160 | GPT-5.5 |
| Design Arena: all code categories | 1260 | 1205 | GPT-5.5 |
| Design Arena: SVG | 1234 | 1108 | GPT-5.5 |
| Design Arena: ASCII art | 1255 | 1089 | GPT-5.5 |
| LiveBench design | 70.3% | 58.3% | GPT-5.5 |
GeneralLike-for-likePublic boards, shown as published, kept out of the index250
| Benchmark | GPT-5.5 | Inkling | Leader |
|---|---|---|---|
| Vals Index | Not measured | 29.0% | Only Inkling measured |
| LiveBench data analysis | 81.6% | 72.8% | GPT-5.5 |
| Public Benefits Bench (Vals AI) | 60.9% | 58.5% | GPT-5.5 |
| SAGE (Vals AI) | 51.5% | 36.5% | GPT-5.5 |
| MedScribe (Vals AI) | 86.9% | 85.4% | GPT-5.5 |
| Vals Multimodal Index | 68.1% | 49.4% | GPT-5.5 |
| IFBench | 75.9% | Not measured | Only GPT-5.5 measured |
| Long context reasoning (AA-LCR) | 84.3% | 77.3% | GPT-5.5 |
| DTBench | 96.0% | 87.5% | GPT-5.5 |
| LMCA | 54.3% | 37.6% | GPT-5.5 |
| Surface Evolver Bench | 88.1% | Not measured | Only GPT-5.5 measured |
| Furniture assembly | 44.2% | Not measured | Only GPT-5.5 measured |
| ExploitBench | 47.4% | Not measured | Only GPT-5.5 measured |
| CL-bench Life | 22.2% | Not measured | Only GPT-5.5 measured |
| LMArena Text | 1471 | 1442 | GPT-5.5 |
| LMArena Text: instruction following | 1478 | 1425 | GPT-5.5 |
| LMArena Text: creative writing | 1455 | 1390 | GPT-5.5 |
| LMArena Vision | 1297 | Not measured | Only GPT-5.5 measured |
| LMArena Text: English | 1470 | 1442 | GPT-5.5 |
| LMArena Text: non-English | 1467 | 1434 | GPT-5.5 |
| LMArena Text: Chinese | 1534 | 1493 | GPT-5.5 |
| LMArena Text: German | 1480 | 1445 | GPT-5.5 |
| LMArena Text: Japanese | 1499 | 1429 | GPT-5.5 |
| LMArena Text: Korean | 1460 | 1403 | GPT-5.5 |
| LMArena Text: French | 1485 | 1455 | GPT-5.5 |
| LMArena Text: Spanish | 1468 | 1449 | GPT-5.5 |
| LMArena Text: Russian | 1473 | 1430 | GPT-5.5 |
| LMArena Text: Polish | 1465 | 1450 | GPT-5.5 |
| LMArena Text: multi-turn | 1476 | 1437 | GPT-5.5 |
| LMArena Text: longer queries | 1484 | 1435 | GPT-5.5 |
| LMArena Text: writing and language | 1466 | 1404 | GPT-5.5 |
| LMArena Text: entertainment and media | 1449 | 1394 | GPT-5.5 |
| LMArena Vision: English | 1292 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: Chinese | 1360 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: reading text | 1306 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: humor | 1293 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: recognizing things | 1231 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: creative writing | 1301 | Not measured | Only GPT-5.5 measured |
| LMArena Document | 1486 | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 7 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.5 | Inkling | 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
Inkling costs less
Repository review
50K input + 3K output tokens
Inkling costs less
Agent loop
200K input + 10K output tokens
Inkling 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-5.5 | Thinking Machines Inkling |
|---|---|---|
| Maker | OpenAI | Thinking Machines |
| Weights | No public weights listed | Open weights |
| Released | April 24, 2026 | July 17, 2026 |
| Context window | 1.05M | 524K |
| Input $/Mtok | $5.00 | $0.975 |
| Output $/Mtok | $30.00 | $4.05 |
| Coding index | 71.3 | 31.5 |
| Independent measurements behind it | 5 | 6 |
| Cost per solved task | $1.65 | $0.76 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.5 better than Inkling for coding?
Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 31.5 for Inkling, though on 5 benchmarks against 6. Pick Inkling for output tokens 7.4x cheaper ($4.05 vs $30.00 per million) and a lower cost per solved task ($0.76 against $1.65).
Which is cheaper, GPT-5.5 or Inkling?
GPT-5.5 costs $5.00 per million input tokens and $30.00 per million output tokens; Inkling costs $0.975 and $4.05. Per solved SWE-bench Verified task, GPT-5.5 costs $1.65 and Inkling $0.76.
Which has the bigger context window, GPT-5.5 or Inkling?
GPT-5.5, with 1.05M tokens against 524K.
How many benchmarks is the GPT-5.5 vs Inkling comparison based on?
95 benchmarks have a result for both models as of October 22, 2026. GPT-5.5's coding index rests on 5 independent benchmarks and Inkling's on 6. Where only one model has a result, the page says so instead of naming a winner.