Data as of November 9, 2026 · How the score is built
GPT-5.6 Terra
Decision readingGPT-5.6 Terra scores 69.4 out of 100 and ranks #16 of 214. This profile shows 42 source-displayable benchmark rows; its strongest eligible category is Multimodal & Grounded at #15. API pricing is $2 input and $12 output per million tokens, with cached input at $0.2.
Released Jul 9, 2026 — see all recent releases
Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Capability
69.4/100
field median 51.1#16 of 214 ranked models
Public
#16of 214
Verified #11 of 77
Price
$2input / $12 output
input median $0.60cached $0.20 · blended $7
Speed
Not measured
field median 92 tok/sTime to first token not measured
Context
1.05Mtokens
field median 256,000Maximum output length is tracked separately
Strongest published evidence
Multimodal & Grounded ranks #15. Particularly strong for screenshots, documents, charts, and grounded multimodal workflows.
Validate before choosing
42 published rows leave some tracked benchmark slots empty. Independent runtime speed has not been measured.
Source-linked · 42 displayable benchmark rows
Category score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #26 of 132Percentile 81stWeight 22%11 benchmarksVerified | 60.4 | 11 benchmarks | Verified | |||
| CodingRank #18 of 158Percentile 89thWeight 20%9 benchmarksVerified | 61.8 | 9 benchmarks | Verified | |||
| ReasoningRank #18 of 157Percentile 89thWeight 17%3 benchmarksVerified | 69.1 | 3 benchmarks | Verified | |||
| MultimodalRank #15 of 67Percentile 79thWeight 12%4 benchmarksVerified | 68.9 | 4 benchmarks | Verified | |||
| KnowledgeRank #20 of 179Percentile 89thWeight 12%8 benchmarksVerified | 68.2 | 8 benchmarks | Verified | |||
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| Inst. FollowingRank #42 of 157Percentile 74thWeight 5%Not listedUnlisted sources | 87.1 | Not listed | Unlisted sources | |||
| MathRank Not rankedWeight 5%3 benchmarksVerified | 86.6 | 3 benchmarks | Verified |
42 of 847 tracked benchmark slots have displayable evidence · bars run 0–100
Coverage detailsHow much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- Agentic11/11 verified
- Coding9/9 verified
- Reasoning3/3 verified
- Multimodal4/4 verified
- Knowledge8/8 verified
- MultilingualNot measured
- Inst. FollowingNot measured
- Math3/3 verified
Capability shape
Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.
GPT-5.6 Terra category percentile values
- Agentic81st percentile
- Coding89th percentile
- Reasoning89th percentile
- Multimodal79th percentile
- Knowledge89th percentile
- MultilingualNot eligible
- Instruction following74th percentile
- MathNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- Agentic#26/132
- Coding#18/158
- Reasoning#18/157
- Multimodal#15/67
- Knowledge#20/179
- MultilingualNot ranked
- Inst. Following#42/157
- MathNot ranked
Benchmark ledger
Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Coding9 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| SWE-bench Pro | Score63.4% | Versus best verified row Best verified: Claude Fable 5.2 · 93% | Gap29.6 behind | Weight26% ref. weight | Provider exact |
| DeepSWE | Score69.6% | Versus best verified row Best verified: Muse Wonder Full · 79.0% | Gap9.4 behind | Weight15% ref. weight | Provider exact |
| CursorBench 3.2 | Score64.9% | Versus best verified row Best verified: Claude Fable 5.1 · 73.4% | Gap8.5 behind | Weight10% ref. weight | Benchmark exact |
| LiveCodeBench (Vals)LiveCodeBench, Vals AI run | Score85.9% | Versus best verified row Best verified: Claude Fable 5.1 · 90.5% | Gap4.6 behind | Weight8% ref. weight | |
