BenchLeader

GPT-5.6 Terra

Reasoning effort

GPT-5.6 Terra is an OpenAI proprietary reasoning model, released 9 Jul 2026. Its best configuration (max reasoning effort) ranks #51 of 775 on the BenchLeader Index at 64.4 ±5.0, in the upper half. The ± is the point: 141 other configurations score within that range, so they and this one cannot be told apart on quality alone — price and speed are what separate them. It scores highest in composite (77) and lowest in knowledge (57). At $4.50 per million tokens blended it is among the most expensive ranked models. Output speed of 133 tokens per second puts it faster than most, with a first answer in 128.5 s. It has been measured at 7 reasoning-effort settings; this summary describes the best-scoring one, and the tabs above switch between them. Last measured 14 Oct 2026.

Blended price
$4.50/M
$2.00 in · $12.00 out
Output speed
133 tok/s
measured by Artificial Analysis
First answer
128 s
first token 1.83 s
Context
1.1M
Full answer
132 s
median, reasoning included
Cost per run
$1.40
one full Intelligence Index run
Released
9 Jul 2026
How it scores by categoryDashed line = average model (50). One step of 15 = one standard deviation.
  1. Overall index64
  2. Reasoning70
  3. Coding65
  4. Agents & tools59
  5. Maths69
  6. Knowledge57
  7. Instruction following70
  8. Multimodal64
  9. Long context67
  10. Composite77

Reasoning-effort configurations

The same model behaves differently depending on how much it is allowed to think. Each row is one setting, scored only on the benchmarks that were run at that setting. “Not stated” collects results from publishers that did not say which setting they used; for a reasoning model that is usually its thinking mode, but we do not assume it. Pick a setting here or at the top of the page to see its price, speed and category scores.

EffortIndexRankSpeedFirst answerChat reply costCategories
no reasoning49.6#385120 tok/s0.76 s$0.0044Agents & tools 44 · Coding 47 · Composite 53 · Knowledge 51 · Long context 54 · Maths 47 · Multimodal 50 · Reasoning 50
low56.5#200117 tok/s1.52 s$0.0044Agents & tools 55 · Coding 54 · Composite 60 · Instruction following 60 · Knowledge 58 · Long context 61 · Maths 62 · Multimodal 59 · Reasoning 51
medium57.0#189121 tok/s1.55 s$0.0044Agents & tools 54 · Coding 55 · Composite 63 · Instruction following 62 · Knowledge 59 · Long context 62 · Multimodal 60 · Reasoning 56
high61.4#97120 tok/s2.52 s$0.0044Agents & tools 66 · Coding 63 · Composite 68 · Instruction following 64 · Knowledge 60 · Long context 64 · Multimodal 62 · Reasoning 65
xhigh62.8#78123 tok/s17 s$0.0044Agents & tools 64 · Coding 60 · Composite 72 · Human preference 66 · Instruction following 66 · Knowledge 60 · Long context 65 · Maths 66 · Multimodal 62 · Reasoning 64
maxbest64.4#51133 tok/s128 s$0.0044Agents & tools 59 · Coding 65 · Composite 77 · Instruction following 70 · Knowledge 57 · Long context 67 · Maths 69 · Multimodal 64 · Reasoning 70
not stated52.6#30969 tok/s1.83 s$0.0044Coding 55 · Composite 58 · Human preference 55 · Reasoning 49

What more thinking costs

Turning the effort up buys index points and multiplies the bill. Here max costs 10× no reasoning for +14.8 on the index — 4.5 points per doubling of spend. Compare that with other models.

no reasoning $0.140max $1.40

How its index has moved

8 Sept 2026 to 20 Oct 2026
526170
  • max
  • xhigh
  • high
  • medium

The index is recomputed from scratch every day, so a line moves when a new benchmark result lands, when a publisher revises a score, or when the models it is normalised against change. Early movement usually means the score is still settling.

Benchmark results

See all LLM benchmarks. One column per reasoning effort. Rank is among every configuration of every model on that benchmark. Hover a score for the run it came from.

