GPT-3.5 Turbo vs Inkling
Inkling leads GPT-3.5 Turbo on the Artificial Analysis Intelligence Index, 25.0 to 5.5, and GPT-3.5 Turbo costs 2.7x less per output token ($1.50 vs $4.05 per million). Updated October 22, 2026; 7 benchmarks have a result for both.
GPT-3.5 Turbo or Inkling: which to pick
Only Inkling has a coding score, 31.5 on the Vibe Coding Index; GPT-3.5 Turbo has none, so the two cannot be ranked on coding.
Pick GPT-3.5 Turbo for output tokens 2.7x cheaper ($1.50 vs $4.05 per million).
- Shared results
- 7
- GPT-3.5 Turbo only
- 6
- Inkling only
- 95
- Like-for-like categories
- 5 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 Inkling has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Inkling
Inkling leads, 25.0 against 5.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Inkling has a AA Agentic Index result, 22.5.
Directional only
Reasoning
GPQA Diamond
Inkling
Inkling leads, 87.1% against 30.6%.
Same board, both measured
Knowledge
MMLU Pro
No call
Only Inkling has a MMLU Pro result, 86.3%.
Directional only
Web design
Design Arena: websites
No call
Only Inkling has a Design Arena: websites result, 1224.
Directional only
General
Vals Index
No call
Only Inkling has a Vals Index result, 29.0%.
Directional only
Long documents
Listed context window
Inkling
Inkling takes 524K tokens against 16K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-3.5 Turbo
GPT-3.5 Turbo $0.0013, Inkling $0.0030 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Inkling has the number, $0.76.
Directional only
At a glance
- Coding index
- GPT-3.5 Turbo not benchmarked, Inkling 31.5 from 6 benchmarks.
- Widest category
- Reasoning, 57.0 points apart on average over 2 shared benchmarks.
- Widest single gap
- GPQA Diamond (Artificial Analysis run): GPT-3.5 Turbo 29.7% against Inkling 87.2%, 57.5 points apart on a 0 to 100 scale.
- Output price
- GPT-3.5 Turbo $1.50 against Inkling $4.05 per million output tokens, 2.7x apart.
- Context window
- GPT-3.5 Turbo takes 16K 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-3.5 Turbo | Bars | Inkling | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Knowledge | 0 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 7 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | GPT-3.5 Turbo | Inkling | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 64.0% | Only Inkling measured |
| LMArena WebDev | Not measured | 1414 | Only Inkling measured |
| AA Coding Index | 10.7 | 52.1 | Inkling |
| LiveCodeBench (Vals AI) | Not measured | 85.5% | Only Inkling measured |
| SWE-bench Verified (Vals AI) | Not measured | 77.6% | Only Inkling measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 0.5% | Only Inkling measured |
| Vibe Code Bench (Vals AI) | Not measured | 19.2% | Only Inkling measured |
| Code migration (Vals AI) | Not measured | 11.8% | Only Inkling measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Inkling measured |
| IOI (Vals AI) | Not measured | 14.9% | Only Inkling measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 47.6% | Only Inkling measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 7.3% | Only Inkling measured |
| SkillsBench (Vals AI) | Not measured | 26.1% | Only Inkling measured |
| CyberBench (Vals AI) | Not measured | 66.8% | Only Inkling measured |
| SciCode | Not measured | 47.0% | Only Inkling measured |
| FrontierCode | Not measured | 14.0% | Only Inkling measured |
| FrontierSWE | Not measured | 4.1% | Only Inkling measured |
| WeirdML | Not measured | 32.3% | Only Inkling measured |
| ALE-Bench | Not measured | 946.0 | Only Inkling measured |
| LMArena Text: coding | Not measured | 1466 | Only Inkling measured |
| LMArena Text: software and IT | Not measured | 1465 | Only Inkling measured |
| LMArena WebDev: React | Not measured | 1404 | Only Inkling measured |
| LMArena WebDev: HTML | Not measured | 1399 | Only Inkling measured |
| SciCode | 0.0% | Not measured | Only GPT-3.5 Turbo measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-3.5 Turbo | Inkling | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.5 | 25.0 | Inkling |
