GPT-5.5 vs Inkling Small
GPT-5.5 leads Inkling Small on coding, 71.3 to 27.3 on the Vibe Coding Index, and Inkling Small costs 25.0x less per output token ($1.20 vs $30.00 per million). Updated October 22, 2026; 79 benchmarks have a result for both.
GPT-5.5 or Inkling Small: which to pick
Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 27.3 for Inkling Small.
Pick Inkling Small for output tokens 25.0x cheaper ($1.20 vs $30.00 per million) and a lower cost per solved task ($0.16 against $1.65).
- Shared results
- 79
- GPT-5.5 only
- 55
- Inkling Small only
- 5
- Like-for-like categories
- 7 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 27.3.
5 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.5
GPT-5.5 leads, 38.4 against 25.7.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.5
GPT-5.5 leads, 36.4 against 23.5.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.5
GPT-5.5 leads, 93.2% against 83.6%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5.5
GPT-5.5 leads, 88.1% against 85.6%.
Same board, both measured
Web design
Design Arena: websites
No call
Only GPT-5.5 has a Design Arena: websites result, 1256.
Directional only
General
Vals Index
No call
Only Inkling Small has a Vals Index result, 27.6%.
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 Small
GPT-5.5 $0.020, Inkling Small $0.0010 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Inkling Small
GPT-5.5 $1.65, Inkling Small $0.16.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.5 71.3 from 5 benchmarks, Inkling Small 27.3 from 4 benchmarks.
- Widest category
- Math, 26.3 points apart on average over 6 shared benchmarks.
- Widest single gap
- FrontierMath, tier 4: GPT-5.5 72.5% against Inkling Small 17.1%, 55.4 points apart on a 0 to 100 scale.
- Output price
- GPT-5.5 $30.00 against Inkling Small $1.20 per million output tokens, 25.0x apart.
- Context window
- GPT-5.5 takes 1.05M tokens, Inkling Small 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 Small | Ties |
|---|---|---|---|---|
| Coding | 13 | 1 | 1 tie | |
| Intelligence | 2 | 0 | ||
| Agentic work | 5 | 0 | ||
| Reasoning | 12 | 0 | ||
| Math | 5 | 1 | ||
| Knowledge | 9 | 2 | ||
| General | 28 | 0 | ||
| All shared boards | 74 | 4 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index131
| Benchmark | GPT-5.5 | Inkling Small | Leader |
|---|---|---|---|
| LiveBench coding | 85.1% | Not measured | Only GPT-5.5 measured |
| LMArena WebDev | 1513 | 1409 | GPT-5.5 |
| AA Coding Index | 74.9 | 52.9 | GPT-5.5 |
| LiveCodeBench (Vals AI) | 85.3% | 85.9% | Inkling Small |
| SWE-bench Verified (Vals AI) | 82.6% | 82.2% | GPT-5.5 |
| Terminal-Bench 4 (Vals AI) | Not measured | 0.0% | Only Inkling Small measured |
| Vibe Code Bench (Vals AI) | 69.8% | 19.1% | GPT-5.5 |
| Code migration (Vals AI) | 45.2% | 13.7% | GPT-5.5 |
| ProgramBench (Vals AI) | 0.5% | 0.5% | Tie |
| IOI (Vals AI) | Not measured | 9.3% | Only Inkling Small measured |
| Terminal-Bench 2.1 (Vals AI) | 76.4% | 55.1% | GPT-5.5 |
| SkillsBench (Vals AI) | 62.5% | 33.6% | GPT-5.5 |
| CyberBench (Vals AI) | Not measured | 64.1% | Only Inkling Small measured |
| SciCode | 56.1% | 49.7% | 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% | Not measured | Only GPT-5.5 measured |
| GSO-Bench | 40.2% | Not measured | Only GPT-5.5 measured |
| WeirdML | 84.9% | Not measured | Only GPT-5.5 measured |
| MirrorCode | 10.0% | Not measured | Only GPT-5.5 measured |
| ALE-Bench | 1943.0 | Not measured | Only GPT-5.5 measured |
| LMArena Text: coding | 1494 | 1450 | GPT-5.5 |
| LMArena Text: software and IT | 1493 | 1447 | GPT-5.5 |
| LMArena WebDev: React | 1506 | 1399 | GPT-5.5 |
| LMArena WebDev: HTML | 1543 | 1398 | GPT-5.5 |
| LMArena WebDev: from an image | 1532 | 1410 | GPT-5.5 |
