Claude Haiku 4.5 vs GPT-5.6 Terra

GPT-5.6 Terra leads Claude Haiku 4.5 on coding, 63.9 to 35.6 on the Vibe Coding Index, and Claude Haiku 4.5 costs 2.4x less per output token ($5.00 vs $12.00 per million). Updated October 22, 2026; 85 benchmarks have a result for both.

Replace Claude Haiku 4.5 Replace GPT-5.6 Terra

Claude Haiku 4.5Anthropic

Coding: 35.6
Overall: 41.0
Output $/M: $5.00

GPT-5.6 TerraOpenAI

Coding: 63.9
Overall: 68.1
Output $/M: $12.00

vs boards won of 85 shared

Claude Haiku 4.5 or GPT-5.6 Terra: which to pick

Pick GPT-5.6 Terra for coding: it scores 63.9 on the Vibe Coding Index against 35.6 for Claude Haiku 4.5.

Pick Claude Haiku 4.5 for output tokens 2.4x cheaper ($5.00 vs $12.00 per million) and work measured by MedScribe (Vals AI), where it leads.

Model AClaude Haiku 4.5Anthropic35.6/1004 independent benchmarks$0.56 per solved task Model BGPT-5.6 TerraOpenAI63.9/1006 independent benchmarks$0.42 per solved task

851344

Shared results: 85
Claude Haiku 4.5 only: 13
GPT-5.6 Terra only: 44
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-5.6 Terra
GPT-5.6 Terra scores 63.9 against 35.6.
4 and 6 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.6 Terra
GPT-5.6 Terra leads, 42.1 against 16.9.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.6 Terra
GPT-5.6 Terra leads, 43.2 against 8.0.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.6 Terra
GPT-5.6 Terra leads, 90.9% against 72.2%.
Same board, both measured
Math
AIME
No call
Only Claude Haiku 4.5 has a AIME result, 82.7%.
Directional only
Knowledge
MMLU Pro
GPT-5.6 Terra
GPT-5.6 Terra leads, 86.7% against 78.7%.
Same board, both measured
Web design
Design Arena: websites
GPT-5.6 Terra
GPT-5.6 Terra leads, 1268 against 1122.
Same board, both measured
Long documents
Listed context window
GPT-5.6 Terra
GPT-5.6 Terra takes 1.05M tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Claude Haiku 4.5
Claude Haiku 4.5 $0.0035, GPT-5.6 Terra $0.0080 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.6 Terra
Claude Haiku 4.5 $0.56, GPT-5.6 Terra $0.42.
Published attempt cost and pass rate

At a glance

Coding index: Claude Haiku 4.5 35.6 from 4 benchmarks, GPT-5.6 Terra 63.9 from 6 benchmarks.
Widest category: Agentic work, 32.2 points apart on average over 10 shared benchmarks.
Widest single gap: ARC-AGI-2: Claude Haiku 4.5 4.0% against GPT-5.6 Terra 83.9%, 79.9 points apart on a 0 to 100 scale.
Output price: Claude Haiku 4.5 $5.00 against GPT-5.6 Terra $12.00 per million output tokens, 2.4x apart.
Context window: Claude Haiku 4.5 takes 200K 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.

Boards won, where both have a result
Category	Claude Haiku 4.5	GPT-5.6 Terra
Coding	0	14
Intelligence	0	2
Agentic work	0	10
Reasoning	0	10
Math	0	3
Knowledge	0	11
Web design	0	9
General	1	25
All shared boards	1	84

