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Claude Opus 4.8 vs GPT-5.6 Terra

Claude Opus 4.8 leads GPT-5.6 Terra on coding, 65.0 to 63.9 on the Vibe Coding Index, and GPT-5.6 Terra costs 2.1x less per output token ($12.00 vs $25.00 per million). Updated October 23, 2026; 121 benchmarks have a result for both.

Replace Claude Opus 4.8 Replace GPT-5.6 Terra
Claude Opus 4.8Anthropic
Coding
65.0
Overall
69.8
Output $/M
$25.00
84
GPT-5.6 TerraOpenAI
Coding
63.9
Overall
68.1
Output $/M
$12.00
36
vs boards won of 121 shared, 1 tied

Claude Opus 4.8 or GPT-5.6 Terra: which to pick

Claude Opus 4.8 and GPT-5.6 Terra are level for coding, 65.0 against 63.9 on the Vibe Coding Index, so price and context decide.

Pick GPT-5.6 Terra for output tokens 2.1x cheaper ($12.00 vs $25.00 per million) and a lower cost per solved task ($0.42 against $2.17). Pick Claude Opus 4.8 for work measured by LMArena WebDev or LiveCodeBench (Vals AI), where it leads.

Model AClaude Opus 4.8Anthropic65.0/1006 independent benchmarks$2.17 per solved taskModel BGPT-5.6 TerraOpenAI63.9/1006 independent benchmarks$0.42 per solved task
Shared results
121
Claude Opus 4.8 only
15
GPT-5.6 Terra only
8
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.

At a glance

Coding index
Claude Opus 4.8 65.0 from 6 benchmarks, GPT-5.6 Terra 63.9 from 6 benchmarks.
Widest category
Agentic work, 10.2 points apart on average over 19 shared benchmarks.
Widest single gap
Kagi LLM Benchmark: Claude Opus 4.8 88.8% against GPT-5.6 Terra 51.3%, 37.5 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.8 $25.00 against GPT-5.6 Terra $12.00 per million output tokens, 2.1x apart.
Context window
Claude Opus 4.8 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.

