GPT-5.5 vs GPT-6.1 Terra
GPT-6.1 Terra leads GPT-5.5 on coding, 77.4 to 67.9 on the Vibe Coding Index, and GPT-6.1 Terra costs 6.0x less per output token ($5.00 vs $30.00 per million). Updated October 29, 2026; 23 benchmarks have a result for both.
GPT-5.5 or GPT-6.1 Terra: which to pick
Pick GPT-6.1 Terra for coding: it scores 77.4 on the Vibe Coding Index against 67.9 for GPT-5.5.
Pick GPT-5.5 for work measured by SciCode or Tax Agent Bench (Vals AI), where it leads.
- Shared results
- 23
- GPT-5.5 only
- 108
- GPT-6.1 Terra only
- 13
- 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-6.1 Terra
GPT-6.1 Terra scores 77.4 against 67.9.
4 benchmarks behind each score
Intelligence
AA Intelligence Index
No call
Only GPT-6.1 Terra has a AA Intelligence Index result, 51.0.
Directional only
Agentic work
AA Agentic Index
No call
Only GPT-5.5 has a AA Agentic Index result, 36.4.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.5 has a GPQA Diamond result, 93.2%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.5 has a MMLU Pro result, 88.1%.
Directional only
Web design
Design Arena: websites
GPT-6.1 Terra
GPT-6.1 Terra leads, 1283 against 1256.
Same board, both measured
General
Vals Index
No call
Only GPT-6.1 Terra has a Vals Index result, 60.5%.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-6.1 Terra
GPT-5.5 $0.020, GPT-6.1 Terra $0.0035 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.5 has the number, $1.65.
Directional only
At a glance
- Coding index
- GPT-5.5 67.9 from 4 benchmarks, GPT-6.1 Terra 77.4 from 4 benchmarks.
- Widest category
- General, 18.3 points apart on average over 2 shared benchmarks.
- Widest single gap
- EBR-bench: GPT-5.5 34.3% against GPT-6.1 Terra 78.1%, 43.8 points apart on a 0 to 100 scale.
- Output price
- GPT-5.5 $30.00 against GPT-6.1 Terra $5.00 per million output tokens, 6.0x apart.
- Context window
- Both take 1.05M tokens.
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 | GPT-6.1 Terra | Ties |
|---|---|---|---|---|
| Coding | 1 | 5 | ||
| Agentic work | 2 | 1 | ||
| Reasoning | 0 | 4 | ||
| Math | 0 | 3 | ||
| Knowledge | 1 | 0 | ||
| Web design | 0 | 4 | ||
| General | 1 | 1 | ||
| All shared boards | 5 | 18 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index15
| Benchmark | GPT-5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 94.3% | Only GPT-6.1 Terra measured |
| LMArena WebDev | 1512 | 1673 | GPT-6.1 Terra |
| AA Coding Index | 74.9 | Not measured | Only GPT-5.5 measured |
| LiveCodeBench (Vals AI) | 85.3% | Not measured | Only GPT-5.5 measured |
| SWE-bench Verified (Vals AI) | 82.6% | Not measured | Only GPT-5.5 measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 49.5% | Only GPT-6.1 Terra measured |
| Vibe Code Bench (Vals AI) | 69.8% | 84.0% | GPT-6.1 Terra |
| Code migration (Vals AI) | 45.2% | Not measured | Only GPT-5.5 measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only GPT-5.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 76.4% | Not measured | Only GPT-5.5 measured |
| SkillsBench (Vals AI) | 62.5% | Not measured | Only GPT-5.5 measured |
| SciCode | 56.1% | 55.1% | 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 | 2608.8 | GPT-6.1 Terra |
| LMArena Text: coding | 1494 | Not measured | Only GPT-5.5 measured |
| LMArena Text: software and IT | 1493 | Not measured | Only GPT-5.5 measured |
| LMArena WebDev: React | 1505 | 1657 | GPT-6.1 Terra |
| LMArena WebDev: HTML | 1543 | 1719 | GPT-6.1 Terra |
| LMArena WebDev: from an image | 1532 | Not measured | Only GPT-5.5 measured |
| SWE Atlas: Codebase QnA | 45.4% | Not measured | Only GPT-5.5 measured |
| SWE Atlas: Refactoring | 44.8% | Not measured | Only GPT-5.5 measured |
| SWE Atlas: Test Writing | 42.6% | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 16 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 51.0 | Only GPT-6.1 Terra measured |
| Epoch Capabilities Index | 159.7 | Not measured | Only GPT-5.5 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | GPT-5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| AA Agentic Index | 36.4 | Not measured | Only GPT-5.5 measured |