CodingLike-for-likeSix of these boards feed the Vibe Coding Index014

Coding benchmarks for Claude Haiku 4.5 and GPT-5.6 Terra
Benchmark	Claude Haiku 4.5	GPT-5.6 Terra	Leader
SWE-bench Verified	66.6%	Not measured	Only Claude Haiku 4.5 measured
SWE-bench Multilingual	64.7%	Not measured	Only Claude Haiku 4.5 measured
LiveBench coding	48.1%	86.2%	GPT-5.6 Terra
LMArena WebDev	1330	1522	GPT-5.6 Terra
AA Coding Index	43.9	76.7	GPT-5.6 Terra
LiveCodeBench (Vals AI)	41.2%	85.9%	GPT-5.6 Terra
SWE-bench Verified (Vals AI)	66.6%	95.4%	GPT-5.6 Terra
Terminal-Bench 4 (Vals AI)	Not measured	22.7%	Only GPT-5.6 Terra measured
Vibe Code Bench (Vals AI)	11.4%	74.6%	GPT-5.6 Terra
Code migration (Vals AI)	7.5%	47.8%	GPT-5.6 Terra
ProgramBench (Vals AI)	0.0%	0.5%	GPT-5.6 Terra
IOI (Vals AI)	Not measured	87.6%	Only GPT-5.6 Terra measured
Terminal-Bench 2.1 (Vals AI)	43.8%	77.5%	GPT-5.6 Terra
Vibe Code Bench 1-100 (Vals AI)	Not measured	14.8%	Only GPT-5.6 Terra measured
SkillsBench (Vals AI)	Not measured	58.9%	Only GPT-5.6 Terra measured
CyberBench (Vals AI)	Not measured	72.1%	Only GPT-5.6 Terra measured
SciCode	Not measured	55.0%	Only GPT-5.6 Terra measured
Terminal-Bench Hard (Artificial Analysis run)	Not measured	62.9%	Only GPT-5.6 Terra measured
Terminal-Bench	35.5%	Not measured	Only Claude Haiku 4.5 measured
FrontierCode	Not measured	41.3%	Only GPT-5.6 Terra measured
WeirdML	45.4%	78.3%	GPT-5.6 Terra
ALE-Bench	Not measured	1951.4	Only GPT-5.6 Terra measured
LMArena Text: coding	1454	1485	GPT-5.6 Terra
LMArena Text: software and IT	1439	1482	GPT-5.6 Terra
LMArena WebDev: React	1326	1513	GPT-5.6 Terra
LMArena WebDev: HTML	1318	1526	GPT-5.6 Terra
LMArena WebDev: from an image	Not measured	1541	Only GPT-5.6 Terra measured
SciCode	Not measured	10.8%	Only GPT-5.6 Terra measured
SWE-Bench Pro V2	Not measured	92.4%	Only GPT-5.6 Terra measured
Neither model has a result on the other 14 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02

Intelligence benchmarks for Claude Haiku 4.5 and GPT-5.6 Terra
Benchmark	Claude Haiku 4.5	GPT-5.6 Terra	Leader
AA Intelligence Index	16.9	42.1	GPT-5.6 Terra
Epoch Capabilities Index	142.2	160.1	GPT-5.6 Terra

Agentic workLike-for-likePublic boards, shown as published, kept out of the index010

Agentic work benchmarks for Claude Haiku 4.5 and GPT-5.6 Terra
Benchmark	Claude Haiku 4.5	GPT-5.6 Terra	Leader
AA Agentic Index	8.0	43.2	GPT-5.6 Terra
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	42.2%	60.4%	GPT-5.6 Terra
LiveBench browser	40.0%	84.0%	GPT-5.6 Terra
LiveBench long agentic	11.1%	48.4%	GPT-5.6 Terra
SREBench (Vals AI)	Not measured	9.5%	Only GPT-5.6 Terra measured
Finance Agent (Vals AI)	31.0%	54.4%	GPT-5.6 Terra
Tax Agent Bench (Vals AI)	5.9%	30.0%	GPT-5.6 Terra
Legal Research Bench (Vals AI)	10.6%	41.4%	GPT-5.6 Terra
Excel Modeling Benchmark (Vals AI)	22.7%	66.2%	GPT-5.6 Terra
Terminal-Bench-Science (Vals AI)	Not measured	10.0%	Only GPT-5.6 Terra measured
τ²-Bench Telecom	Not measured	86.3%	Only GPT-5.6 Terra measured
APEX-Agents	Not measured	58.2%	Only GPT-5.6 Terra measured
BALROG	31.2%	53.2%	GPT-5.6 Terra
DeepResearch Bench	45.5%	Not measured	Only Claude Haiku 4.5 measured
Vending-Bench 2	$459	$7,343	GPT-5.6 Terra
Berkeley Function Calling Leaderboard (BFCL)	68.7%	Not measured	Only Claude Haiku 4.5 measured
MCP Atlas	40.2%	Not measured	Only Claude Haiku 4.5 measured
Neither model has a result on the other 18 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index010

Reasoning benchmarks for Claude Haiku 4.5 and GPT-5.6 Terra
Benchmark	Claude Haiku 4.5	GPT-5.6 Terra	Leader
GPQA Diamond	72.2%	90.9%	GPT-5.6 Terra
LiveBench reasoning	61.7%	90.6%	GPT-5.6 Terra
MMMU Pro (Vals AI)	46.1%	86.5%	GPT-5.6 Terra
GPQA Diamond (Artificial Analysis run)	Not measured	92.5%	Only GPT-5.6 Terra measured
Humanity's Last Exam (Artificial Analysis run)	Not measured	42.9%	Only GPT-5.6 Terra measured
GPQA Diamond (Epoch AI run)	71.2%	93.3%	GPT-5.6 Terra
ARC-AGI	47.7%	96.5%	GPT-5.6 Terra
ARC-AGI-2	4.0%	83.9%	GPT-5.6 Terra
SimpleBench	Not measured	48.9%	Only GPT-5.6 Terra measured
Chess puzzles	8.0%	47.0%	GPT-5.6 Terra
Mystery game puzzles	Not measured	35.0%	Only GPT-5.6 Terra measured
LMArena Text: hard prompts	1421	1469	GPT-5.6 Terra
LMArena Text: expert	1443	1496	GPT-5.6 Terra
LMArena Text: hard prompts in English	1435	1465	GPT-5.6 Terra
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 6 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index03

