Claude Opus 5.5 vs GPT-6.1 Terra
Claude Opus 5.5 leads GPT-6.1 Terra on coding, 88.9 to 77.4 on the Vibe Coding Index, and GPT-6.1 Terra costs 4.0x less per output token ($5.00 vs $20.00 per million). Updated October 29, 2026; 35 benchmarks have a result for both.
vs boards won of 35 shared, 1 tied
Claude Opus 5.5 or GPT-6.1 Terra: which to pick
Pick Claude Opus 5.5 for coding: it scores 88.9 on the Vibe Coding Index against 77.4 for GPT-6.1 Terra.
Pick GPT-6.1 Terra for output tokens 4.0x cheaper ($5.00 vs $20.00 per million) and a larger context window (1.05M against 1M tokens).
Model AClaude Opus 5.5Anthropic88.9/1005 independent benchmarksNo cost per solved taskModel BGPT-6.1 TerraOpenAI77.4/1004 independent benchmarksNo cost per solved task
- Shared results
- 35
- Claude Opus 5.5 only
- 80
- GPT-6.1 Terra only
- 1
- Like-for-like categories
- 8 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
Claude Opus 5.5
Claude Opus 5.5 scores 88.9 against 77.4.
5 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
Claude Opus 5.5
Claude Opus 5.5 leads, 58.4 against 51.0.
Same board, both measured
Web design
Design Arena: websites
Claude Opus 5.5
Claude Opus 5.5 leads, 1326 against 1283.
Same board, both measured
General
Vals Index
Claude Opus 5.5
Claude Opus 5.5 leads, 70.2% against 60.5%.
Same board, both measured
Long documents
Listed context window
GPT-6.1 Terra
GPT-6.1 Terra takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-6.1 Terra
Claude Opus 5.5 $0.014, GPT-6.1 Terra $0.0035 per turn.
List prices
At a glance
- Coding index
- Claude Opus 5.5 88.9 from 5 benchmarks, GPT-6.1 Terra 77.4 from 4 benchmarks.
- Widest category
- Agentic work, 15.4 points apart on average over 7 shared benchmarks.
- Widest single gap
- Tax Agent Bench (Vals AI): Claude Opus 5.5 45.6% against GPT-6.1 Terra 15.2%, 30.4 points apart on a 0 to 100 scale.
- Output price
- Claude Opus 5.5 $20.00 against GPT-6.1 Terra $5.00 per million output tokens, 4.0x apart.
- Context window
- Claude Opus 5.5 takes 1M tokens, GPT-6.1 Terra 1.05M.
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 | Claude Opus 5.5 | Bars | GPT-6.1 Terra | Ties |
|---|---|---|---|---|
| Coding | 7 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 6 | 1 | ||
| Reasoning | 3 | 3 | ||
| Math | 2 | 0 | 1 tie | |
| Knowledge | 1 | 0 | ||
| Web design | 5 | 0 | ||
| General | 3 | 1 | ||
| All shared boards | 28 | 6 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index71
| Benchmark | Claude Opus 5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| LiveBench coding | 96.3% | 94.3% | Claude Opus 5.5 |
| LMArena WebDev | 1810 | 1673 | Claude Opus 5.5 |
| Terminal-Bench 4 (Vals AI) | 65.2% | 49.5% | Claude Opus 5.5 |
| Vibe Code Bench (Vals AI) | 90.3% | 84.0% | Claude Opus 5.5 |
| Code migration (Vals AI) | 66.7% | Not measured | Only Claude Opus 5.5 measured |
| ProgramBench (Vals AI) | 18.5% | Not measured | Only Claude Opus 5.5 measured |
| IOI (Vals AI) | 95.1% | Not measured | Only Claude Opus 5.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 87.6% | Not measured | Only Claude Opus 5.5 measured |
| SWE-bench Multimodal (Vals AI) | 70.2% | Not measured | Only Claude Opus 5.5 measured |
| Vibe Code Bench 1-100 (Vals AI) | 30.4% | Not measured | Only Claude Opus 5.5 measured |
| CyberBench (Vals AI) | 74.6% | Not measured | Only Claude Opus 5.5 measured |
| SciCode | 66.9% | 55.1% | Claude Opus 5.5 |
| FrontierCode | 54.6% | Not measured | Only Claude Opus 5.5 measured |
| FrontierSWE | 62.3% | Not measured | Only Claude Opus 5.5 measured |
| MirrorCode | 77.4% | Not measured | Only Claude Opus 5.5 measured |
| ALE-Bench | 2147.4 | 2608.8 | GPT-6.1 Terra |
| LMArena Text: coding | 1547 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: software and IT | 1538 | Not measured | Only Claude Opus 5.5 measured |
| LMArena WebDev: React | 1860 | 1657 | Claude Opus 5.5 |
| LMArena WebDev: HTML | 1753 | 1719 | Claude Opus 5.5 |
| LMArena WebDev: from an image | 1753 | Not measured | Only Claude Opus 5.5 measured |
| SciCode | 18.5% | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Claude Opus 5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| AA Intelligence Index | 58.4 | 51.0 | Claude Opus 5.5 |
| Epoch Capabilities Index | 168.8 | Not measured | Only Claude Opus 5.5 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index61
| Benchmark | Claude Opus 5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1320 | Not measured | Only Claude Opus 5.5 measured |