Reasoning

Benchmarkno reasoninglowmediumhighxhighmaxnot statedSourceTrend
GPQA Diamond77.3%#13587.4%#72–––93.3%#18–Epoch AI Benchmarking Hub
SimpleBench––––48.9%#45–48.9%#45SimpleBench
Arena Hard Prompts––––1489#49––Arena (LMArena)
LiveBench 2.0 Reasoningnot in indexeffort not stated––––––90.6%#11LiveBench
LiveBench 1.0 Reasoningnot in index–––––90.6%#11–LiveBench
GPQA Diamond (AA)not in index74.7%#25584.3%#14187.2%#10089.6%#7190.8%#5592.5%#35–Artificial Analysis
Humanity's Last Exam (AA)not in index11.4%#29029.2%#15533.3%#13638.5%#9741.9%#7542.9%#61–Artificial Analysis
GPQA Diamond (Vals)not in index––––90.9%#24––Vals AI
Kagi LLM Benchmarkeffort not stated––––––51.3%#82Kagi LLM Benchmark
ARC-AGI-1–60.2%#15077.0%#11892.0%#5694.0%#4396.5%#23–ARC Prize
ARC-AGI-2–18.8%#13537.5%#11567.1%#6474.2%#4883.9%#35–ARC Prize
ARC-AGI-3–0.0%#630.1%#600.5%#420.7%#400.8%#38–ARC Prize
CritPt2.0%#1979.4%#12217.4%#7822.9%#5227.1%#3330.0%#16–Artificial Analysis
Chess Puzzlesnot in index5.0%#13127.0%#71–––47.0%#24–Epoch AI Benchmarking Hub
Mystery Game Puzzlesnot in index14.0%#9619.0%#6310.0%#111––35.0%#22–Epoch AI Benchmarking Hub
LMCAnot in index46.5%#8349.3%#7049.6%#6851.4%#5952.2%#5555.0%#46–Epoch AI Benchmarking Hub
DTBenchnot in index78.7%#13890.1%#8290.1%#8291.2%#7392.5%#6893.3%#64–Epoch AI Benchmarking Hub

Coding

Benchmarkno reasoninglowmediumhighxhighmaxnot statedSourceTrend
SciCode45.1%#13949.9%#11150.5%#10352.4%#8652.3%#8755.0%#52–SciCode
WeirdML–––78.3%#20–––WeirdML
FrontierCodeeffort not stated––––––41.3%#24Cognition
Arena Coding––––1517#43––Arena (LMArena)
Arena WebDev––––1522#51––Arena (LMArena)
LiveBench 2.0 Codingnot in indexeffort not stated––––––86.2%#19LiveBench
LiveBench 1.0 Codingnot in index–––––78.3%#31–LiveBench
SciCode (AA)not in index45.1%#14349.9%#11150.5%#10352.4%#8552.3%#8655.0%#54–Artificial Analysis
LiveCodeBench––––85.9%#25––Vals AI
IOI–––––87.6%#7–Vals AI
SWE-bench (Vals)not in index–––––95.4%#5–Vals AI
Code Migrationnot in index–––––47.8%#13–Vals AI
ProgramBenchnot in index–––––0.5%#18–Vals AI
Vibe Code Bench 1-100not in index–––––14.8%#18–Vals AI
Vibe Code Bench v1.1not in index–––––74.6%#36–Vals AI
Surface Evolver Benchnot in index––––83.8%#7––Epoch AI Benchmarking Hub
DeepSWE v1.1not in index–24.1%#6635.1%#6153.8%#4260.2%#3269.6%#14–Epoch AI Benchmarking Hub
CursorBenchnot in index–25.2%#7327.6%#7130.7%#6633.6%#5441.3%#37–Cursor
ALE-Benchnot in index–––––1951.4#10–Epoch AI Benchmarking Hub
Terminal-Bench 4.0 (AA)not in index0.5%#1361.5%#1191.0%#1251.5%#11910.1%#8735.4%#33–Artificial Analysis
Terminal-Bench 2.1 (AA)not in index56.2%#10362.5%#8872.3%#6975.7%#6180.2%#4488.0%#12–Artificial Analysis
Startrise Frontendnot in indexeffort not stated––––––66.9%#22Startrise