| Neither model has a result on the other 13 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.5 | Inkling Small | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.4 | 25.7 | GPT-5.5 |
| Epoch Capabilities Index | 159.7 | 150.3 | GPT-5.5 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GPT-5.5 | Inkling Small | Leader |
|---|---|---|---|
| AA Agentic Index | 36.4 | 23.5 | GPT-5.5 |
| Design Arena: agents building web apps | 1117 | Not measured | Only GPT-5.5 measured |
| 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% | Not measured | Only GPT-5.5 measured |
| LiveBench browser | 48.0% | Not measured | Only GPT-5.5 measured |
| LiveBench long agentic | 44.6% | Not measured | Only GPT-5.5 measured |
| SREBench (Vals AI) | 3.8% | Not measured | Only GPT-5.5 measured |
| Finance Agent (Vals AI) | 51.8% | 41.3% | GPT-5.5 |
| Tax Agent Bench (Vals AI) | 21.8% | 15.4% | GPT-5.5 |
| Legal Research Bench (Vals AI) | 40.4% | 25.5% | GPT-5.5 |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 2.9% | Only Inkling Small measured |
| Excel Modeling Benchmark (Vals AI) | 64.5% | 31.8% | 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% | Not measured | Only GPT-5.5 measured |
| 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 index120
| Benchmark | GPT-5.5 | Inkling Small | Leader |
|---|---|---|---|
| GPQA Diamond | 93.2% | 83.6% | GPT-5.5 |
| LiveBench reasoning | 89.7% | Not measured | Only GPT-5.5 measured |
| MMMU Pro (Vals AI) | 88.3% | Not measured | Only GPT-5.5 measured |
| GPQA Diamond (Artificial Analysis run) | 93.5% | 89.5% | GPT-5.5 |
| Humanity's Last Exam (Artificial Analysis run) | 45.8% | 33.3% | GPT-5.5 |
| GPQA Diamond (Epoch AI run) | 90.7% | 88.5% | GPT-5.5 |
| ARC-AGI | 95.0% | 84.0% | GPT-5.5 |
| ARC-AGI-2 | 85.0% | 40.1% | GPT-5.5 |
| SimpleBench | 69.0% | Not measured | Only GPT-5.5 measured |
| Chess puzzles | 63.0% | Not measured | Only GPT-5.5 measured |
| Mystery game puzzles | 56.0% | 6.0% | GPT-5.5 |
| EBR-bench | 34.3% | Not measured | Only GPT-5.5 measured |
| LMArena Text: hard prompts | 1489 | 1423 | GPT-5.5 |
| LMArena Text: expert | 1507 | 1441 | GPT-5.5 |
| LMArena Text: hard prompts in English | 1483 | 1429 | GPT-5.5 |
| LMArena Vision: diagrams | 1325 | 1251 | GPT-5.5 |
| LMArena Vision: homework | 1332 | 1257 | GPT-5.5 |
| 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 Small | Leader |
|---|---|---|---|
| OTIS Mock AIME | 84.4% | 90.0% | Inkling Small |
| FrontierMath, tiers 1 to 3 | 85.3% | 46.3% | GPT-5.5 |
| FrontierMath, tier 4 | 72.5% | 17.1% | GPT-5.5 |
| ProofBench | 50.0% | 6.0% | GPT-5.5 |
| LMArena Text: math | 1487 | 1459 | GPT-5.5 |
| LMArena Text: mathematical work | 1496 | 1441 | 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 Small | Leader |
|---|---|---|---|
| MMLU Pro | 88.1% | 85.6% | 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% | 69.6% | Inkling Small |
| TaxEval (Vals AI) | 75.0% | 75.5% | Inkling Small |
| MortgageTax (Vals AI) | 68.8% | 62.3% | GPT-5.5 |
| MedCode (Vals AI) | 49.1% | 37.9% | GPT-5.5 |
| SimpleQA Verified | 63.0% | 19.1% | GPT-5.5 |
| LMArena Text: science | 1485 | 1428 | GPT-5.5 |
| LMArena Text: medicine and healthcare | 1465 | 1413 | GPT-5.5 |
| LMArena Text: legal and government | 1491 | 1415 | GPT-5.5 |
| LMArena Text: business and finance | 1478 | 1413 | 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 designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-5.5 | Inkling Small | Leader |
|---|---|---|---|
| Design Arena: websites | 1256 | Not measured | Only GPT-5.5 measured |
| Design Arena: UI components | 1257 | Not measured | Only GPT-5.5 measured |
| Design Arena: game dev | 1293 | Not measured | Only GPT-5.5 measured |
| Design Arena: data viz | 1264 | Not measured | Only GPT-5.5 measured |
| Design Arena: 3D | 1197 | Not measured | Only GPT-5.5 measured |
| Design Arena: all code categories | 1260 | Not measured | Only GPT-5.5 measured |