| Design Arena: agents building mobile apps | 1307 | Not measured | Only Claude Opus 5.5 measured |
| Design Arena: spreadsheets | 1395 | Not measured | Only Claude Opus 5.5 measured |
| LiveBench research | 85.0% | 73.9% | Claude Opus 5.5 |
| LiveBench browser | 88.4% | 93.1% | GPT-6.1 Terra |
| LiveBench long agentic | 72.8% | 48.6% | Claude Opus 5.5 |
| SREBench (Vals AI) | 33.6% | Not measured | Only Claude Opus 5.5 measured |
| Finance Agent (Vals AI) | 58.6% | Not measured | Only Claude Opus 5.5 measured |
| Tax Agent Bench (Vals AI) | 45.6% | 15.2% | Claude Opus 5.5 |
| Legal Research Bench (Vals AI) | 50.5% | 26.0% | Claude Opus 5.5 |
| Harvey's Legal Agent Benchmark (Vals AI) | 9.2% | 1.7% | Claude Opus 5.5 |
| Excel Modeling Benchmark (Vals AI) | 75.9% | Not measured | Only Claude Opus 5.5 measured |
| BioMysteryBench (Vals AI) | 79.3% | Not measured | Only Claude Opus 5.5 measured |
| Terminal-Bench-Science (Vals AI) | 47.1% | Not measured | Only Claude Opus 5.5 measured |
| Vals Science Index | 58.7% | Not measured | Only Claude Opus 5.5 measured |
| Time Horizon Index (Vals AI) | 91.3% | Not measured | Only Claude Opus 5.5 measured |
| CUA-bench (Vals AI) | 14.0% | Not measured | Only Claude Opus 5.5 measured |
| Robo-bench (Vals AI) | 14.6% | Not measured | Only Claude Opus 5.5 measured |
| APEX-Agents | 73.5% | 68.3% | Claude Opus 5.5 |
| Remote Labor Index | 21.3% | Not measured | Only Claude Opus 5.5 measured |
| SpireClimb | 3.3% | Not measured | Only Claude Opus 5.5 measured |
| Vending-Bench 2 | $9,235 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Search | 1213 | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 19 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index33
| Benchmark | Claude Opus 5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| LiveBench reasoning | 92.2% | 88.7% | Claude Opus 5.5 |
| MysteryMechanism (Vals AI) | 49.5% | Not measured | Only Claude Opus 5.5 measured |
| Humanity's Last Exam (Artificial Analysis run) | 61.4% | 46.2% | Claude Opus 5.5 |
| GPQA Diamond (Epoch AI run) | 90.6% | 94.3% | GPT-6.1 Terra |
| ARC-AGI | 98.5% | Not measured | Only Claude Opus 5.5 measured |
| ARC-AGI-2 | 93.3% | Not measured | Only Claude Opus 5.5 measured |
| Chess puzzles | 67.0% | Not measured | Only Claude Opus 5.5 measured |
| Mystery game puzzles | 71.0% | 74.0% | GPT-6.1 Terra |
| EBR-bench | 71.4% | 78.1% | GPT-6.1 Terra |
| LMArena Text: hard prompts | 1536 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: expert | 1548 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: hard prompts in English | 1539 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision: diagrams | 1345 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision: homework | 1362 | Not measured | Only Claude Opus 5.5 measured |
| Humanity's Last Exam (Scale run) | 55.0% | 35.7% | Claude Opus 5.5 |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Claude Opus 5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | 100.0% | Tie |
| FrontierMath, tiers 1 to 3 | 91.2% | 90.9% | Claude Opus 5.5 |
| FrontierMath, tier 4 | 95.0% | 92.7% | Claude Opus 5.5 |
| ProofBench | 100.0% | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: math | 1517 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: mathematical work | 1526 | Not measured | Only Claude Opus 5.5 measured |
| MathArena | 79.0% | Not measured | Only Claude Opus 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 | Claude Opus 5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 49.8% | Not measured | Only Claude Opus 5.5 measured |
| SimpleQA Verified | 72.2% | 57.3% | Claude Opus 5.5 |
| LMArena Text: science | 1520 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: medicine and healthcare | 1510 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: legal and government | 1512 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: business and finance | 1497 | Not measured | Only Claude Opus 5.5 measured |
| FACTS Benchmark Suite | 64.0% | Not measured | Only Claude Opus 5.5 measured |
| PRBench Legal | 47.6% | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 12 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Claude Opus 5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| Design Arena: websites | 1326 | 1283 | Claude Opus 5.5 |
| Design Arena: UI components | 1378 | 1277 | Claude Opus 5.5 |
| Design Arena: game dev | 1436 | 1348 | Claude Opus 5.5 |
| Design Arena: data viz | 1394 | Not measured | Only Claude Opus 5.5 measured |
