GPT-5.3-Codex vs Inkling
GPT-5.3-Codex leads Inkling on coding, 60.0 to 31.5 on the Vibe Coding Index, and Inkling costs 3.5x less per output token ($4.05 vs $14.00 per million). Updated October 22, 2026; 23 benchmarks have a result for both.
GPT-5.3-Codex or Inkling: which to pick
Pick GPT-5.3-Codex for coding: it scores 60.0 on the Vibe Coding Index against 31.5 for Inkling, though on 3 benchmarks against 6.
Pick Inkling for output tokens 3.5x cheaper ($4.05 vs $14.00 per million) and a larger context window (524K against 400K tokens).
- Shared results
- 23
- GPT-5.3-Codex only
- 11
- Inkling only
- 83
- Like-for-like categories
- 6 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-5.3-Codex
GPT-5.3-Codex scores 60.0 against 31.5.
3 and 6 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.3-Codex
GPT-5.3-Codex leads, 32.5 against 25.0.
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
No call
Only Inkling has a GPQA Diamond result, 87.1%.
Directional only
Knowledge
MMLU Pro
No call
Only Inkling has a MMLU Pro result, 86.3%.
Directional only
Web design
Design Arena: websites
Inkling
Inkling leads, 1224 against 1162.
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
Inkling
Inkling takes 524K tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Inkling
GPT-5.3-Codex $0.0088, Inkling $0.0030 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.3-Codex
GPT-5.3-Codex $0.59, Inkling $0.76.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.3-Codex 60.0 from 3 benchmarks, Inkling 31.5 from 6 benchmarks.
- Widest category
- Agentic work, 20.5 points apart on average over 1 shared benchmark.
- Widest single gap
- WeirdML: GPT-5.3-Codex 79.3% against Inkling 32.3%, 47.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5.3-Codex $14.00 against Inkling $4.05 per million output tokens, 3.5x apart.
- Context window
- GPT-5.3-Codex takes 400K 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-5.3-Codex | Bars | Inkling | Ties |
|---|---|---|---|---|
| Coding | 7 | 2 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 2 | 0 | ||
| Web design | 3 | 5 | ||
| General | 1 | 0 | ||
| All shared boards | 15 | 8 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index72
| Benchmark | GPT-5.3-Codex | Inkling | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 64.0% | Only Inkling measured |
| LMArena WebDev | 1407 | 1414 | Inkling |
| AA Coding Index | Not measured | 52.1 | Only Inkling measured |
| LiveCodeBench (Vals AI) | 87.3% | 85.5% | GPT-5.3-Codex |
| SWE-bench Verified (Vals AI) | 78.0% | 77.6% | GPT-5.3-Codex |
| Terminal-Bench 4 (Vals AI) | Not measured | 0.5% | Only Inkling measured |
| Vibe Code Bench (Vals AI) | 61.8% | 19.2% | GPT-5.3-Codex |
| Code migration (Vals AI) | Not measured | 11.8% | Only Inkling measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Inkling measured |
| IOI (Vals AI) | 53.8% | 14.9% | GPT-5.3-Codex |
| 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 |
| Terminal-Bench Hard (Artificial Analysis run) | 53.0% | Not measured | Only GPT-5.3-Codex measured |
| Terminal-Bench | 78.4% | Not measured | Only GPT-5.3-Codex measured |
| FrontierCode | Not measured | 14.0% | Only Inkling measured |
| FrontierSWE | Not measured | 4.1% | Only Inkling measured |
| WeirdML | 79.3% | 32.3% | GPT-5.3-Codex |
| ALE-Bench | 1655.2 | 946.0 | GPT-5.3-Codex |
| LMArena Text: coding | Not measured | 1466 | Only Inkling measured |
| LMArena Text: software and IT | Not measured | 1465 | Only Inkling measured |
| LMArena WebDev: React | 1395 | 1404 | Inkling |
| LMArena WebDev: HTML | 1422 | 1399 | GPT-5.3-Codex |
| LMArena WebDev: from an image | 1443 | Not measured | Only GPT-5.3-Codex measured |
| SWE-Bench Pro V2 | Not measured | 89.9% | Only Inkling measured |
| Neither model has a result on the other 16 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.3-Codex | Inkling | Leader |
|---|---|---|---|
| AA Intelligence Index | 32.5 | 25.0 | GPT-5.3-Codex |
| Epoch Capabilities Index | 157.1 | 148.4 | GPT-5.3-Codex |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5.3-Codex | Inkling | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 22.5 | Only Inkling measured |
| Design Arena: agents building web apps | 1032 | 1196 | Inkling |
| Design Arena: agents building full-stack apps | 983 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: agents building mobile apps | 1053 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: agents building Android apps | 1084 | Not measured | Only GPT-5.3-Codex measured |