| VulcanBench v3 | Score87.0% | Versus best verified row Best verified: Grok 4.5 · 89.9% | Gap2.9 behind | Weight3% ref. weight | Benchmark exact |
| Terminal-Bench 2.1 | Score87.4% | Versus best verified row Best verified: SWE-2 · 92.8% | Gap5.4 behind | WeightScored in Agentic | Provider exact |
| FrontierCode 1.1 Extended | Score55.8% | Versus best verified row Best verified: GPT-6 Astra · 64.5% | Gap8.7 behind | WeightDisplay only | Provider exact |
| SWE-bench (Vals)SWE-bench, Vals AI run | Score95.4% | Versus best verified row Best verified: Claude Opus 5 · 97.0% | Gap1.6 behind | WeightDisplay only | Verified |
| CursorBench 4.0 | Score41.3% | Versus best verified row Best verified: Claude Fable 5.2 · 60.0% | Gap18.7 behind | WeightDisplay only | Benchmark exact |
Agentic11 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Terminal-Bench 2.1 | Score87.4% | Versus best verified row Best verified: SWE-2 · 92.8% | Gap5.4 behind | Weight8% ref. weight | Provider exact |
| BrowseComp | Score87.5% | Versus best verified row Best verified: Atria Dawn Preview · 92.5% | Gap5 behind | Weight8% ref. weight | Provider exact |
| Terminal-Bench 2.1 (Vals)Terminal-Bench 2.1, Vals AI run | Score77.5% | Versus best verified row Best verified: GPT-6 Astra · 87.3% | Gap9.8 behind | Weight4% ref. weight | |
| Terminal-Bench 3.0 | Score20.8% | Versus best verified row Best verified: Claude Opus 5 · 42.7% | Gap21.9 behind | Weight3% ref. weight | Benchmark exact |
| Toolathlon | Score53.1% | Versus best verified row Best verified: Muse Spark 1.1 · 75.6% | Gap22.5 behind | Weight3% ref. weight | Provider exact |
| Terminal-Bench 4.1 | Score21.50% | Versus best verified row Best verified: Claude Opus 5.5 · 65.80% | Gap44.3 behind | WeightDisplay only | Benchmark exact |
| OSWorld 2.0 | Score50.2% | Versus best verified row Best verified: Kimi K3.1 Pro · 79.6% | Gap29.4 behind | WeightDisplay only | Provider exact |
| CyberGym | Score81.8% | Versus best verified row Best verified: MiMo-V2.6-Flash · 95.1% | Gap13.3 behind | WeightDisplay only | Provider exact |
| ExploitGym | Score23.2% | Versus best verified row Best verified: Gemini 4 Carbon · 53.5% | Gap30.3 behind | WeightDisplay only | Provider exact |
| ApprenticeBenchApprenticeBench: end-to-end computer use, continual learning, and long-horizon agency on a real accounts-payable job | Score16% | Versus best verified row Best verified: Claude Fable 5.1 · 72% | Gap56 behind | WeightDisplay only | Benchmark exact |
| MazeBenchMazeBench: visual spatial reasoning in a 3D open world | Score6% | Versus best verified row Best verified: GPT-6 Astra · 23% | Gap17 behind | WeightDisplay only | Benchmark exact |
Reasoning3 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| ARC-AGI-2Abstraction and Reasoning Corpus for AGI v2 | Score83.9% | Versus best verified row Best verified: GPT-6 Astra · 95% | Gap11.1 behind | Weight15% ref. weight | Benchmark exact |
| ARC-AGI-3Abstraction and Reasoning Corpus for AGI v3 | Score0.8% | Versus best verified row Best verified: Claude Fable 5.2 · 65.7% | Gap64.9 behind | Weight15% ref. weight | Benchmark exact |
| ARC-AGI-1ARC-AGI-1 Semi-Private Evaluation | Score96.50% | Versus best verified row Best verified: Claude Fable 5 · 98.50% | Gap2 behind | WeightDisplay only | Benchmark exact |
Multimodal4 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| MMMU-ProMassive Multi-discipline Multimodal Understanding Pro | Score80.7% | Versus best verified row Best verified: GPT-6.1 Terra · 85.5% | Gap4.8 behind | Weight30% ref. weight | Provider exact |
