Claude Haiku 5.5 vs GPT-6.1 Terra
GPT-6.1 Terra leads Claude Haiku 5.5 on coding, 77.4 to 70.8 on the Vibe Coding Index, and Claude Haiku 5.5 costs 10.0x less per output token ($0.50 vs $5.00 per million). Updated October 29, 2026; 35 benchmarks have a result for both.
Claude Haiku 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 70.8 for Claude Haiku 5.5, though on 4 benchmarks against 5.
Pick Claude Haiku 5.5 for output tokens 10.0x cheaper ($0.50 vs $5.00 per million) and work measured by Vibe Code Bench (Vals AI) or LiveBench research, where it leads.
- Shared results
- 35
- Claude Haiku 5.5 only
- 56
- 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
GPT-6.1 Terra
GPT-6.1 Terra scores 77.4 against 70.8.
5 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-6.1 Terra
GPT-6.1 Terra leads, 51.0 against 36.2.
Same board, both measured
Web design
Design Arena: websites
GPT-6.1 Terra
GPT-6.1 Terra leads, 1283 against 1262.
Same board, both measured
General
Vals Index
GPT-6.1 Terra
GPT-6.1 Terra leads, 60.5% against 58.7%.
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
Claude Haiku 5.5
Claude Haiku 5.5 $0.0003, GPT-6.1 Terra $0.0035 per turn.
List prices
At a glance
- Coding index
- Claude Haiku 5.5 70.8 from 5 benchmarks, GPT-6.1 Terra 77.4 from 4 benchmarks.
- Widest category
- Knowledge, 33.5 points apart on average over 1 shared benchmark.
- Widest single gap
- FrontierMath, tier 4: Claude Haiku 5.5 46.3% against GPT-6.1 Terra 92.7%, 46.3 points apart on a 0 to 100 scale.
- Output price
- Claude Haiku 5.5 $0.50 against GPT-6.1 Terra $5.00 per million output tokens, 10.0x apart.
- Context window
- Claude Haiku 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 Haiku 5.5 | Bars | GPT-6.1 Terra | Ties |
|---|---|---|---|---|
| Coding | 1 | 7 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 4 | 3 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 1 | ||
| Web design | 2 | 3 | ||
| General | 0 | 4 | 1 tie | |
| All shared boards | 7 | 27 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index17
| Benchmark | Claude Haiku 5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| LiveBench coding | 91.4% | 94.3% | GPT-6.1 Terra |
| LMArena WebDev | 1589 | 1673 | GPT-6.1 Terra |
| Terminal-Bench 4 (Vals AI) | 36.4% | 49.5% | GPT-6.1 Terra |
| Vibe Code Bench (Vals AI) | 90.4% | 84.0% | Claude Haiku 5.5 |
| Code migration (Vals AI) | 44.6% | Not measured | Only Claude Haiku 5.5 measured |
| ProgramBench (Vals AI) | 2.5% | Not measured | Only Claude Haiku 5.5 measured |
| IOI (Vals AI) | 47.3% | Not measured | Only Claude Haiku 5.5 measured |
| SWE-bench Multimodal (Vals AI) | 44.0% | Not measured | Only Claude Haiku 5.5 measured |
| Vibe Code Bench 1-100 (Vals AI) | 20.4% | Not measured | Only Claude Haiku 5.5 measured |
| CyberBench (Vals AI) | 75.5% | Not measured | Only Claude Haiku 5.5 measured |
| SciCode | 55.0% | 55.1% | GPT-6.1 Terra |
| FrontierCode | 46.4% | Not measured | Only Claude Haiku 5.5 measured |
| FrontierSWE | 43.8% | Not measured | Only Claude Haiku 5.5 measured |
| ALE-Bench | 1587.0 | 2608.8 | GPT-6.1 Terra |
| LMArena Text: coding | 1454 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: software and IT | 1449 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena WebDev: React | 1608 | 1657 | GPT-6.1 Terra |
| LMArena WebDev: HTML | 1568 | 1719 | GPT-6.1 Terra |
| SciCode | 9.2% | Not measured | Only Claude Haiku 5.5 measured |
| SWE-Bench Pro V2 | 87.2% | Not measured | Only Claude Haiku 5.5 measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Claude Haiku 5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| AA Intelligence Index | 36.2 | 51.0 | GPT-6.1 Terra |
| Epoch Capabilities Index | 159.3 | Not measured | Only Claude Haiku 5.5 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index43
| Benchmark | Claude Haiku 5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| LiveBench research | 81.9% | 73.9% | Claude Haiku 5.5 |
| LiveBench browser | 69.5% | 93.1% | GPT-6.1 Terra |
| LiveBench long agentic | 40.0% | 48.6% | GPT-6.1 Terra |
| SREBench (Vals AI) | 5.7% | Not measured | Only Claude Haiku 5.5 measured |
| Finance Agent (Vals AI) | 54.1% | Not measured | Only Claude Haiku 5.5 measured |
| Tax Agent Bench (Vals AI) | 31.9% | 15.2% | Claude Haiku 5.5 |
| Legal Research Bench (Vals AI) | 43.8% | 26.0% | Claude Haiku 5.5 |
| Harvey's Legal Agent Benchmark (Vals AI) | 4.2% | 1.7% | Claude Haiku 5.5 |
| Excel Modeling Benchmark (Vals AI) | 59.0% | Not measured | Only Claude Haiku 5.5 measured |
| BioMysteryBench (Vals AI) | 70.4% | Not measured | Only Claude Haiku 5.5 measured |
| Terminal-Bench-Science (Vals AI) | 10.0% | Not measured | Only Claude Haiku 5.5 measured |
| Vals Science Index | 38.5% | Not measured | Only Claude Haiku 5.5 measured |
| APEX-Agents | 56.1% | 68.3% | GPT-6.1 Terra |
| Vending-Bench 2 | $3,602 | Not measured | Only Claude Haiku 5.5 measured |
| Neither model has a result on the other 28 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Claude Haiku 5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| LiveBench reasoning | 82.4% | 88.7% | GPT-6.1 Terra |
| MysteryMechanism (Vals AI) | 35.1% | Not measured | Only Claude Haiku 5.5 measured |
| Humanity's Last Exam (Artificial Analysis run) | 44.4% | 46.2% | GPT-6.1 Terra |
| GPQA Diamond (Epoch AI run) | 89.6% | 94.3% | GPT-6.1 Terra |
| ARC-AGI | 89.0% | Not measured | Only Claude Haiku 5.5 measured |
| ARC-AGI-2 | 61.3% | Not measured | Only Claude Haiku 5.5 measured |
