Claude Haiku 5.5 vs GPT-5.6 Terra
Claude Haiku 5.5 leads GPT-5.6 Terra on coding, 70.7 to 63.9 on the Vibe Coding Index, and Claude Haiku 5.5 costs 24.0x less per output token ($0.50 vs $12.00 per million). Updated October 22, 2026; 56 benchmarks have a result for both.
Claude Haiku 5.5 or GPT-5.6 Terra: which to pick
Pick Claude Haiku 5.5 for coding: it scores 70.7 on the Vibe Coding Index against 63.9 for GPT-5.6 Terra, though on 5 benchmarks against 6.
Pick GPT-5.6 Terra for a larger context window (1.05M against 1M tokens) and work measured by Code migration (Vals AI) or IOI (Vals AI), where it leads.
- Shared results
- 56
- Claude Haiku 5.5 only
- 9
- GPT-5.6 Terra only
- 73
- 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 Haiku 5.5
Claude Haiku 5.5 scores 70.7 against 63.9.
5 and 6 benchmarks behind the scores
Intelligence
AA Intelligence Index
Claude Haiku 5.5
Claude Haiku 5.5 leads, 43.4 against 42.1.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.6 Terra has a AA Agentic Index result, 43.2.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.6 Terra has a GPQA Diamond result, 90.9%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.6 Terra has a MMLU Pro result, 86.7%.
Directional only
Web design
Design Arena: websites
GPT-5.6 Terra
GPT-5.6 Terra leads, 1268 against 1262.
Same board, both measured
General
Vals Index
No call
Only Claude Haiku 5.5 has a Vals Index result, 58.7%.
Directional only
Long documents
Listed context window
GPT-5.6 Terra
GPT-5.6 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-5.6 Terra $0.0080 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.6 Terra has the number, $0.42.
Directional only
At a glance
- Coding index
- Claude Haiku 5.5 70.7 from 5 benchmarks, GPT-5.6 Terra 63.9 from 6 benchmarks.
- Widest category
- Knowledge, 13.8 points apart on average over 2 shared benchmarks.
- Widest single gap
- IOI (Vals AI): Claude Haiku 5.5 47.3% against GPT-5.6 Terra 87.6%, 40.3 points apart on a 0 to 100 scale.
- Output price
- Claude Haiku 5.5 $0.50 against GPT-5.6 Terra $12.00 per million output tokens, 24.0x apart.
- Context window
- Claude Haiku 5.5 takes 1M tokens, GPT-5.6 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-5.6 Terra | Ties |
|---|---|---|---|---|
| Coding | 10 | 4 | 1 tie | |
| Intelligence | 1 | 1 | ||
| Agentic work | 4 | 6 | 1 tie | |
| Reasoning | 2 | 5 | ||
| Math | 1 | 3 | ||
| Knowledge | 1 | 1 | ||
| Web design | 6 | 1 | ||
| General | 3 | 5 | ||
| All shared boards | 28 | 26 | 2 ties |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index104
| Benchmark | Claude Haiku 5.5 | GPT-5.6 Terra | Leader |
|---|---|---|---|
| LiveBench coding | 91.4% | 86.2% | Claude Haiku 5.5 |
| LMArena WebDev | 1586 | 1522 | Claude Haiku 5.5 |
| AA Coding Index | Not measured | 76.7 | Only GPT-5.6 Terra measured |
| LiveCodeBench (Vals AI) | Not measured | 85.9% | Only GPT-5.6 Terra measured |
| SWE-bench Verified (Vals AI) | Not measured | 95.4% | Only GPT-5.6 Terra measured |
| Terminal-Bench 4 (Vals AI) | 36.4% | 22.7% | Claude Haiku 5.5 |
| Vibe Code Bench (Vals AI) | 90.4% | 74.6% | Claude Haiku 5.5 |
| Code migration (Vals AI) | 44.6% | 47.8% | GPT-5.6 Terra |
| ProgramBench (Vals AI) | 2.5% | 0.5% | Claude Haiku 5.5 |
| IOI (Vals AI) | 47.3% | 87.6% | GPT-5.6 Terra |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 77.5% | Only GPT-5.6 Terra 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% | 14.8% | Claude Haiku 5.5 |
| SkillsBench (Vals AI) | Not measured | 58.9% | Only GPT-5.6 Terra measured |
| CyberBench (Vals AI) | 75.5% | 72.1% | Claude Haiku 5.5 |
| SciCode | 55.0% | 55.0% | Tie |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 62.9% | Only GPT-5.6 Terra measured |
