GPT-5.1 vs Inkling Small
Updated October 21, 2026. 64 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GPT-5.1 for coding: it scores 53.3 on the Vibe Coding Index against 29.9 for Inkling Small.
Pick Inkling Small when output tokens cost 8.3x less, or when a solved task costs $0.16 against $1.02.
- Shared results
- 64
- GPT-5.1 only
- 36
- Inkling Small only
- 20
- 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
GPT-5.1
GPT-5.1 scores 53.3 against 29.9.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
Inkling Small
Inkling Small leads, 25.7 against 24.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Inkling Small has a AA Agentic Index result, 23.5.
Directional only
Reasoning
GPQA Diamond
GPT-5.1
GPT-5.1 leads, 86.6% against 83.6%.
Same board, both measured
Math
AIME
No call
Only GPT-5.1 has a AIME result, 93.3%.
Directional only
Knowledge
MMLU Pro
GPT-5.1
GPT-5.1 leads, 86.4% against 85.6%.
Same board, both measured
Web design
Design Arena: websites
No call
Only GPT-5.1 has a Design Arena: websites result, 1187.
Directional only
General
Vals Index
No call
Only Inkling Small has a Vals Index result, 27.6%.
Directional only
Long documents
Listed context window
Inkling Small
Inkling Small takes 524K tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Inkling Small
GPT-5.1 $0.0063, Inkling Small $0.0010 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Inkling Small
GPT-5.1 $1.02, Inkling Small $0.16.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.1 53.3 from 2 benchmarks, Inkling Small 29.9 from 1 benchmark.
- Widest category
- Knowledge, 7.0 points apart on average over 11 shared benchmarks.
- Widest single gap
- SimpleQA Verified: GPT-5.1 48.0% against Inkling Small 19.1%, 28.9 points apart on a 0 to 100 scale.
- Output price
- GPT-5.1 $10.00 against Inkling Small $1.20 per million output tokens, 8.3x apart.
- Context window
- GPT-5.1 takes 400K 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-5.1 | Bars | Inkling Small | Ties |
|---|---|---|---|---|
| Coding | 6 | 4 | ||
| Intelligence | 0 | 2 | ||
| Reasoning | 7 | 5 | ||
| Math | 1 | 2 | ||
| Knowledge | 8 | 3 | ||
| General | 25 | 1 | ||
| All shared boards | 47 | 17 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index64
| Benchmark | GPT-5.1 | Inkling Small | Leader |
|---|---|---|---|
| SWE-bench Verified | 66.0% | Not measured | Only GPT-5.1 measured |
| LMArena WebDev | 1396 | 1409 | Inkling Small |
| AA Coding Index | 49.4 | 52.9 | Inkling Small |
| LiveCodeBench (Vals AI) | 86.5% | 85.9% | GPT-5.1 |
| SWE-bench Verified (Vals AI) | 69.8% | 82.2% | Inkling Small |
| Terminal-Bench 4 (Vals AI) | Not measured | 0.0% | Only Inkling Small measured |
| Vibe Code Bench (Vals AI) | 24.6% | 19.1% | GPT-5.1 |
| Code migration (Vals AI) | Not measured | 13.7% | Only Inkling Small measured |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only Inkling Small measured |
| IOI (Vals AI) | Not measured | 9.3% | Only Inkling Small measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 55.1% | Only Inkling Small measured |
| SkillsBench (Vals AI) | Not measured | 33.6% | Only Inkling Small measured |
| CyberBench (Vals AI) | Not measured | 64.1% | Only Inkling Small measured |
| LiveCodeBench (Artificial Analysis run) | 86.8% | Not measured | Only GPT-5.1 measured |
| SciCode | Not measured | 49.7% | Only Inkling Small measured |
| Terminal-Bench Hard (Artificial Analysis run) | 45.5% | Not measured | Only GPT-5.1 measured |
| Terminal-Bench | 47.6% | Not measured | Only GPT-5.1 measured |
| GSO-Bench | 13.7% | Not measured | Only GPT-5.1 measured |
| WeirdML | 60.8% | Not measured | Only GPT-5.1 measured |
| LMArena Text: coding | 1453 | 1450 | GPT-5.1 |
| LMArena Text: software and IT | 1454 | 1447 | GPT-5.1 |
| LMArena WebDev: React | 1307 | 1399 | Inkling Small |
| LMArena WebDev: HTML | 1405 | 1398 | GPT-5.1 |
| LMArena WebDev: from an image | 1421 | 1410 | GPT-5.1 |
| Neither model has a result on the other 14 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-5.1 | Inkling Small | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.7 | 25.7 | Inkling Small |