| Epoch Capabilities Index | Not measured | 148.4 | Only Inkling measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | GPT-3.5 Turbo | Inkling | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 22.5 | Only Inkling measured |
| Design Arena: agents building web apps | Not measured | 1196 | Only Inkling measured |
| LiveBench research | Not measured | 59.9% | Only Inkling measured |
| LiveBench browser | Not measured | 16.0% | Only Inkling measured |
| LiveBench long agentic | Not measured | 14.1% | Only Inkling measured |
| SREBench (Vals AI) | Not measured | 0.0% | Only Inkling measured |
| Finance Agent (Vals AI) | Not measured | 46.6% | Only Inkling measured |
| Tax Agent Bench (Vals AI) | Not measured | 15.3% | Only Inkling measured |
| Legal Research Bench (Vals AI) | Not measured | 28.4% | Only Inkling measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 3.8% | Only Inkling measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 38.4% | Only Inkling measured |
| APEX-Agents | Not measured | 33.8% | Only Inkling measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-3.5 Turbo | Inkling | Leader |
|---|---|---|---|
| GPQA Diamond | 30.6% | 87.1% | Inkling |
| LiveBench reasoning | Not measured | 78.3% | Only Inkling measured |
| MMMU Pro (Vals AI) | Not measured | 78.5% | Only Inkling measured |
| GPQA Diamond (Artificial Analysis run) | 29.7% | 87.2% | Inkling |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 31.9% | Only Inkling measured |
| GPQA Diamond (Epoch AI run) | Not measured | 88.3% | Only Inkling measured |
| ARC-AGI | Not measured | 79.5% | Only Inkling measured |
| ARC-AGI-2 | Not measured | 36.5% | Only Inkling measured |
| SimpleBench | Not measured | 50.0% | Only Inkling measured |
| Chess puzzles | Not measured | 21.0% | Only Inkling measured |
| BIG-Bench Hard | 61.6% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: hard prompts | Not measured | 1451 | Only Inkling measured |
| LMArena Text: expert | Not measured | 1466 | Only Inkling measured |
| LMArena Text: hard prompts in English | Not measured | 1448 | Only Inkling measured |
| Neither model has a result on the other 8 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-3.5 Turbo | Inkling | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 88.9% | Only Inkling measured |
| FrontierMath, tiers 1 to 3 | Not measured | 33.3% | Only Inkling measured |
| FrontierMath, tier 4 | Not measured | 4.9% | Only Inkling measured |
| ProofBench | Not measured | 0.0% | Only Inkling measured |
| GSM8K | 57.8% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: math | Not measured | 1479 | Only Inkling measured |
| LMArena Text: mathematical work | Not measured | 1460 | Only Inkling measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-3.5 Turbo | Inkling | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 86.3% | Only Inkling measured |
| LegalBench (Vals AI) | 64.4% | 83.0% | Inkling |
| CorpFin (Vals AI) | Not measured | 68.6% | Only Inkling measured |
| TaxEval (Vals AI) | Not measured | 75.3% | Only Inkling measured |
| MortgageTax (Vals AI) | Not measured | 64.0% | Only Inkling measured |
| MedQA (Vals AI) | 58.5% | Not measured | Only GPT-3.5 Turbo measured |
| MedCode (Vals AI) | Not measured | 41.2% | Only Inkling measured |
| MMLU Pro (Artificial Analysis run) | 46.2% | Not measured | Only GPT-3.5 Turbo measured |
| SimpleQA Verified | Not measured | 40.3% | Only Inkling measured |
| MMLU | 68.5% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: science | Not measured | 1455 | Only Inkling measured |
| LMArena Text: medicine and healthcare | Not measured | 1447 | Only Inkling measured |
| LMArena Text: legal and government | Not measured | 1448 | Only Inkling measured |
| LMArena Text: business and finance | Not measured | 1438 | Only Inkling measured |
| Neither model has a result on the other 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-3.5 Turbo | Inkling | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1224 | Only Inkling measured |
| Design Arena: UI components | Not measured | 1198 | Only Inkling measured |