| FrontierCode | 46.4% | 41.3% | Claude Haiku 5.5 |
| FrontierSWE | 43.8% | Not measured | Only Claude Haiku 5.5 measured |
| WeirdML | Not measured | 78.3% | Only GPT-5.6 Terra measured |
| ALE-Bench | Not measured | 1951.4 | Only GPT-5.6 Terra measured |
| LMArena Text: coding | Not measured | 1485 | Only GPT-5.6 Terra measured |
| LMArena Text: software and IT | Not measured | 1482 | Only GPT-5.6 Terra measured |
| LMArena WebDev: React | 1605 | 1513 | Claude Haiku 5.5 |
| LMArena WebDev: HTML | 1569 | 1526 | Claude Haiku 5.5 |
| LMArena WebDev: from an image | Not measured | 1541 | Only GPT-5.6 Terra measured |
| SciCode | 9.2% | 10.8% | GPT-5.6 Terra |
| SWE-Bench Pro V2 | 87.2% | 92.4% | GPT-5.6 Terra |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Claude Haiku 5.5 | GPT-5.6 Terra | Leader |
|---|---|---|---|
| AA Intelligence Index | 43.4 | 42.1 | Claude Haiku 5.5 |
| Epoch Capabilities Index | 159.3 | 160.1 | GPT-5.6 Terra |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index46
| Benchmark | Claude Haiku 5.5 | GPT-5.6 Terra | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 43.2 | Only GPT-5.6 Terra measured |
| Design Arena: agents building web apps | Not measured | 1120 | Only GPT-5.6 Terra measured |
| Design Arena: agents building full-stack apps | Not measured | 1061 | Only GPT-5.6 Terra measured |
| Design Arena: agents building mobile apps | Not measured | 1110 | Only GPT-5.6 Terra measured |
| Design Arena: agents building Android apps | Not measured | 1060 | Only GPT-5.6 Terra measured |
| Design Arena: agents building games | Not measured | 1083 | Only GPT-5.6 Terra measured |
| Design Arena: HTML slides | Not measured | 1047 | Only GPT-5.6 Terra measured |
| Design Arena: PowerPoint slides | Not measured | 1104 | Only GPT-5.6 Terra measured |
| LiveBench research | 81.9% | 60.4% | Claude Haiku 5.5 |
| LiveBench browser | 80.0% | 84.0% | GPT-5.6 Terra |
| LiveBench long agentic | 57.6% | 48.4% | Claude Haiku 5.5 |
| SREBench (Vals AI) | 5.7% | 9.5% | GPT-5.6 Terra |
| Finance Agent (Vals AI) | 54.1% | 54.4% | GPT-5.6 Terra |
| Tax Agent Bench (Vals AI) | 31.9% | 30.0% | Claude Haiku 5.5 |
| Legal Research Bench (Vals AI) | 43.3% | 41.4% | Claude Haiku 5.5 |
| Harvey's Legal Agent Benchmark (Vals AI) | 4.2% | Not measured | Only Claude Haiku 5.5 measured |
| Excel Modeling Benchmark (Vals AI) | 59.0% | 66.2% | GPT-5.6 Terra |
| BioMysteryBench (Vals AI) | 70.4% | Not measured | Only Claude Haiku 5.5 measured |
| Terminal-Bench-Science (Vals AI) | 10.0% | 10.0% | Tie |
| Vals Science Index | 38.5% | Not measured | Only Claude Haiku 5.5 measured |
| τ²-Bench Telecom | Not measured | 86.3% | Only GPT-5.6 Terra measured |
| APEX-Agents | 56.1% | 58.2% | GPT-5.6 Terra |
| BALROG | Not measured | 53.2% | Only GPT-5.6 Terra measured |
| Vending-Bench 2 | $3,602 | $7,343 | GPT-5.6 Terra |
| Neither model has a result on the other 18 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index25
| Benchmark | Claude Haiku 5.5 | GPT-5.6 Terra | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 90.9% | Only GPT-5.6 Terra measured |
| LiveBench reasoning | 82.4% | 90.6% | GPT-5.6 Terra |
| MysteryMechanism (Vals AI) | 35.1% | Not measured | Only Claude Haiku 5.5 measured |
| MMMU Pro (Vals AI) | Not measured | 86.5% | Only GPT-5.6 Terra measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 92.5% | Only GPT-5.6 Terra measured |
| Humanity's Last Exam (Artificial Analysis run) | 44.4% | 42.9% | Claude Haiku 5.5 |
| GPQA Diamond (Epoch AI run) | 89.6% | 93.3% | GPT-5.6 Terra |
| ARC-AGI | 89.0% | 96.5% | GPT-5.6 Terra |
| ARC-AGI-2 | 61.3% | 83.9% | GPT-5.6 Terra |
| SimpleBench | Not measured | 48.9% | Only GPT-5.6 Terra measured |