| ParseBenchParseBench: document parsing for AI agents (LlamaIndex leaderboard) | Score67.06% | Versus best verified row Best verified: Claude Opus 5.5 · 78.80% | Gap11.7 behind | Weight7% ref. weight | |
| ExtractBench (LlamaIndex)ExtractBench: schema-guided enterprise document extraction (LlamaIndex leaderboard) | Score92.26% | Versus best verified row Best verified: GPT-6.1 Sol · 95.31% | Gap3 behind | WeightDisplay only | |
| MMMU-Pro w/ PythonMMMU-Pro with Python | Score82% | Versus best verified row Best verified: Kimi K3.1 Pro · 90% | Gap8 behind | WeightDisplay only | Provider exact |
Knowledge8 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| MMLU-Pro (Vals)MMLU-Pro, Vals AI run | Score86.7% | Versus best verified row Best verified: Claude Fable 5.1 · 92.4% | Gap5.7 behind | Weight6% ref. weight | Verified |
| GPQAGraduate-Level Google-Proof Q&A | Score92.9% | Versus best verified row Best verified: GPT-6 Astra · 96% | Gap3.1 behind | Weight3% ref. weight | Provider exact |
| GPQA Diamond (Vals)GPQA Diamond, Vals AI run | Score90.9% | Versus best verified row Best verified: Gemini 3.1 Pro · 95.5% | Gap4.6 behind | Weight2% ref. weight | |
| GPQA-DGPQA Diamond | Score92.9% | Versus best verified row Best verified: GPT-6 Astra · 96.0% | Gap3.1 behind | WeightDisplay only | Provider exact |
| HLE-Verified | Score51.1% | Versus best verified row Best verified: Gemini 3.8 Flash · 54.9% | Gap3.8 behind | WeightDisplay only | Provider exact |
| LABBench2LABBench2: An Improved Benchmark for AI Systems Performing Biology Research | Score81.2% | Versus best verified row Best verified: Gemini 4 Argon · 88.8% | Gap7.6 behind | WeightDisplay only | Provider exact |
| HealthBench Professional | Score57.7% | Versus best verified row Best verified: Claude Sonnet 5.5 · 69.2% | Gap11.5 behind | WeightDisplay only | Provider exact |
| HealthBench Hard | Score32.7% | Versus best verified row Best verified: Muse Spark · 42.8% | Gap10.1 behind | WeightDisplay only | Provider exact |
Math3 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)FrontierMath v2 Tiers 1-3 | Score84.900% | Versus best verified row Best verified: GPT-6 Astra · 93.684% | Gap8.8 behind | WeightWeighted 30% | Provider exact |
| FrontierMath v2 (Tier 4)FrontierMath v2 Tier 4 | Score68.300% | Versus best verified row Best verified: GPT-6.1 Sol · 100.000% | Gap31.7 behind | WeightWeighted 10% | Provider exact |
| FrontierMath (legacy)FrontierMath legacy aggregate | Score84.9% | Versus best verified row Best verified: GPT-5.6 Sol · 89% | Gap4.1 behind | WeightDisplay only | Provider exact |
External signals4 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| ExploitBenchExploitBench v8-bench | Score53% | Versus best verified row Best verified: GPT-6 Astra · 100% | Gap47.1 behind | WeightDisplay only | Provider exact |
| Chess PuzzlesChess Puzzles (Epoch AI) | Score47.0% | Versus best verified row Best verified: Claude Fable 5.2 · 79.0% | Gap32 behind | WeightDisplay only | Benchmark exact |
| Mystery Game PuzzlesMystery Game Puzzles (Epoch AI) | Score35.0% | Versus best verified row Best verified: Claude Fable 5.2 · 90.0% | Gap55 behind | WeightDisplay only | Benchmark exact |
| Furniture AssemblyFurniture Assembly Benchmark (Epoch AI) | Score54.2% | Versus best verified row Best verified: Claude Fable 5.2 · 90.0% | Gap35.8 behind | WeightDisplay only | Benchmark exact |
What it costs to get this score
Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.