Math benchmarks for Claude Haiku 4.5 and GPT-5.6 Terra
Benchmark	Claude Haiku 4.5	GPT-5.6 Terra	Leader
AIME	82.7%	Not measured	Only Claude Haiku 4.5 measured
MGSM (Vals AI)	92.2%	Not measured	Only Claude Haiku 4.5 measured
OTIS Mock AIME	66.7%	99.7%	GPT-5.6 Terra
FrontierMath, tiers 1 to 3	Not measured	86.0%	Only GPT-5.6 Terra measured
FrontierMath, tier 4	Not measured	70.7%	Only GPT-5.6 Terra measured
ProofBench	Not measured	74.0%	Only GPT-5.6 Terra measured
MATH level 5	96.4%	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: math	1398	1465	GPT-5.6 Terra
LMArena Text: mathematical work	1430	1478	GPT-5.6 Terra
Neither model has a result on the other 5 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index011

Knowledge benchmarks for Claude Haiku 4.5 and GPT-5.6 Terra
Benchmark	Claude Haiku 4.5	GPT-5.6 Terra	Leader
MMLU Pro	78.7%	86.7%	GPT-5.6 Terra
LegalBench (Vals AI)	81.2%	85.1%	GPT-5.6 Terra
CaseLaw (Vals AI)	56.5%	Not measured	Only Claude Haiku 4.5 measured
CorpFin (Vals AI)	60.6%	65.3%	GPT-5.6 Terra
TaxEval (Vals AI)	67.5%	76.2%	GPT-5.6 Terra
MortgageTax (Vals AI)	62.2%	67.3%	GPT-5.6 Terra
MedQA (Vals AI)	79.6%	Not measured	Only Claude Haiku 4.5 measured
MedCode (Vals AI)	32.7%	43.4%	GPT-5.6 Terra
SimpleQA Verified	13.2%	43.2%	GPT-5.6 Terra
LMArena Text: science	1406	1452	GPT-5.6 Terra
LMArena Text: medicine and healthcare	1394	1430	GPT-5.6 Terra
LMArena Text: legal and government	1400	1461	GPT-5.6 Terra
LMArena Text: business and finance	1400	1448	GPT-5.6 Terra
FACTS Benchmark Suite	Not measured	52.0%	Only GPT-5.6 Terra measured
Neither model has a result on the other 6 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index09

Web design benchmarks for Claude Haiku 4.5 and GPT-5.6 Terra
Benchmark	Claude Haiku 4.5	GPT-5.6 Terra	Leader
Design Arena: websites	1122	1268	GPT-5.6 Terra
Design Arena: UI components	1097	1256	GPT-5.6 Terra
Design Arena: game dev	1096	1229	GPT-5.6 Terra
Design Arena: data viz	1124	1240	GPT-5.6 Terra
Design Arena: 3D	1071	1134	GPT-5.6 Terra
Design Arena: all code categories	1114	1240	GPT-5.6 Terra
Design Arena: SVG	1025	1219	GPT-5.6 Terra
Design Arena: ASCII art	1140	1178	GPT-5.6 Terra
LiveBench design	59.9%	76.0%	GPT-5.6 Terra