| Chess puzzles | 55.0% | Not measured | Only Claude Haiku 5.5 measured |
| Mystery game puzzles | 30.0% | 74.0% | GPT-6.1 Terra |
| EBR-bench | 43.8% | 78.1% | GPT-6.1 Terra |
| LMArena Text: hard prompts | 1421 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: expert | 1454 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: hard prompts in English | 1427 | Not measured | Only Claude Haiku 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 10 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Claude Haiku 5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.9% | 100.0% | GPT-6.1 Terra |
| FrontierMath, tiers 1 to 3 | 75.1% | 90.9% | GPT-6.1 Terra |
| FrontierMath, tier 4 | 46.3% | 92.7% | GPT-6.1 Terra |
| ProofBench | 89.0% | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: math | 1434 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: mathematical work | 1438 | Not measured | Only Claude Haiku 5.5 measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Claude Haiku 5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 51.5% | Not measured | Only Claude Haiku 5.5 measured |
| SimpleQA Verified | 23.8% | 57.3% | GPT-6.1 Terra |
| LMArena Text: science | 1407 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: medicine and healthcare | 1372 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: legal and government | 1391 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: business and finance | 1405 | Not measured | Only Claude Haiku 5.5 measured |
| Neither model has a result on the other 14 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index23
| Benchmark | Claude Haiku 5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| Design Arena: websites | 1262 | 1283 | GPT-6.1 Terra |
| Design Arena: UI components | 1279 | 1277 | Claude Haiku 5.5 |
| Design Arena: game dev | 1321 | 1348 | GPT-6.1 Terra |
| Design Arena: data viz | 1287 | Not measured | Only Claude Haiku 5.5 measured |
| Design Arena: 3D | 1343 | Not measured | Only Claude Haiku 5.5 measured |
| Design Arena: all code categories | 1280 | 1295 | GPT-6.1 Terra |
| Design Arena: SVG | 1202 | Not measured | Only Claude Haiku 5.5 measured |
| LiveBench design | 83.1% | 82.3% | Claude Haiku 5.5 |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Claude Haiku 5.5 | GPT-6.1 Terra | Leader |
|---|---|---|---|
| Vals Index | 58.7% | 60.5% | GPT-6.1 Terra |
| LiveBench data analysis | 53.1% | 82.3% | GPT-6.1 Terra |
| Public Benefits Bench (Vals AI) | 63.2% | Not measured | Only Claude Haiku 5.5 measured |
| SAGE (Vals AI) | 89.8% | Not measured | Only Claude Haiku 5.5 measured |
| MedScribe (Vals AI) | 89.5% | Not measured | Only Claude Haiku 5.5 measured |
| Long context reasoning (AA-LCR) | 82.7% | 82.7% | Tie |
| DTBench | 95.0% | Not measured | Only Claude Haiku 5.5 measured |
| LMCA | 51.1% | Not measured | Only Claude Haiku 5.5 measured |
| Furniture assembly | 47.5% | 79.2% | GPT-6.1 Terra |
| LMArena Text | 1401 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: instruction following | 1415 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: creative writing | 1336 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: English | 1411 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: non-English | 1387 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: Chinese | 1438 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: French | 1430 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: Spanish | 1387 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: Russian | 1370 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: multi-turn | 1398 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: longer queries | 1400 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: writing and language | 1368 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: entertainment and media | 1352 | Not measured | Only Claude Haiku 5.5 measured |
| MultiChallenge | 67.7% | 74.2% | GPT-6.1 Terra |
| Neither model has a result on the other 25 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Haiku 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 Haiku 5.5 costs less
Repository review
50K input + 3K output tokens
Claude Haiku 5.5 costs less
Agent loop
200K input + 10K output tokens
Claude Haiku 5.5 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 Haiku 5.5 | OpenAI GPT-6.1 Terra |
|---|---|---|
| Maker | Anthropic | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | October 7, 2026 | October 26, 2026 |
| Context window | 1M | 1.05M |
| Input $/Mtok | $0.10 | $1.00 |
| Output $/Mtok | $0.50 | $5.00 |
| Coding index | 70.8 | 77.4 |
| Independent measurements behind it | 5 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Haiku 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 70.8 for Claude Haiku 5.5, though on 4 benchmarks against 5. Pick Claude Haiku 5.5 for output tokens 10.0x cheaper ($0.50 vs $5.00 per million) and work measured by Vibe Code Bench (Vals AI) or LiveBench research, where it leads.
Which is cheaper, Claude Haiku 5.5 or GPT-6.1 Terra?
Claude Haiku 5.5 costs $0.10 per million input tokens and $0.50 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 Haiku 5.5 or GPT-6.1 Terra?
GPT-6.1 Terra, with 1.05M tokens against 1M.
How many benchmarks is the Claude Haiku 5.5 vs GPT-6.1 Terra comparison based on?
35 benchmarks have a result for both models as of October 29, 2026. Claude Haiku 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.