| Epoch Capabilities Index | 149.8 | 150.3 | Inkling Small |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-5.1 | Inkling Small | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 23.5 | Only Inkling Small measured |
| Finance Agent (Vals AI) | Not measured | 41.3% | Only Inkling Small measured |
| Tax Agent Bench (Vals AI) | Not measured | 15.4% | Only Inkling Small measured |
| Legal Research Bench (Vals AI) | Not measured | 25.5% | Only Inkling Small measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 2.9% | Only Inkling Small measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 31.8% | Only Inkling Small measured |
| τ²-Bench Telecom | 81.9% | Not measured | Only GPT-5.1 measured |
| DeepResearch Bench | 42.8% | Not measured | Only GPT-5.1 measured |
| Vending-Bench 2 | $1,473 | Not measured | Only GPT-5.1 measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index75
| Benchmark | GPT-5.1 | Inkling Small | Leader |
|---|---|---|---|
| GPQA Diamond | 86.6% | 83.6% | GPT-5.1 |
| MMMU Pro (Vals AI) | 83.2% | Not measured | Only GPT-5.1 measured |
| GPQA Diamond (Artificial Analysis run) | 87.3% | 89.5% | Inkling Small |
| Humanity's Last Exam (Artificial Analysis run) | 28.5% | 33.3% | Inkling Small |
| GPQA Diamond (Epoch AI run) | 87.6% | 88.5% | Inkling Small |
| ARC-AGI | 72.8% | 84.0% | Inkling Small |
| ARC-AGI-2 | 17.6% | 40.1% | Inkling Small |
| SimpleBench | 53.2% | Not measured | Only GPT-5.1 measured |
| Chess puzzles | 42.0% | Not measured | Only GPT-5.1 measured |
| Mystery game puzzles | 19.0% | 6.0% | GPT-5.1 |
| VPCT | 58.7% | Not measured | Only GPT-5.1 measured |
| LMArena Text: hard prompts | 1457 | 1423 | GPT-5.1 |
| LMArena Text: expert | 1470 | 1441 | GPT-5.1 |
| LMArena Text: hard prompts in English | 1462 | 1429 | GPT-5.1 |
| LMArena Vision: diagrams | 1264 | 1251 | GPT-5.1 |
| LMArena Vision: homework | 1272 | 1257 | GPT-5.1 |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | GPT-5.1 | Inkling Small | Leader |
|---|---|---|---|
| AIME | 93.3% | Not measured | Only GPT-5.1 measured |
| MGSM (Vals AI) | 93.0% | Not measured | Only GPT-5.1 measured |
| AA Math Index | 94.0 | Not measured | Only GPT-5.1 measured |
| AIME 2025 (Artificial Analysis run) | 94.0% | Not measured | Only GPT-5.1 measured |
| OTIS Mock AIME | 88.6% | 90.0% | Inkling Small |
| FrontierMath, tiers 1 to 3 | Not measured | 46.3% | Only Inkling Small measured |
| FrontierMath, tier 4 | Not measured | 17.1% | Only Inkling Small measured |
| ProofBench | Not measured | 6.0% | Only Inkling Small measured |
| LMArena Text: math | 1446 | 1459 | Inkling Small |
| LMArena Text: mathematical work | 1449 | 1441 | GPT-5.1 |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index83
| Benchmark | GPT-5.1 | Inkling Small | Leader |
|---|---|---|---|
| MMLU Pro | 86.4% | 85.6% | GPT-5.1 |
| LegalBench (Vals AI) | 85.7% | 83.0% | GPT-5.1 |
| CaseLaw (Vals AI) | 73.4% | Not measured | Only GPT-5.1 measured |
| CorpFin (Vals AI) | 63.8% | 69.6% | Inkling Small |
| TaxEval (Vals AI) | 74.9% | 75.5% | Inkling Small |
| MortgageTax (Vals AI) | 61.4% | 62.3% | Inkling Small |
| MedQA (Vals AI) | 96.4% | Not measured | Only GPT-5.1 measured |
| MedCode (Vals AI) | 52.7% | 37.9% | GPT-5.1 |
| MMLU Pro (Artificial Analysis run) | 87.0% | Not measured | Only GPT-5.1 measured |
| SimpleQA Verified | 48.0% | 19.1% | GPT-5.1 |
| LMArena Text: science | 1459 | 1428 | GPT-5.1 |
| LMArena Text: medicine and healthcare | 1456 | 1413 | GPT-5.1 |
| LMArena Text: legal and government | 1459 | 1415 | GPT-5.1 |
| LMArena Text: business and finance | 1431 | 1413 | GPT-5.1 |
| Neither model has a result on the other 3 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5.1 | Inkling Small | Leader |
|---|---|---|---|
| Design Arena: websites | 1187 | Not measured | Only GPT-5.1 measured |
| Design Arena: UI components | 1166 | Not measured | Only GPT-5.1 measured |
| Design Arena: game dev | 1179 | Not measured | Only GPT-5.1 measured |
| Design Arena: data viz | 1204 | Not measured | Only GPT-5.1 measured |