GeneralLike-for-likePublic boards, shown as published, kept out of the index125

General benchmarks for Claude Haiku 4.5 and GPT-5.6 Terra
Benchmark	Claude Haiku 4.5	GPT-5.6 Terra	Leader
LiveBench data analysis	59.3%	79.3%	GPT-5.6 Terra
Public Benefits Bench (Vals AI)	54.3%	62.4%	GPT-5.6 Terra
SAGE (Vals AI)	31.8%	47.0%	GPT-5.6 Terra
MedScribe (Vals AI)	85.2%	82.9%	Claude Haiku 4.5
Vals Multimodal Index	42.9%	65.1%	GPT-5.6 Terra
IFBench	Not measured	71.2%	Only GPT-5.6 Terra measured
Long context reasoning (AA-LCR)	Not measured	83.0%	Only GPT-5.6 Terra measured
DTBench	73.6%	93.3%	GPT-5.6 Terra
LMCA	30.9%	54.9%	GPT-5.6 Terra
Surface Evolver Bench	Not measured	83.8%	Only GPT-5.6 Terra measured
Furniture assembly	Not measured	54.2%	Only GPT-5.6 Terra measured
ExploitBench	13.7%	Not measured	Only Claude Haiku 4.5 measured
LMArena Text	1397	1448	GPT-5.6 Terra
LMArena Text: instruction following	1414	1456	GPT-5.6 Terra
LMArena Text: creative writing	1371	1413	GPT-5.6 Terra
LMArena Vision	Not measured	1271	Only GPT-5.6 Terra measured
LMArena Text: English	1414	1449	GPT-5.6 Terra
LMArena Text: non-English	1377	1441	GPT-5.6 Terra
LMArena Text: Chinese	1418	1514	GPT-5.6 Terra
LMArena Text: German	1374	1460	GPT-5.6 Terra
LMArena Text: Japanese	1338	1454	GPT-5.6 Terra
LMArena Text: Korean	1346	1427	GPT-5.6 Terra
LMArena Text: French	1411	1466	GPT-5.6 Terra
LMArena Text: Spanish	1421	1451	GPT-5.6 Terra
LMArena Text: Russian	1381	1452	GPT-5.6 Terra
LMArena Text: Polish	1343	1446	GPT-5.6 Terra
LMArena Text: multi-turn	1409	1453	GPT-5.6 Terra
LMArena Text: longer queries	1427	1454	GPT-5.6 Terra
LMArena Text: writing and language	1386	1431	GPT-5.6 Terra
LMArena Text: entertainment and media	1369	1418	GPT-5.6 Terra
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	1420	1472	GPT-5.6 Terra
MultiChallenge	50.5%	Not measured	Only Claude Haiku 4.5 measured
EQ-Bench 4	1064	1234	GPT-5.6 Terra
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

Image generation benchmarks for Claude Haiku 4.5 and GPT-5.6 Terra
Benchmark	Claude Haiku 4.5	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 4.5$0.0035Fits in one request

GPT-5.6 Terra$0.0080Fits in one request

Claude Haiku 4.5 costs less

Repository review

50K input + 3K output tokens

Claude Haiku 4.5$0.065Fits in one request

GPT-5.6 Terra$0.136Fits in one request

Claude Haiku 4.5 costs less

Agent loop

200K input + 10K output tokens

Claude Haiku 4.5$0.250Exceeds the context window

GPT-5.6 Terra$0.520Fits in one request

Claude Haiku 4.5 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.

Specifications of Claude Haiku 4.5 and GPT-5.6 Terra
Specification	Anthropic Claude Haiku 4.5	OpenAI GPT-5.6 Terra
Maker	Anthropic	OpenAI
Weights	No public weights listed	No public weights listed
Released	October 15, 2025	July 9, 2026
Context window	200K	1.05M
Input $/Mtok	$1.00	$2.00
Output $/Mtok	$5.00	$12.00
Coding index	35.6	63.9
Independent measurements behind it	4	6
Cost per solved task	$0.56	$0.42
Source	OpenRouter listing	OpenRouter listing

Questions

Is Claude Haiku 4.5 better than GPT-5.6 Terra for coding?

Pick GPT-5.6 Terra for coding: it scores 63.9 on the Vibe Coding Index against 35.6 for Claude Haiku 4.5. Pick Claude Haiku 4.5 for output tokens 2.4x cheaper ($5.00 vs $12.00 per million) and work measured by MedScribe (Vals AI), where it leads.

Which is cheaper, Claude Haiku 4.5 or GPT-5.6 Terra?

Claude Haiku 4.5 costs $1.00 per million input tokens and $5.00 per million output tokens; GPT-5.6 Terra costs $2.00 and $12.00. Per solved SWE-bench Verified task, Claude Haiku 4.5 costs $0.56 and GPT-5.6 Terra $0.42.

Which has the bigger context window, Claude Haiku 4.5 or GPT-5.6 Terra?

GPT-5.6 Terra, with 1.05M tokens against 200K.

How many benchmarks is the Claude Haiku 4.5 vs GPT-5.6 Terra comparison based on?

85 benchmarks have a result for both models as of October 22, 2026. Claude Haiku 4.5's coding index rests on 4 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.

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Claude Haiku 4.5 or GPT-5.6 Terra: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Math

Knowledge

Web design

Long documents

Everyday cost

Cost per solved task

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

Compare next