| Chess puzzles | 55.0% | 47.0% | Claude Haiku 5.5 |
| Mystery game puzzles | 30.0% | 35.0% | GPT-5.6 Terra |
| EBR-bench | 43.8% | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: hard prompts | Not measured | 1469 | Only GPT-5.6 Terra measured |
| LMArena Text: expert | Not measured | 1496 | Only GPT-5.6 Terra measured |
| LMArena Text: hard prompts in English | Not measured | 1465 | Only GPT-5.6 Terra measured |
| LMArena Vision: diagrams | Not measured | 1295 | Only GPT-5.6 Terra measured |
| LMArena Vision: homework | Not measured | 1312 | Only GPT-5.6 Terra measured |
| Kagi LLM Benchmark | Not measured | 51.3% | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | Claude Haiku 5.5 | GPT-5.6 Terra | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.9% | 99.7% | GPT-5.6 Terra |
| FrontierMath, tiers 1 to 3 | 75.1% | 86.0% | GPT-5.6 Terra |
| FrontierMath, tier 4 | 46.3% | 70.7% | GPT-5.6 Terra |
| ProofBench | 89.0% | 74.0% | Claude Haiku 5.5 |
| LMArena Text: math | Not measured | 1465 | Only GPT-5.6 Terra measured |
| LMArena Text: mathematical work | Not measured | 1478 | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Claude Haiku 5.5 | GPT-5.6 Terra | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 86.7% | Only GPT-5.6 Terra measured |
| LegalBench (Vals AI) | Not measured | 85.1% | Only GPT-5.6 Terra measured |
| CorpFin (Vals AI) | Not measured | 65.3% | Only GPT-5.6 Terra measured |
| TaxEval (Vals AI) | Not measured | 76.2% | Only GPT-5.6 Terra measured |
| MortgageTax (Vals AI) | Not measured | 67.3% | Only GPT-5.6 Terra measured |
| MedCode (Vals AI) | 51.5% | 43.4% | Claude Haiku 5.5 |
| SimpleQA Verified | 23.8% | 43.2% | GPT-5.6 Terra |
| LMArena Text: science | Not measured | 1452 | Only GPT-5.6 Terra measured |
| LMArena Text: medicine and healthcare | Not measured | 1430 | Only GPT-5.6 Terra measured |
| LMArena Text: legal and government | Not measured | 1461 | Only GPT-5.6 Terra measured |
| LMArena Text: business and finance | Not measured | 1448 | Only GPT-5.6 Terra measured |
| FACTS Benchmark Suite | Not measured | 52.0% | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 8 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index61
| Benchmark | Claude Haiku 5.5 | GPT-5.6 Terra | Leader |
|---|---|---|---|
| Design Arena: websites | 1262 | 1268 | GPT-5.6 Terra |
| Design Arena: UI components | 1283 | 1256 | Claude Haiku 5.5 |
| Design Arena: game dev | 1315 | 1229 | Claude Haiku 5.5 |
| Design Arena: data viz | 1297 | 1240 | Claude Haiku 5.5 |
| Design Arena: 3D | 1342 | 1134 | Claude Haiku 5.5 |
| Design Arena: all code categories | 1278 | 1240 | Claude Haiku 5.5 |
| Design Arena: SVG | Not measured | 1219 | Only GPT-5.6 Terra measured |
| Design Arena: ASCII art | Not measured | 1178 | Only GPT-5.6 Terra measured |
| LiveBench design | 83.1% | 76.0% | Claude Haiku 5.5 |
GeneralLike-for-likePublic boards, shown as published, kept out of the index35
| Benchmark | Claude Haiku 5.5 | GPT-5.6 Terra | Leader |
|---|---|---|---|
| Vals Index | 58.7% | Not measured | Only Claude Haiku 5.5 measured |
| LiveBench data analysis | 53.1% | 79.3% | GPT-5.6 Terra |
| Public Benefits Bench (Vals AI) | 63.2% | 62.4% | Claude Haiku 5.5 |
| SAGE (Vals AI) | 45.8% | 47.0% | GPT-5.6 Terra |
| MedScribe (Vals AI) | 89.5% | 82.9% | Claude Haiku 5.5 |
| Vals Multimodal Index | Not measured | 65.1% | Only GPT-5.6 Terra measured |
| IFBench | Not measured | 71.2% | Only GPT-5.6 Terra measured |
| Long context reasoning (AA-LCR) | 82.7% | 83.0% | GPT-5.6 Terra |
| DTBench | 95.0% | 93.3% | Claude Haiku 5.5 |
| LMCA | 51.1% | 54.9% | GPT-5.6 Terra |
| Surface Evolver Bench | Not measured | 83.8% | Only GPT-5.6 Terra measured |