| Design Arena: 3D | 1061 | Not measured | Only GPT-5.1 measured |
| Design Arena: all code categories | 1171 | Not measured | Only GPT-5.1 measured |
| Design Arena: SVG | 1149 | Not measured | Only GPT-5.1 measured |
| Design Arena: ASCII art | 1118 | Not measured | Only GPT-5.1 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index251
| Benchmark | GPT-5.1 | Inkling Small | Leader |
|---|---|---|---|
| Vals Index | Not measured | 27.6% | Only Inkling Small measured |
| Public Benefits Bench (Vals AI) | Not measured | 59.4% | Only Inkling Small measured |
| SAGE (Vals AI) | 43.2% | 32.7% | GPT-5.1 |
| MedScribe (Vals AI) | 88.1% | 84.1% | GPT-5.1 |
| Vals Multimodal Index | Not measured | 50.0% | Only Inkling Small measured |
| IFBench | 72.9% | Not measured | Only GPT-5.1 measured |
| Long context reasoning (AA-LCR) | 80.0% | 75.7% | GPT-5.1 |
| DTBench | 90.1% | Not measured | Only GPT-5.1 measured |
| LMCA | 43.9% | Not measured | Only GPT-5.1 measured |
| CL-bench | 23.7% | Not measured | Only GPT-5.1 measured |
| CL-bench Life | 17.3% | Not measured | Only GPT-5.1 measured |
| LMArena Text | 1443 | 1413 | GPT-5.1 |
| LMArena Text: instruction following | 1443 | 1399 | GPT-5.1 |
| LMArena Text: creative writing | 1427 | 1334 | GPT-5.1 |
| LMArena Vision | 1250 | 1237 | GPT-5.1 |
| LMArena Text: English | 1451 | 1421 | GPT-5.1 |
| LMArena Text: non-English | 1431 | 1401 | GPT-5.1 |
| LMArena Text: Chinese | 1495 | 1464 | GPT-5.1 |
| LMArena Text: German | 1438 | 1408 | GPT-5.1 |
| LMArena Text: Japanese | 1453 | 1401 | GPT-5.1 |
| LMArena Text: Korean | 1401 | 1367 | GPT-5.1 |
| LMArena Text: French | 1450 | 1435 | GPT-5.1 |
| LMArena Text: Spanish | 1433 | 1422 | GPT-5.1 |
| LMArena Text: Russian | 1435 | 1394 | GPT-5.1 |
| LMArena Text: Polish | 1440 | 1428 | GPT-5.1 |
| LMArena Text: multi-turn | 1450 | 1416 | GPT-5.1 |
| LMArena Text: longer queries | 1448 | 1402 | GPT-5.1 |
| LMArena Text: writing and language | 1428 | 1357 | GPT-5.1 |
| LMArena Text: entertainment and media | 1415 | 1352 | GPT-5.1 |
| LMArena Vision: English | 1252 | 1243 | GPT-5.1 |
| LMArena Vision: Chinese | 1270 | 1292 | Inkling Small |
| LMArena Vision: reading text | 1255 | 1243 | GPT-5.1 |
| LMArena Vision: humor | 1263 | 1207 | GPT-5.1 |
| LMArena Vision: captioning | 1252 | Not measured | Only GPT-5.1 measured |
| LMArena Vision: recognizing things | 1232 | Not measured | Only GPT-5.1 measured |
| LMArena Vision: creative writing | 1266 | 1205 | GPT-5.1 |
| LMArena Document | 1403 | Not measured | Only GPT-5.1 measured |
| Neither model has a result on the other 9 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.1 | 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-5.1 | Thinking Machines Inkling Small |
|---|---|---|
| Maker | OpenAI | Thinking Machines |
| Weights | No public weights listed | Open weights |
| Released | November 13, 2025 | July 30, 2026 |
| Context window | 400K | 524K |
| Input $/Mtok | $1.25 | $0.45 |
| Output $/Mtok | $10.00 | $1.20 |
| Coding index | 53.3 | 29.9 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $1.02 | $0.16 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1 better than Inkling Small for coding?
Pick GPT-5.1 for coding: it scores 53.3 on the Vibe Coding Index against 29.9 for Inkling Small. Pick Inkling Small when output tokens cost 8.3x less, or when a solved task costs $0.16 against $1.02.
Which is cheaper, GPT-5.1 or Inkling Small?
GPT-5.1 costs $1.25 per million input tokens and $10.00 per million output tokens; Inkling Small costs $0.45 and $1.20. Per solved SWE-bench Verified task, GPT-5.1 costs $1.02 and Inkling Small $0.16.
Which has the bigger context window, GPT-5.1 or Inkling Small?
Inkling Small, with 524K tokens against 400K.
How many benchmarks is the GPT-5.1 vs Inkling Small comparison based on?
64 benchmarks have a result for both models as of October 21, 2026. GPT-5.1's coding index rests on 2 independent benchmarks and Inkling Small's on 1. Where only one model has a result, the page says so instead of naming a winner.