| Design Arena: agents building web apps | 1118 | 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 | 1161 | 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 | 1142 | Not measured | Only GPT-5.5 measured |
| Design Arena: HTML slides | 963 | Not measured | Only GPT-5.5 measured |
| Design Arena: PowerPoint slides | 1064 | Not measured | Only GPT-5.5 measured |
| LiveBench research | Not measured | 73.9% | Only GPT-6.1 Terra measured |
| LiveBench browser | Not measured | 93.1% | Only GPT-6.1 Terra measured |
| LiveBench long agentic | Not measured | 48.6% | Only GPT-6.1 Terra measured |
| SREBench (Vals AI) | 3.8% | Not measured | Only GPT-5.5 measured |
| Finance Agent (Vals AI) | 51.8% | Not measured | Only GPT-5.5 measured |
| Tax Agent Bench (Vals AI) | 21.8% | 15.2% | GPT-5.5 |
| Legal Research Bench (Vals AI) | 40.4% | 26.0% | GPT-5.5 |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 1.7% | Only GPT-6.1 Terra measured |
| Excel Modeling Benchmark (Vals AI) | 64.5% | Not measured | Only GPT-5.5 measured |
| 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% | 68.3% | GPT-6.1 Terra |
| 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 |
| MCP Atlas | 75.3% | 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 index04
| Benchmark | GPT-5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| GPQA Diamond | 93.2% | Not measured | Only GPT-5.5 measured |
| LiveBench reasoning | Not measured | 88.7% | Only GPT-6.1 Terra measured |
| MMMU Pro (Vals AI) | 88.3% | Not measured | Only GPT-5.5 measured |
| GPQA Diamond (Artificial Analysis run) | 93.5% | Not measured | Only GPT-5.5 measured |
| Humanity's Last Exam (Artificial Analysis run) | 45.8% | 46.2% | GPT-6.1 Terra |
| GPQA Diamond (Epoch AI run) | 90.7% | 94.3% | GPT-6.1 Terra |
| ARC-AGI | 95.0% | Not measured | Only GPT-5.5 measured |
| ARC-AGI-2 | 85.0% | Not measured | Only GPT-5.5 measured |
| 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% | 74.0% | GPT-6.1 Terra |
| EBR-bench | 34.3% | 78.1% | GPT-6.1 Terra |
| LMArena Text: hard prompts | 1489 | Not measured | Only GPT-5.5 measured |
| LMArena Text: expert | 1507 | Not measured | Only GPT-5.5 measured |
| LMArena Text: hard prompts in English | 1483 | Not measured | Only GPT-5.5 measured |
| 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 |
| Humanity's Last Exam (Scale run) | Not measured | 35.7% | Only GPT-6.1 Terra measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GPT-5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| OTIS Mock AIME | 84.4% | 100.0% | GPT-6.1 Terra |
| FrontierMath, tiers 1 to 3 | 85.3% | 90.9% | GPT-6.1 Terra |
| FrontierMath, tier 4 | 72.5% | 92.7% | GPT-6.1 Terra |
| ProofBench | 50.0% | Not measured | Only GPT-5.5 measured |
| LMArena Text: math | 1487 | Not measured | Only GPT-5.5 measured |
| LMArena Text: mathematical work | 1496 | Not measured | Only GPT-5.5 measured |
| MathArena | 59.8% | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| MMLU Pro | 88.1% | Not measured | Only GPT-5.5 measured |
| LegalBench (Vals AI) | 86.5% | Not measured | Only GPT-5.5 measured |
| CaseLaw (Vals AI) | 66.2% | Not measured | Only GPT-5.5 measured |
| CorpFin (Vals AI) | 68.4% | Not measured | Only GPT-5.5 measured |
| TaxEval (Vals AI) | 75.0% | Not measured | Only GPT-5.5 measured |
| MortgageTax (Vals AI) | 68.8% | Not measured | Only GPT-5.5 measured |
| MedCode (Vals AI) | 49.1% | Not measured | Only GPT-5.5 measured |
| SimpleQA Verified | 63.0% | 57.3% | GPT-5.5 |
| LMArena Text: science | 1485 | Not measured | Only GPT-5.5 measured |
| LMArena Text: medicine and healthcare | 1465 | Not measured | Only GPT-5.5 measured |
| LMArena Text: legal and government | 1491 | Not measured | Only GPT-5.5 measured |
| LMArena Text: business and finance | 1478 | Not measured | Only GPT-5.5 measured |
| FACTS Benchmark Suite | 45.8% | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| Design Arena: websites | 1256 | 1283 | GPT-6.1 Terra |
| Design Arena: UI components | 1254 | 1277 | GPT-6.1 Terra |
| Design Arena: game dev | 1292 | 1348 | GPT-6.1 Terra |
| Design Arena: data viz | 1263 | Not measured | Only GPT-5.5 measured |
| Design Arena: 3D | 1194 | Not measured | Only GPT-5.5 measured |