| Design Arena: agents building Godot games | 1124 | Not measured | Only GPT-5.3-Codex 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 |
| τ²-Bench Telecom | 86.0% | Not measured | Only GPT-5.3-Codex measured |
| APEX-Agents | Not measured | 33.8% | Only Inkling measured |
| METR time horizons | 74.5% | Not measured | Only GPT-5.3-Codex measured |
| Vending-Bench 2 | $5,940 | Not measured | Only GPT-5.3-Codex measured |
| MCP Atlas | Not measured | 76.0% | Only Inkling measured |
| Neither model has a result on the other 22 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.3-Codex | Inkling | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 87.1% | Only Inkling measured |
| 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) | 91.5% | 87.2% | GPT-5.3-Codex |
| Humanity's Last Exam (Artificial Analysis run) | 42.5% | 31.9% | GPT-5.3-Codex |
| 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 |
| 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 |
| Humanity's Last Exam (Scale run) | Not measured | 11.2% | Only Inkling measured |
| Neither model has a result on the other 9 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-5.3-Codex | 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 |
| 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 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | GPT-5.3-Codex | Inkling | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 86.3% | Only Inkling measured |
| LegalBench (Vals AI) | Not measured | 83.0% | Only Inkling measured |
| 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 |
| MedCode (Vals AI) | Not measured | 41.2% | Only Inkling measured |
| SimpleQA Verified | Not measured | 40.3% | Only Inkling 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 9 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index35
| Benchmark | GPT-5.3-Codex | Inkling | Leader |
|---|---|---|---|
| Design Arena: websites | 1162 | 1224 | Inkling |
| Design Arena: UI components | 1135 | 1199 | Inkling |
| Design Arena: game dev | 1161 | 1165 | Inkling |
| Design Arena: data viz | 1164 | 1157 | GPT-5.3-Codex |
| Design Arena: 3D | 1007 | 1160 | Inkling |
| Design Arena: all code categories | 1144 | 1205 | Inkling |
| Design Arena: SVG | 1128 | 1108 | GPT-5.3-Codex |
| Design Arena: ASCII art | 1151 | 1089 | GPT-5.3-Codex |
| LiveBench design | Not measured | 58.3% | Only Inkling measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.3-Codex | 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 |
| IFBench | 75.4% | Not measured | Only GPT-5.3-Codex measured |
| Long context reasoning (AA-LCR) | 83.3% | 77.3% | GPT-5.3-Codex |
| DTBench | Not measured | 87.5% | Only Inkling measured |
| LMCA | Not measured | 37.6% | Only Inkling measured |
| 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 |
| EQ-Bench 4 | Not measured | 1226 | 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-5.3-Codex | 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-5.3-Codex | Thinking Machines Inkling |
|---|---|---|
| Maker | OpenAI | Thinking Machines |
| Weights | No public weights listed | Open weights |
| Released | February 24, 2026 | July 17, 2026 |
| Context window | 400K | 524K |
| Input $/Mtok | $1.75 | $1.00 |
| Output $/Mtok | $14.00 | $4.05 |
| Coding index | 60.0 | 31.5 |
| Independent measurements behind it | 3 | 6 |
| Cost per solved task | $0.59 | $0.76 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.3-Codex better than Inkling for coding?
Pick GPT-5.3-Codex for coding: it scores 60.0 on the Vibe Coding Index against 31.5 for Inkling, though on 3 benchmarks against 6. Pick Inkling for output tokens 3.5x cheaper ($4.05 vs $14.00 per million) and a larger context window (524K against 400K tokens).
Which is cheaper, GPT-5.3-Codex or Inkling?
GPT-5.3-Codex costs $1.75 per million input tokens and $14.00 per million output tokens; Inkling costs $1.00 and $4.05. Per solved SWE-bench Verified task, GPT-5.3-Codex costs $0.59 and Inkling $0.76.
Which has the bigger context window, GPT-5.3-Codex or Inkling?
Inkling, with 524K tokens against 400K.
How many benchmarks is the GPT-5.3-Codex vs Inkling comparison based on?
23 benchmarks have a result for both models as of October 22, 2026. GPT-5.3-Codex's coding index rests on 3 independent benchmarks and Inkling's on 6. Where only one model has a result, the page says so instead of naming a winner.