Boards won, where both have a result
CategoryClaude Opus 4.8BarsGPT-5.6 TerraTies
Coding137
Intelligence02
Agentic work127
Reasoning125
Math24
Knowledge102
Web design531 tie
General306
All shared boards84361 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index137
Coding benchmarks for Claude Opus 4.8 and GPT-5.6 Terra
BenchmarkClaude Opus 4.8GPT-5.6 TerraLeader
LiveBench coding77.3%86.2%GPT-5.6 Terra
LMArena WebDev15561521Claude Opus 4.8
AA Coding Index74.376.7GPT-5.6 Terra
LiveCodeBench (Vals AI)87.8%85.9%Claude Opus 4.8
SWE-bench Verified (Vals AI)88.6%95.4%GPT-5.6 Terra
Terminal-Bench 4 (Vals AI)23.2%22.7%Claude Opus 4.8
Vibe Code Bench (Vals AI)82.7%74.6%Claude Opus 4.8
Code migration (Vals AI)47.3%47.8%GPT-5.6 Terra
ProgramBench (Vals AI)1.0%0.5%Claude Opus 4.8
IOI (Vals AI)Not measured87.6%Only GPT-5.6 Terra measured
Terminal-Bench 2.1 (Vals AI)71.9%77.5%GPT-5.6 Terra
Vibe Code Bench 1-100 (Vals AI)Not measured14.8%Only GPT-5.6 Terra measured
SkillsBench (Vals AI)59.2%58.9%Claude Opus 4.8
CyberBench (Vals AI)Not measured72.1%Only GPT-5.6 Terra measured
SciCode54.4%55.0%GPT-5.6 Terra
Terminal-Bench Hard (Artificial Analysis run)58.3%62.9%GPT-5.6 Terra
FrontierCode46.5%41.3%Claude Opus 4.8
GSO-Bench47.1%Not measuredOnly Claude Opus 4.8 measured
WeirdML82.9%78.3%Claude Opus 4.8
ALE-BenchNot measured1951.4Only GPT-5.6 Terra measured
LMArena Text: coding14911486Claude Opus 4.8
LMArena Text: software and IT14881482Claude Opus 4.8
LMArena WebDev: React15571511Claude Opus 4.8
LMArena WebDev: HTML15431526Claude Opus 4.8
LMArena WebDev: from an imageNot measured1541Only GPT-5.6 Terra measured
SciCode12.3%10.8%Claude Opus 4.8
SWE-Bench Pro V2Not measured92.4%Only GPT-5.6 Terra measured
SWE Atlas: Codebase QnA57.3%Not measuredOnly Claude Opus 4.8 measured
SWE Atlas: Refactoring46.7%Not measuredOnly Claude Opus 4.8 measured
SWE Atlas: Test Writing49.6%Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 13 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Claude Opus 4.8 and GPT-5.6 Terra
BenchmarkClaude Opus 4.8GPT-5.6 TerraLeader
AA Intelligence Index41.842.1GPT-5.6 Terra
Epoch Capabilities Index159.0160.1GPT-5.6 Terra
Agentic workLike-for-likePublic boards, shown as published, kept out of the index127
Agentic work benchmarks for Claude Opus 4.8 and GPT-5.6 Terra
BenchmarkClaude Opus 4.8GPT-5.6 TerraLeader
AA Agentic Index41.943.2GPT-5.6 Terra
Design Arena: agents building web apps12331120Claude Opus 4.8
Design Arena: agents building full-stack apps12491061Claude Opus 4.8
Design Arena: agents building mobile apps12221110Claude Opus 4.8
Design Arena: agents building Android apps12341061Claude Opus 4.8
Design Arena: agents building Godot games1231Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building games12391081Claude Opus 4.8
Design Arena: HTML slides11261013Claude Opus 4.8
Design Arena: PowerPoint slides11921095Claude Opus 4.8
Design Arena: spreadsheets1315Not measuredOnly Claude Opus 4.8 measured
LiveBench research81.8%60.4%Claude Opus 4.8
LiveBench browser96.0%84.0%Claude Opus 4.8
LiveBench long agentic48.3%48.4%GPT-5.6 Terra
SREBench (Vals AI)Not measured9.5%Only GPT-5.6 Terra measured
Finance Agent (Vals AI)53.9%54.4%GPT-5.6 Terra
Tax Agent Bench (Vals AI)30.0%30.0%GPT-5.6 Terra
Legal Research Bench (Vals AI)43.8%41.4%Claude Opus 4.8
Excel Modeling Benchmark (Vals AI)69.4%66.2%Claude Opus 4.8
Terminal-Bench-Science (Vals AI)4.3%10.0%GPT-5.6 Terra
Time Horizon Index (Vals AI)11.8%Not measuredOnly Claude Opus 4.8 measured
τ²-Bench Telecom94.4%86.3%Claude Opus 4.8
APEX-Agents48.9%58.2%GPT-5.6 Terra
Remote Labor Index8.3%Not measuredOnly Claude Opus 4.8 measured
OSWorld 2.020.6%Not measuredOnly Claude Opus 4.8 measured
BALROGNot measured53.2%Only GPT-5.6 Terra measured
DeepResearch Bench50.2%Not measuredOnly Claude Opus 4.8 measured
PostTrainBench33.8%Not measuredOnly Claude Opus 4.8 measured
Vending-Bench 2$5,787$7,343GPT-5.6 Terra
LMArena Search1204Not measuredOnly Claude Opus 4.8 measured
MCP Atlas82.2%Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 12 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index125
Reasoning benchmarks for Claude Opus 4.8 and GPT-5.6 Terra
BenchmarkClaude Opus 4.8GPT-5.6 TerraLeader
GPQA Diamond92.4%90.9%Claude Opus 4.8
LiveBench reasoning89.2%90.6%GPT-5.6 Terra
MMMU Pro (Vals AI)86.6%86.5%Claude Opus 4.8
GPQA Diamond (Artificial Analysis run)92.0%92.5%GPT-5.6 Terra
Humanity's Last Exam (Artificial Analysis run)48.7%42.9%Claude Opus 4.8