| Design Arena: 3D | 1466 | Not measured | Only Claude Opus 5.5 measured |
| Design Arena: all code categories | 1385 | 1295 | Claude Opus 5.5 |
| Design Arena: SVG | 1323 | Not measured | Only Claude Opus 5.5 measured |
| Design Arena: ASCII art | 1351 | Not measured | Only Claude Opus 5.5 measured |
| LiveBench design | 86.9% | 82.3% | Claude Opus 5.5 |
GeneralLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | Claude Opus 5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| Vals Index | 70.2% | 60.5% | Claude Opus 5.5 |
| LiveBench data analysis | 80.3% | 82.3% | GPT-6.1 Terra |
| Public Benefits Bench (Vals AI) | 70.6% | Not measured | Only Claude Opus 5.5 measured |
| SAGE (Vals AI) | 91.3% | Not measured | Only Claude Opus 5.5 measured |
| MedScribe (Vals AI) | 91.4% | Not measured | Only Claude Opus 5.5 measured |
| Long context reasoning (AA-LCR) | 84.7% | 82.7% | Claude Opus 5.5 |
| DTBench | 98.9% | Not measured | Only Claude Opus 5.5 measured |
| LMCA | 68.2% | Not measured | Only Claude Opus 5.5 measured |
| Furniture assembly | 83.3% | 79.2% | Claude Opus 5.5 |
| LMArena Text | 1516 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: instruction following | 1539 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: creative writing | 1534 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision | 1321 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: English | 1521 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: non-English | 1506 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: Chinese | 1583 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: German | 1496 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: Japanese | 1538 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: French | 1496 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: Spanish | 1504 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: Russian | 1515 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: multi-turn | 1500 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: longer queries | 1533 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: writing and language | 1531 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: entertainment and media | 1514 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision: English | 1317 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision: reading text | 1326 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision: creative writing | 1320 | Not measured | Only Claude Opus 5.5 measured |
| MultiChallenge | Not measured | 74.2% | Only GPT-6.1 Terra measured |
| EQ-Bench 4 | 1340 | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 18 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Opus 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
Claude Opus 5.5$0.014Fits in one request
GPT-6.1 Terra$0.0035Fits in one request
GPT-6.1 Terra costs less
Repository review
50K input + 3K output tokens
Claude Opus 5.5$0.260Fits in one request
GPT-6.1 Terra$0.065Fits in one request
GPT-6.1 Terra costs less
Agent loop
200K input + 10K output tokens
Claude Opus 5.5$1.00Fits in one request
GPT-6.1 Terra$0.250Fits in one request
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 | Anthropic Claude Opus 5.5 | OpenAI GPT-6.1 Terra |
|---|---|---|
| Maker | Anthropic | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | September 22, 2026 | October 26, 2026 |
| Context window | 1M | 1.05M |
| Input $/Mtok | $4.00 | $1.00 |
| Output $/Mtok | $20.00 | $5.00 |
| Coding index | 88.9 | 77.4 |
| Independent measurements behind it | 5 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Opus 5.5 better than GPT-6.1 Terra for coding?
Pick Claude Opus 5.5 for coding: it scores 88.9 on the Vibe Coding Index against 77.4 for GPT-6.1 Terra. Pick GPT-6.1 Terra for output tokens 4.0x cheaper ($5.00 vs $20.00 per million) and a larger context window (1.05M against 1M tokens).
Which is cheaper, Claude Opus 5.5 or GPT-6.1 Terra?
Claude Opus 5.5 costs $4.00 per million input tokens and $20.00 per million output tokens; GPT-6.1 Terra costs $1.00 and $5.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Claude Opus 5.5 or GPT-6.1 Terra?
GPT-6.1 Terra, with 1.05M tokens against 1M.
How many benchmarks is the Claude Opus 5.5 vs GPT-6.1 Terra comparison based on?
35 benchmarks have a result for both models as of October 29, 2026. Claude Opus 5.5's coding index rests on 5 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.