| Furniture assembly | 47.5% | 54.2% | GPT-5.6 Terra |
| LMArena Text | Not measured | 1448 | Only GPT-5.6 Terra measured |
| LMArena Text: instruction following | Not measured | 1456 | Only GPT-5.6 Terra measured |
| LMArena Text: creative writing | Not measured | 1413 | Only GPT-5.6 Terra measured |
| LMArena Vision | Not measured | 1271 | Only GPT-5.6 Terra measured |
| LMArena Text: English | Not measured | 1449 | Only GPT-5.6 Terra measured |
| LMArena Text: non-English | Not measured | 1441 | Only GPT-5.6 Terra measured |
| LMArena Text: Chinese | Not measured | 1514 | Only GPT-5.6 Terra measured |
| LMArena Text: German | Not measured | 1460 | Only GPT-5.6 Terra measured |
| LMArena Text: Japanese | Not measured | 1454 | Only GPT-5.6 Terra measured |
| LMArena Text: Korean | Not measured | 1427 | Only GPT-5.6 Terra measured |
| LMArena Text: French | Not measured | 1466 | Only GPT-5.6 Terra measured |
| LMArena Text: Spanish | Not measured | 1451 | Only GPT-5.6 Terra measured |
| LMArena Text: Russian | Not measured | 1452 | Only GPT-5.6 Terra measured |
| LMArena Text: Polish | Not measured | 1446 | Only GPT-5.6 Terra measured |
| LMArena Text: multi-turn | Not measured | 1453 | Only GPT-5.6 Terra measured |
| LMArena Text: longer queries | Not measured | 1454 | Only GPT-5.6 Terra measured |
| LMArena Text: writing and language | Not measured | 1431 | Only GPT-5.6 Terra measured |
| LMArena Text: entertainment and media | Not measured | 1418 | Only GPT-5.6 Terra measured |
| LMArena Vision: English | Not measured | 1272 | Only GPT-5.6 Terra measured |
| LMArena Vision: Chinese | Not measured | 1337 | Only GPT-5.6 Terra measured |
| LMArena Vision: reading text | Not measured | 1278 | Only GPT-5.6 Terra measured |
| LMArena Vision: humor | Not measured | 1236 | Only GPT-5.6 Terra measured |
| LMArena Vision: creative writing | Not measured | 1248 | Only GPT-5.6 Terra measured |
| LMArena Document | Not measured | 1472 | Only GPT-5.6 Terra measured |
| MultiChallenge | 67.7% | Not measured | Only Claude Haiku 5.5 measured |
| EQ-Bench 4 | Not measured | 1234 | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 10 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Haiku 5.5 | GPT-5.6 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-5.6 Terra |
|---|---|---|
| Maker | Anthropic | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | October 7, 2026 | July 9, 2026 |
| Context window | 1M | 1.05M |
| Input $/Mtok | $0.10 | $2.00 |
| Output $/Mtok | $0.50 | $12.00 |
| Coding index | 70.7 | 63.9 |
| Independent measurements behind it | 5 | 6 |
| Cost per solved task | Not computable | $0.42 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Haiku 5.5 better than GPT-5.6 Terra for coding?
Pick Claude Haiku 5.5 for coding: it scores 70.7 on the Vibe Coding Index against 63.9 for GPT-5.6 Terra, though on 5 benchmarks against 6. Pick GPT-5.6 Terra for a larger context window (1.05M against 1M tokens) and work measured by Code migration (Vals AI) or IOI (Vals AI), where it leads.
Which is cheaper, Claude Haiku 5.5 or GPT-5.6 Terra?
Claude Haiku 5.5 costs $0.10 per million input tokens and $0.50 per million output tokens; GPT-5.6 Terra costs $2.00 and $12.00. Cost per solved task is known for GPT-5.6 Terra only.
Which has the bigger context window, Claude Haiku 5.5 or GPT-5.6 Terra?
GPT-5.6 Terra, with 1.05M tokens against 1M.
How many benchmarks is the Claude Haiku 5.5 vs GPT-5.6 Terra comparison based on?
56 benchmarks have a result for both models as of October 22, 2026. Claude Haiku 5.5's coding index rests on 5 independent benchmarks and GPT-5.6 Terra's on 6. Where only one model has a result, the page says so instead of naming a winner.