GPQA Diamond (Epoch AI run)91.0%93.3%GPT-5.6 Terra
ARC-AGI92.5%96.5%GPT-5.6 Terra
ARC-AGI-272.1%83.9%GPT-5.6 Terra
SimpleBench64.8%48.9%Claude Opus 4.8
Chess puzzles52.0%47.0%Claude Opus 4.8
Mystery game puzzles36.0%35.0%Claude Opus 4.8
EBR-bench28.6%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: hard prompts14821469Claude Opus 4.8
LMArena Text: expert15031496Claude Opus 4.8
LMArena Text: hard prompts in English14871465Claude Opus 4.8
LMArena Vision: diagrams13151295Claude Opus 4.8
LMArena Vision: homework13371312Claude Opus 4.8
Kagi LLM Benchmark88.8%51.3%Claude Opus 4.8
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index24
Math benchmarks for Claude Opus 4.8 and GPT-5.6 Terra
BenchmarkClaude Opus 4.8GPT-5.6 TerraLeader
OTIS Mock AIME98.3%99.7%GPT-5.6 Terra
FrontierMath, tiers 1 to 380.0%86.0%GPT-5.6 Terra
FrontierMath, tier 456.1%70.7%GPT-5.6 Terra
ProofBench69.0%74.0%GPT-5.6 Terra
LMArena Text: math14861466Claude Opus 4.8
LMArena Text: mathematical work14971478Claude Opus 4.8
MathArena39.8%Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index102
Knowledge benchmarks for Claude Opus 4.8 and GPT-5.6 Terra
BenchmarkClaude Opus 4.8GPT-5.6 TerraLeader
MMLU Pro89.6%86.7%Claude Opus 4.8
LegalBench (Vals AI)83.6%85.1%GPT-5.6 Terra
CorpFin (Vals AI)66.7%65.3%Claude Opus 4.8
TaxEval (Vals AI)75.6%76.2%GPT-5.6 Terra
MortgageTax (Vals AI)69.9%67.3%Claude Opus 4.8
MedCode (Vals AI)53.2%43.4%Claude Opus 4.8
SimpleQA Verified53.0%43.2%Claude Opus 4.8
LMArena Text: science14771452Claude Opus 4.8
LMArena Text: medicine and healthcare14641432Claude Opus 4.8
LMArena Text: legal and government14771462Claude Opus 4.8
LMArena Text: business and finance14581448Claude Opus 4.8
FACTS Benchmark Suite53.5%52.0%Claude Opus 4.8
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index53
Web design benchmarks for Claude Opus 4.8 and GPT-5.6 Terra
BenchmarkClaude Opus 4.8GPT-5.6 TerraLeader
Design Arena: websites12581268GPT-5.6 Terra
Design Arena: UI components12551256GPT-5.6 Terra
Design Arena: game dev12641229Claude Opus 4.8
Design Arena: data viz12401240Tie
Design Arena: 3D12241135Claude Opus 4.8
Design Arena: all code categories12551241Claude Opus 4.8
Design Arena: SVG11941219GPT-5.6 Terra
Design Arena: ASCII art12771178Claude Opus 4.8
LiveBench design78.8%76.0%Claude Opus 4.8
GeneralLike-for-likePublic boards, shown as published, kept out of the index306
General benchmarks for Claude Opus 4.8 and GPT-5.6 Terra
BenchmarkClaude Opus 4.8GPT-5.6 TerraLeader
LiveBench data analysis66.0%79.3%GPT-5.6 Terra
Public Benefits Bench (Vals AI)68.1%62.4%Claude Opus 4.8
SAGE (Vals AI)54.8%47.0%Claude Opus 4.8
MedScribe (Vals AI)85.8%82.9%Claude Opus 4.8
Vals Multimodal Index70.9%65.1%Claude Opus 4.8
IFBench62.2%71.2%GPT-5.6 Terra
Long context reasoning (AA-LCR)77.7%83.0%GPT-5.6 Terra
DTBench94.9%93.3%Claude Opus 4.8
LMCA57.5%54.9%Claude Opus 4.8
Surface Evolver Bench87.5%83.8%Claude Opus 4.8
Furniture assembly42.5%54.2%GPT-5.6 Terra
LMArena Text14611448Claude Opus 4.8
LMArena Text: instruction following14761455Claude Opus 4.8
LMArena Text: creative writing14541413Claude Opus 4.8
LMArena Vision12941271Claude Opus 4.8
LMArena Text: English14691449Claude Opus 4.8
LMArena Text: non-English14501441Claude Opus 4.8
LMArena Text: Chinese15061514GPT-5.6 Terra
LMArena Text: German14731461Claude Opus 4.8
LMArena Text: Japanese14421453GPT-5.6 Terra
LMArena Text: Korean14301423Claude Opus 4.8
LMArena Text: French14811466Claude Opus 4.8
LMArena Text: Spanish14651448Claude Opus 4.8
LMArena Text: Russian14741453Claude Opus 4.8
LMArena Text: Polish14591447Claude Opus 4.8
LMArena Text: multi-turn14761453Claude Opus 4.8
LMArena Text: longer queries14841453Claude Opus 4.8
LMArena Text: writing and language14611432Claude Opus 4.8
LMArena Text: entertainment and media14401419Claude Opus 4.8
LMArena Vision: English12931272Claude Opus 4.8
LMArena Vision: Chinese13461337Claude Opus 4.8
LMArena Vision: reading text13031278Claude Opus 4.8
LMArena Vision: humor12821236Claude Opus 4.8
LMArena Vision: creative writing13011248Claude Opus 4.8
LMArena Document14751472Claude Opus 4.8
EQ-Bench 412811234Claude Opus 4.8
Neither model has a result on the other 12 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.8 and GPT-5.6 Terra
BenchmarkClaude Opus 4.8GPT-5.6 TerraLeader
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 4.8$0.018Fits in one request
GPT-5.6 Terra$0.0080Fits in one request