| Design Arena: SVG | 1234 | Not measured | Only GPT-5.5 measured |
| Design Arena: ASCII art | 1255 | Not measured | Only GPT-5.5 measured |
| LiveBench design | 70.3% | Not measured | Only GPT-5.5 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index280
| Benchmark | GPT-5.5 | Inkling Small | Leader |
|---|---|---|---|
| Vals Index | Not measured | 27.6% | Only Inkling Small measured |
| LiveBench data analysis | 81.6% | Not measured | Only GPT-5.5 measured |
| Public Benefits Bench (Vals AI) | 60.9% | 59.4% | GPT-5.5 |
| SAGE (Vals AI) | 51.5% | 32.7% | GPT-5.5 |
| MedScribe (Vals AI) | 86.9% | 84.1% | GPT-5.5 |
| Vals Multimodal Index | 68.1% | 50.0% | GPT-5.5 |
| IFBench | 75.9% | Not measured | Only GPT-5.5 measured |
| Long context reasoning (AA-LCR) | 84.3% | 75.7% | GPT-5.5 |
| DTBench | 96.0% | Not measured | Only GPT-5.5 measured |
| LMCA | 54.3% | Not measured | Only GPT-5.5 measured |
| 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 | 1413 | GPT-5.5 |
| LMArena Text: instruction following | 1478 | 1399 | GPT-5.5 |
| LMArena Text: creative writing | 1455 | 1334 | GPT-5.5 |
| LMArena Vision | 1297 | 1237 | GPT-5.5 |
| LMArena Text: English | 1470 | 1421 | GPT-5.5 |
| LMArena Text: non-English | 1467 | 1401 | GPT-5.5 |
| LMArena Text: Chinese | 1534 | 1464 | GPT-5.5 |
| LMArena Text: German | 1480 | 1408 | GPT-5.5 |
| LMArena Text: Japanese | 1499 | 1401 | GPT-5.5 |
| LMArena Text: Korean | 1460 | 1367 | GPT-5.5 |
| LMArena Text: French | 1485 | 1435 | GPT-5.5 |
| LMArena Text: Spanish | 1468 | 1422 | GPT-5.5 |
| LMArena Text: Russian | 1473 | 1394 | GPT-5.5 |
| LMArena Text: Polish | 1465 | 1428 | GPT-5.5 |
| LMArena Text: multi-turn | 1476 | 1416 | GPT-5.5 |
| LMArena Text: longer queries | 1484 | 1402 | GPT-5.5 |
| LMArena Text: writing and language | 1466 | 1357 | GPT-5.5 |
| LMArena Text: entertainment and media | 1449 | 1352 | GPT-5.5 |
| LMArena Vision: English | 1292 | 1243 | GPT-5.5 |
| LMArena Vision: Chinese | 1360 | 1292 | GPT-5.5 |
| LMArena Vision: reading text | 1306 | 1243 | GPT-5.5 |
| LMArena Vision: humor | 1293 | 1207 | GPT-5.5 |
| LMArena Vision: recognizing things | 1231 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: creative writing | 1301 | 1205 | GPT-5.5 |
| 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 Small | 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 Small costs less
Repository review
50K input + 3K output tokens
Inkling Small costs less
Agent loop
200K input + 10K output tokens
Inkling Small 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 Small |
|---|---|---|
| Maker | OpenAI | Thinking Machines |
| Weights | No public weights listed | Open weights |
| Released | April 24, 2026 | July 30, 2026 |
| Context window | 1.05M | 524K |
| Input $/Mtok | $5.00 | $0.45 |
| Output $/Mtok | $30.00 | $1.20 |
| Coding index | 71.3 | 27.3 |
| Independent measurements behind it | 5 | 4 |
| Cost per solved task | $1.65 | $0.16 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.5 better than Inkling Small for coding?
Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 27.3 for Inkling Small. Pick Inkling Small for output tokens 25.0x cheaper ($1.20 vs $30.00 per million) and a lower cost per solved task ($0.16 against $1.65).
Which is cheaper, GPT-5.5 or Inkling Small?
GPT-5.5 costs $5.00 per million input tokens and $30.00 per million output tokens; Inkling Small costs $0.45 and $1.20. Per solved SWE-bench Verified task, GPT-5.5 costs $1.65 and Inkling Small $0.16.
Which has the bigger context window, GPT-5.5 or Inkling Small?
GPT-5.5, with 1.05M tokens against 524K.
How many benchmarks is the GPT-5.5 vs Inkling Small comparison based on?
79 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 Small's on 4. Where only one model has a result, the page says so instead of naming a winner.