| Design Arena: all code categories | 1259 | 1295 | GPT-6.1 Terra |
| Design Arena: SVG | 1231 | Not measured | Only GPT-5.5 measured |
| Design Arena: ASCII art | 1252 | Not measured | Only GPT-5.5 measured |
| LiveBench design | Not measured | 82.3% | Only GPT-6.1 Terra measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GPT-5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| Vals Index | Not measured | 60.5% | Only GPT-6.1 Terra measured |
| LiveBench data analysis | Not measured | 82.3% | Only GPT-6.1 Terra measured |
| Public Benefits Bench (Vals AI) | 60.9% | Not measured | Only GPT-5.5 measured |
| MedScribe (Vals AI) | 86.9% | Not measured | Only GPT-5.5 measured |
| Vals Multimodal Index | 68.1% | Not measured | Only GPT-5.5 measured |
| IFBench | 75.9% | Not measured | Only GPT-5.5 measured |
| Long context reasoning (AA-LCR) | 84.3% | 82.7% | 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% | 79.2% | GPT-6.1 Terra |
| ExploitBench | 47.4% | Not measured | Only GPT-5.5 measured |
| CL-bench Life | 22.2% | Not measured | Only GPT-5.5 measured |
| LMArena Text | 1472 | Not measured | Only GPT-5.5 measured |
| LMArena Text: instruction following | 1479 | Not measured | Only GPT-5.5 measured |
| LMArena Text: creative writing | 1455 | Not measured | Only GPT-5.5 measured |
| LMArena Vision | 1297 | Not measured | Only GPT-5.5 measured |
| LMArena Text: English | 1470 | Not measured | Only GPT-5.5 measured |
| LMArena Text: non-English | 1467 | Not measured | Only GPT-5.5 measured |
| LMArena Text: Chinese | 1534 | Not measured | Only GPT-5.5 measured |
| LMArena Text: German | 1481 | Not measured | Only GPT-5.5 measured |
| LMArena Text: Japanese | 1499 | Not measured | Only GPT-5.5 measured |
| LMArena Text: Korean | 1460 | Not measured | Only GPT-5.5 measured |
| LMArena Text: French | 1485 | Not measured | Only GPT-5.5 measured |
| LMArena Text: Spanish | 1469 | Not measured | Only GPT-5.5 measured |
| LMArena Text: Russian | 1473 | Not measured | Only GPT-5.5 measured |
| LMArena Text: Polish | 1466 | Not measured | Only GPT-5.5 measured |
| LMArena Text: multi-turn | 1476 | Not measured | Only GPT-5.5 measured |
| LMArena Text: longer queries | 1484 | Not measured | Only GPT-5.5 measured |
| LMArena Text: writing and language | 1466 | Not measured | Only GPT-5.5 measured |
| LMArena Text: entertainment and media | 1449 | Not measured | Only GPT-5.5 measured |
| 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 |
| MultiChallenge | Not measured | 74.2% | Only GPT-6.1 Terra measured |
| EQ-Bench 4 | 1295 | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 8 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.5 | GPT-6.1 Terra | 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-6.1 Terra costs less
Repository review
50K input + 3K output tokens
GPT-6.1 Terra costs less
Agent loop
200K input + 10K output tokens
GPT-6.1 Terra 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 | OpenAI GPT-6.1 Terra |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | April 24, 2026 | October 26, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $5.00 | $1.00 |
| Output $/Mtok | $30.00 | $5.00 |
| Coding index | 67.9 | 77.4 |
| Independent measurements behind it | 4 | 4 |
| Cost per solved task | $1.65 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.5 better than GPT-6.1 Terra for coding?
Pick GPT-6.1 Terra for coding: it scores 77.4 on the Vibe Coding Index against 67.9 for GPT-5.5. Pick GPT-5.5 for work measured by SciCode or Tax Agent Bench (Vals AI), where it leads.
Which is cheaper, GPT-5.5 or GPT-6.1 Terra?
GPT-5.5 costs $5.00 per million input tokens and $30.00 per million output tokens; GPT-6.1 Terra costs $1.00 and $5.00. Cost per solved task is known for GPT-5.5 only.
Which has the bigger context window, GPT-5.5 or GPT-6.1 Terra?
Neither: both take 1.05M tokens.
How many benchmarks is the GPT-5.5 vs GPT-6.1 Terra comparison based on?
23 benchmarks have a result for both models as of October 29, 2026. GPT-5.5's coding index rests on 4 independent benchmarks and GPT-6.1 Terra's on 4. Where only one model has a result, the page says so instead of naming a winner.