Agents & tools

Benchmarkno reasoninglowmediumhighxhighmaxnot statedSourceTrend
Terminal-Bench–––––21.5%#70–Terminal-Bench
APEX-Agents–––––58.2%#15–Mercor
Arena Agent––––0.3#28––Arena (LMArena)
LiveBench Long Agenticnot in indexeffort not stated––––––48.4%#15LiveBench
LiveBench Browsernot in indexeffort not stated––––––84.0%#10LiveBench
LiveBench Agentic Codingnot in index–––––55.0%#30–LiveBench
Terminal-Bench Hard–43.9%#37–57.6%#1162.9%#257.6%#11–Artificial Analysis
τ²-Bench Telecom (AA)not in index–60.5%#17772.8%#14678.4%#12980.4%#12286.3%#87–Artificial Analysis
Terminal-Bench 2.1 (Vals)–––––77.5%#14–Vals AI
GDPval-AA v2.1not in index29.9%#14430.4%#13938.3%#10643.8%#8147.4%#6447.6%#61–Artificial Analysis
τ³-Banking (AA)15.7%#11218.8%#10025.6%#7828.7%#7029.7%#6740.2%#29–Artificial Analysis
ITBench SRE (AA)not in index–––––51.0%#5–Artificial Analysis
APEX-Agents (AA)not in index–––––38.9%#4–Artificial Analysis
CyberBenchnot in index–––––72.1%#17–Vals AI
Finance Agent v2not in index–––––54.4%#26–Vals AI
Legal Research Benchnot in index–––––41.4%#25–Vals AI
SkillsBenchnot in index–––––58.9%#11–Vals AI
SREBenchnot in index–––––9.5%#14–Vals AI
Tax Agent Benchnot in index–––––30.0%#27–Vals AI
Terminal-Bench 4.0 (Vals)not in index–––––22.7%#26–Vals AI
Terminal-Bench Sciencenot in index–––––10.0%#15–Vals AI
BALROGnot in index–––––53.2%#6–BALROG
Vending-Bench 2not in indexeffort not stated––––––7343.2#16Andon Labs
AutomationBenchnot in index12.5%#14729.1%#11533.5%#11242.0%#9347.1%#8759.6%#38–Artificial Analysis
GDP.pdf (AA)not in index11.2%#11717.6%#7917.0%#8620.8%#5824.6%#3124.0%#37–Artificial Analysis
EnterpriseOps-Gymnot in index–––––38.5%#31–Artificial Analysis
Terminal-Bench-Science 0.1 (AA)not in index–––––13.8%#21–Artificial Analysis
FACTS Searchnot in indexeffort not stated––––––81.7%#9Google

Maths

Benchmarkno reasoninglowxhighmaxSourceTrend
FrontierMath Tiers 1–3–––86.0%#10Epoch AI Benchmarking Hub
FrontierMath Tier 4–––70.7%#20Epoch AI Benchmarking Hub
OTIS Mock AIME53.3%#17788.9%#75–99.7%#13Epoch AI Benchmarking Hub
ProofBench––74.0%#15–Vals AI
LiveBench Mathematicsnot in index–––94.9%#18LiveBench
Arena Maths––1480#36–Arena (LMArena)

Knowledge

Benchmarkno reasoninglowmediumhighxhighmaxnot statedSourceTrend
SimpleQA Verified–––––43.2%#41–Epoch AI Benchmarking Hub
LiveBench 2.0 Data Analysisnot in indexeffort not stated––––––79.3%#14LiveBench
LiveBench Researchnot in indexeffort not stated––––––60.4%#39LiveBench
LiveBench 1.0 Data Analysisnot in index–––––79.3%#15–LiveBench
AA-Omniscience-23.2#254-6.8#171-5.1#163-3.5#151-3.0#1500.1#136–Artificial Analysis
MMLU-Pro––––86.7%#39––Vals AI
LegalBench–––––85.1%#25–Vals AI
CorpFin––––65.3%#29––Vals AI
TaxEval––––76.2%#6––Vals AI
Excel Modeling Benchmarknot in index–––––66.2%#22–Vals AI
MedCodenot in index––––43.4%#45––Vals AI
MedScribenot in index––––82.9%#48––Vals AI
Public Benefits Benchnot in index–––––62.4%#27–Vals AI
GDP.pdfnot in index––24.7%#17–––24.7%#17Epoch AI Benchmarking Hub
AA-Omniscience: accuracynot in index36.8%#14443.7%#9644.6%#9245.5%#8845.5%#8746.8%#78–Artificial Analysis
AA-Omniscience: non-hallucinationnot in index5.0%#52010.1%#41510.2%#40910.2%#41111.0%#39612.1%#379–Artificial Analysis