| Design Arena: game dev | Not measured | 1165 | Only Inkling measured |
| Design Arena: data viz | Not measured | 1156 | Only Inkling measured |
| Design Arena: 3D | Not measured | 1160 | Only Inkling measured |
| Design Arena: all code categories | Not measured | 1205 | Only Inkling measured |
| Design Arena: SVG | Not measured | 1108 | Only Inkling measured |
| Design Arena: ASCII art | Not measured | 1089 | Only Inkling measured |
| LiveBench design | Not measured | 58.3% | Only Inkling measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-3.5 Turbo | Inkling | Leader |
|---|---|---|---|
| Vals Index | Not measured | 29.0% | Only Inkling measured |
| LiveBench data analysis | Not measured | 72.8% | Only Inkling measured |
| Public Benefits Bench (Vals AI) | Not measured | 58.5% | Only Inkling measured |
| SAGE (Vals AI) | Not measured | 36.5% | Only Inkling measured |
| MedScribe (Vals AI) | Not measured | 85.4% | Only Inkling measured |
| Vals Multimodal Index | Not measured | 49.4% | Only Inkling measured |
| Long context reasoning (AA-LCR) | Not measured | 77.3% | Only Inkling measured |
| DTBench | 48.5% | 87.5% | Inkling |
| LMCA | 9.7% | 37.6% | Inkling |
| LMArena Text | Not measured | 1442 | Only Inkling measured |
| LMArena Text: instruction following | Not measured | 1425 | Only Inkling measured |
| LMArena Text: creative writing | Not measured | 1390 | Only Inkling measured |
| LMArena Text: English | Not measured | 1442 | Only Inkling measured |
| LMArena Text: non-English | Not measured | 1434 | Only Inkling measured |
| LMArena Text: Chinese | Not measured | 1493 | Only Inkling measured |
| LMArena Text: German | Not measured | 1445 | Only Inkling measured |
| LMArena Text: Japanese | Not measured | 1429 | Only Inkling measured |
| LMArena Text: Korean | Not measured | 1403 | Only Inkling measured |
| LMArena Text: French | Not measured | 1455 | Only Inkling measured |
| LMArena Text: Spanish | Not measured | 1449 | Only Inkling measured |
| LMArena Text: Russian | Not measured | 1430 | Only Inkling measured |
| LMArena Text: Polish | Not measured | 1450 | Only Inkling measured |
| LMArena Text: multi-turn | Not measured | 1437 | Only Inkling measured |
| LMArena Text: longer queries | Not measured | 1435 | Only Inkling measured |
| LMArena Text: writing and language | Not measured | 1404 | Only Inkling measured |
| LMArena Text: entertainment and media | Not measured | 1394 | Only Inkling measured |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-3.5 Turbo | 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
GPT-3.5 Turbo costs less
Repository review
50K input + 3K output tokens
GPT-3.5 Turbo costs less
Agent loop
200K input + 10K output tokens
GPT-3.5 Turbo 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-3.5 Turbo | Thinking Machines Inkling |
|---|---|---|
| Maker | OpenAI | Thinking Machines |
| Weights | No public weights listed | Open weights |
| Released | May 28, 2023 | July 17, 2026 |
| Context window | 16K | 524K |
| Input $/Mtok | $0.50 | $0.975 |
| Output $/Mtok | $1.50 | $4.05 |
| Coding index | Not benchmarked | 31.5 |
| Independent measurements behind it | 0 | 6 |
| Cost per solved task | Not computable | $0.76 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-3.5 Turbo better than Inkling for coding?
Only Inkling has a coding score, 31.5 on the Vibe Coding Index; GPT-3.5 Turbo has none, so the two cannot be ranked on coding. Pick GPT-3.5 Turbo for output tokens 2.7x cheaper ($1.50 vs $4.05 per million).
Which is cheaper, GPT-3.5 Turbo or Inkling?
GPT-3.5 Turbo costs $0.50 per million input tokens and $1.50 per million output tokens; Inkling costs $0.975 and $4.05. Cost per solved task is known for Inkling only.
Which has the bigger context window, GPT-3.5 Turbo or Inkling?
Inkling, with 524K tokens against 16K.
How many benchmarks is the GPT-3.5 Turbo vs Inkling comparison based on?
7 benchmarks have a result for both models as of October 22, 2026. GPT-3.5 Turbo's coding index rests on 0 independent benchmarks and Inkling's on 6. Where only one model has a result, the page says so instead of naming a winner.