GPT-5.6 Terra costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.8$0.325Fits in one request
GPT-5.6 Terra$0.136Fits in one request

GPT-5.6 Terra costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.8$1.25Fits in one request
GPT-5.6 Terra$0.520Fits in one request

GPT-5.6 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.

Specifications of Claude Opus 4.8 and GPT-5.6 Terra
SpecificationAnthropic Claude Opus 4.8OpenAI GPT-5.6 Terra
MakerAnthropicOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedMay 27, 2026July 9, 2026
Context window1M1.05M
Input $/Mtok$5.00$2.00
Output $/Mtok$25.00$12.00
Coding index65.063.9
Independent measurements behind it66
Cost per solved task$2.17$0.42
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.8 better than GPT-5.6 Terra for coding?

Claude Opus 4.8 and GPT-5.6 Terra are level for coding, 65.0 against 63.9 on the Vibe Coding Index, so price and context decide. Pick GPT-5.6 Terra for output tokens 2.1x cheaper ($12.00 vs $25.00 per million) and a lower cost per solved task ($0.42 against $2.17). Pick Claude Opus 4.8 for work measured by LMArena WebDev or LiveCodeBench (Vals AI), where it leads.

Which is cheaper, Claude Opus 4.8 or GPT-5.6 Terra?

Claude Opus 4.8 costs $5.00 per million input tokens and $25.00 per million output tokens; GPT-5.6 Terra costs $2.00 and $12.00. Per solved SWE-bench Verified task, Claude Opus 4.8 costs $2.17 and GPT-5.6 Terra $0.42.

Which has the bigger context window, Claude Opus 4.8 or GPT-5.6 Terra?

GPT-5.6 Terra, with 1.05M tokens against 1M.

How many benchmarks is the Claude Opus 4.8 vs GPT-5.6 Terra comparison based on?

121 benchmarks have a result for both models as of October 23, 2026. Claude Opus 4.8's coding index rests on 6 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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