GPT-5.6 Terra · 69.4 score · $7 blended per million tokens
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
Horizontal: blended price per million tokens, log scale · Vertical: public score
Published price history
This chart appears only when at least two dated first-party price records exist for the exact model. It shows rate changes, not an inferred cost trend.
2 dated first-party price records. The newest record lists $12 per million tokens.
Lineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- gpt-5.6-terraOpenAI model catalog
- Context window
- 1.05MOpenAI model catalog
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- text, imageOpenAI model catalog
- Output modalities
- textOpenAI model catalog
- Parameters
- Not disclosed by the provider
- Availability
- OpenAI Responses APIOpenAI model catalog
- Cloud regions
- Not tracked yet
- Lifecycle
- activeOpenAI model catalog
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Published at $0.20 per million cached input tokensOpenAI pricing
- Self-host
- Weights are not published
- Rate limits
- Not tracked yet
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
GPT-5.6 Terra ranks #16 of 214 on the public leaderboard with a score of 69.42/100. Its source-verified position is #11 of 77.
GPT-5.6 Terra is a proprietary model with a 1.05M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
GPT-5.6 Terra sits in the GPT-5.6 family with GPT-5.6 Sol, GPT-5.6 Luna, GPT-5.6 Cyber. 42 of 847 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Multimodal & Grounded at #15, while its lowest eligible position is Instruction Following at #42. particularly strong for screenshots, documents, charts, and grounded multimodal workflows.
Last updated November 9, 2026. Runtime fields remain blank until a sourced snapshot exists.
Deployment options
Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.
Where to run GPT-5.6 Terra by API
OpenRouter is the one host we track that publishes a per-token price for it. Prices read from each host’s own pages on October 20, 2026.
| Host | Input /1M | Output /1M | Cached /1M | Context |
|---|---|---|---|---|
| OpenRouter | $2.00 | $12.00 | $0.20 | 1.05M |
Ask your AI, from current BenchLM data
Where does GPT-5.6 Terra rank right now, and what does it cost?
Questions
How does GPT-5.6 Terra perform overall in AI benchmarks?
GPT-5.6 Terra ranks #16 out of 214 models on the public BenchAlign leaderboard, with a score of 69.42/100. Its evidence status is Supported, and this profile shows 42 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is GPT-5.6 Terra good for knowledge and understanding?
GPT-5.6 Terra ranks #20 out of 179 eligible models for knowledge and understanding, with a public category score of 68.2/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is GPT-5.6 Terra good for coding and programming?
GPT-5.6 Terra ranks #18 out of 158 eligible models for coding and programming, with a public category score of 61.8/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is GPT-5.6 Terra good for mathematics?
GPT-5.6 Terra has source-displayable benchmark coverage for mathematics, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is GPT-5.6 Terra good for reasoning and logic?
GPT-5.6 Terra ranks #18 out of 157 eligible models for reasoning and logic, with a public category score of 69.1/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is GPT-5.6 Terra good for agentic tool use and computer tasks?
GPT-5.6 Terra ranks #26 out of 132 eligible models for agentic tool use and computer tasks, with a public category score of 60.4/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is GPT-5.6 Terra good for multimodal and grounded tasks?
GPT-5.6 Terra ranks #15 out of 67 eligible models for multimodal and grounded tasks, with a public category score of 68.9/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Which sibling models are related to GPT-5.6 Terra?
GPT-5.6 Terra belongs to the GPT-5.6 family. Related tracked variants include GPT-5.6 Sol, GPT-5.6 Luna, GPT-5.6 Cyber. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.
Does GPT-5.6 Terra have full benchmark coverage on BenchLM?
No. GPT-5.6 Terra currently has 63 source-displayable rows. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of GPT-5.6 Terra?
GPT-5.6 Terra has a documented context window of 1.05M. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.