Instruction following

BenchmarklowmediumhighxhighmaxSourceTrend
LiveBench Languagenot in index––––82.9%#22LiveBench
LiveBench Instruction Followingnot in index––––64.6%#46LiveBench
IFBench59.7%#12662.2%#11864.4%#10766.3%#9771.2%#58Artificial Analysis
Arena Instruction Followingnot in index–––1464#47–Arena (LMArena)

Human preference

Benchmarkxhighnot statedSourceTrend
Arena Text1466#51–Arena (LMArena)
EQ-Bench 4effort not stated–1234#11EQ-Bench
Arena Creative Writingnot in index1429#73–Arena (LMArena)
Arena Multi-turnnot in index1471#57–Arena (LMArena)
Arena Longer Queriesnot in index1468#62–Arena (LMArena)

Multimodal

Benchmarkno reasoninglowmediumhighxhighmaxnot statedSourceTrend
Arena Vision––––1271#43––Arena (LMArena)
LiveBench Designnot in indexeffort not stated––––––76.0%#25LiveBench
MMMU-Pro66.7%#16876.1%#9276.8%#8579.1%#6379.5%#5980.7%#43–Artificial Analysis
MMMU-Pro (Vals)not in index–––––86.5%#20–Vals AI
MortgageTaxnot in index––––67.3%#26––Vals AI
SAGEnot in index–––––47.0%#33–Vals AI
Blueprint-Bench 2not in indexeffort not stated––––––30.8%#17Epoch AI Benchmarking Hub

Long context

Benchmarkno reasoninglowmediumhighxhighmaxSourceTrend
AA-LCR58.7%#28471.3%#20074.0%#16577.7%#12779.0%#10583.0%#25Artificial Analysis
Arena Documentnot in index––––1477#14–Arena (LMArena)
MLCRnot in index–8.9%#6512.2%#5412.2%#5421.7%#2531.7%#19Artificial Analysis

Composite

Benchmarkno reasoninglowmediumhighxhighmaxnot statedSourceTrend
Epoch Capabilities Indexnot in indexeffort not stated––––––160.1#13Epoch AI Benchmarking Hub
LiveBench 2.0effort not stated––––––75.0%#16LiveBench
LiveBench 1.0not in index–––––77.9%#21–LiveBench
AA Intelligence Index v4.3.220.8#21927.5#14130.1#12134.2#9638.0#7942.1#53–Artificial Analysis
Vals Multimodal Indexnot in index––––65.1%#14––Vals AI

Where to run it

Every provider serving this model through OpenRouter, with throughput and first-token latency measured on live traffic over the last 30 minutes and each provider’s own price. Purple marks the best in each column.

ProviderSpeedFirst tokenInput $/MOutput $/MContextQuantisation
OpenAI87 tok/s1.96 s$1.00$6.001.1M–
Amazon Bedrock84 tok/s3.27 s$2.20$13.201.1M–
OpenAI83 tok/s1.04 s$4.00$24.001.1M–
OpenAI69 tok/s1.82 s$2.00$12.001.1M–
Azure42 tok/s2.57 s$2.00$12.001.1M–

Price history

Listed price per 1M tokens over time, as recorded by OpenRouter for the provider with the longest history.

$0.00$4.13$8.25$12.38$16.50Jul 26Aug 26Sept 26Oct 26
input outputnow $2.00 in · $12.00 out

What a task costs

Estimates from list price, output speed and time to first answer for the best configuration. “With caching” assumes three-quarters of the input is served from the prompt cache at $0.200 per 1M. Reasoning tokens are not modelled.

WorkloadTokens in / outCostWith cachingTime
Chat reply400 / 300$0.0044$0.00392.2 min
Summarize a 30-page report12,000 / 600$0.031$0.0152.2 min
Code edit6,000 / 1,500$0.030$0.0222.3 min
Agentic coding session60,000 / 4,000$0.168$0.0872.6 min
Structured extraction2,000 / 200$0.0064$0.00372.2 min

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See also

Data as of 21 Oct 2026. Compare these configurations.

Cite as: BenchLeader, “GPT-5.6 Terra: benchmarks, pricing, speed and rank”, https://www.benchleader.com/models/gpt-5-6-terra, data as of 21 Oct 2026.