BenchLeader

GPT-6 Astra

Reasoning effort

GPT-6 Astra is an OpenAI proprietary reasoning model, released 2 Sept 2026. Its best configuration (max reasoning effort) ranks #4 of 775 on the BenchLeader Index at 70.6 ±3.7, in the top ten. The ± is the point: 41 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 (89) and lowest in agents & tools (65). At $20.00 per million tokens blended it is among the most expensive ranked models. Output speed of 64 tokens per second puts it slower than most, with a first answer in 328.5 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 19 Oct 2026.

Blended price
$20.00/M
$10.00 in · $50.00 out
Output speed
64 tok/s
measured by Artificial Analysis
First answer
328 s
first token 4.00 s
Context
1.1M
Full answer
336 s
median, reasoning included
Cost per run
$3.26
one full Intelligence Index run
Released
2 Sept 2026
How it scores by categoryDashed line = average model (50). One step of 15 = one standard deviation.
  1. Overall index71
  2. Reasoning76
  3. Coding74
  4. Agents & tools65
  5. Maths72
  6. Knowledge79
  7. Human preference67
  8. Multimodal66
  9. Long context65
  10. Composite89

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 reasoning59.0#14039 tok/s4.00 s$0.019Coding 59 · Maths 70 · Reasoning 65
low66.0#3554 tok/s2.40 s$0.019Agents & tools 58 · Coding 60 · Composite 81 · Knowledge 80 · Long context 65 · Maths 72 · Multimodal 68 · Reasoning 76
medium67.6#2252 tok/s4.30 s$0.019Agents & tools 62 · Coding 60 · Composite 85 · Knowledge 81 · Long context 65 · Maths 77 · Multimodal 68 · Reasoning 79
high69.7#855 tok/s64 s$0.019Agents & tools 65 · Coding 70 · Composite 87 · Knowledge 81 · Long context 65 · Maths 77 · Multimodal 70 · Reasoning 79
xhigh69.0#1459 tok/s159 s$0.019Agents & tools 67 · Coding 62 · Composite 88 · Knowledge 81 · Long context 65 · Maths 77 · Multimodal 70 · Reasoning 80
maxbest70.6#464 tok/s328 s$0.019Agents & tools 65 · Coding 74 · Composite 89 · Human preference 67 · Knowledge 79 · Long context 65 · Maths 72 · Multimodal 66 · Reasoning 76
not stated67.9#1939 tok/s4.00 s$0.019Agents & tools 71 · Coding 83 · Composite 70 · Knowledge 56 · Maths 78 · Reasoning 86

What more thinking costs

Turning the effort up buys index points and multiplies the bill. Here max costs 4.0× low for +4.6 on the index — 2.3 points per doubling of spend. Compare that with other models.

low $0.818max $3.26

How its index has moved

8 Sept 2026 to 21 Oct 2026
616876
  • max
  • high
  • xhigh
  • not stated

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 Diamond–––––95.8%#2–Epoch AI Benchmarking Hub
Humanity's Last Exameffort not stated––––––54.8%#1Scale AI / CAIS
Arena Hard Prompts–––––1502#30–Arena (LMArena)
LiveBench 2.0 Reasoningnot in indexeffort not stated––––––92.7%#2LiveBench
LiveBench 1.0 Reasoningnot in index–––––92.7%#1–LiveBench
GPQA Diamond (AA)not in index–93.1%#2493.9%#1095.0%#496.3%#196.1%#2–Artificial Analysis
Humanity's Last Exam (AA)not in index–49.2%#2952.7%#2053.1%#1754.6%#1354.7%#12–Artificial Analysis
ARC-AGI-186.0%#9996.5%#2397.5%#1298.5%#198.5%#197.5%#12–ARC Prize
ARC-AGI-259.6%#8585.4%#2892.1%#792.1%#793.3%#395.0%#1–ARC Prize
ARC-AGI-396.7%#998.0%#598.4%#399.9%#198.4%#398.6%#2–ARC Prize
CritPt–26.3%#3829.1%#2028.9%#2331.4%#831.7%#3–Artificial Analysis
MysteryMechanismnot in index–––––53.1%#1–Vals AI
Chess Puzzlesnot in index–––––74.0%#2–Epoch AI Benchmarking Hub
Mystery Game Puzzlesnot in index–––––84.0%#1–Epoch AI Benchmarking Hub
LMCAnot in index–62.2%#2962.9%#2363.8%#1864.4%#16–64.1%#17Epoch AI Benchmarking Hub
DTBenchnot in index–94.9%#4697.1%#1796.5%#2297.3%#9–97.1%#17Epoch AI Benchmarking Hub
BTF-3not in index–13.5%#9–––––Epoch AI Benchmarking Hub

Coding

Benchmarkno reasoninglowmediumhighxhighmaxnot statedSourceTrend
SciCode53.5%#7554.0%#6754.2%#6455.4%#4855.7%#4556.5%#37–SciCode
WeirdML–––92.9%#4–93.3%#2–WeirdML
FrontierCode–––––53.3%#4–Cognition
GSO-Bencheffort not stated––––––79.4%#2GSO-Bench
Arena Coding–––––1543#9–Arena (LMArena)
Arena WebDev–––––1774#2–Arena (LMArena)
LiveBench 2.0 Codingnot in indexeffort not stated––––––93.7%#8LiveBench
LiveBench 1.0 Codingnot in index–––––80.4%#20–LiveBench
SciCode (AA)not in index–54.0%#6854.2%#6555.4%#5055.7%#4656.5%#36–Artificial Analysis
IOI–––––100.0%#1–Vals AI
Code Migrationnot in index–––––67.7%#3–Vals AI
ProgramBenchnot in index–––––5.5%#4–Vals AI
Vibe Code Bench 1-100not in index–––––27.6%#5–Vals AI
Vibe Code Bench v1.1not in index–––––89.6%#7–Vals AI
SWE Atlas: Codebase QnAnot in index––––59.1%#3––Scale AI SEAL
SWE Atlas: Refactoringnot in index––––59.0%#1––Scale AI SEAL
SWE Atlas: Test Writingnot in index––––50.7%#5––Scale AI SEAL
MirrorCodenot in index–––46.7%#4–––Epoch AI Benchmarking Hub
DeepSWE v1.1not in index–67.0%#2272.8%#873.2%#474.1%#173.2%#4–Epoch AI Benchmarking Hub
ALE-Benchnot in index–––––2951.3#1–Epoch AI Benchmarking Hub
FrontierSWEnot in index–––––65.5%#1–Epoch AI Benchmarking Hub
Terminal-Bench 4.0 (AA)not in index–41.9%#2849.5%#1954.0%#1259.6%#259.1%#5–Artificial Analysis
Terminal-Bench 2.1 (AA)not in index–88.0%#1289.5%#589.9%#389.1%#788.4%#10–Artificial Analysis
Startrise Frontendnot in indexeffort not stated––––––79.9%#3Startrise
FrontierCode 1.1 (AA)not in index–––––47.0%#7–Artificial Analysis

Agents & tools

Benchmarklowmediumhighxhighmaxnot statedSourceTrend
Terminal-Bench50.6%#3254.2%#2657.9%#1957.9%#1958.2%#17–Terminal-Bench
Remote Labor Indexeffort not stated–––––20.8%#2Scale AI / CAIS
APEX-Agentseffort not stated–––––64.7%#8Mercor
Arena Agent––––15.1#2–Arena (LMArena)
LiveBench Long Agenticnot in indexeffort not stated–––––82.4%#2LiveBench
LiveBench Browsernot in indexeffort not stated–––––84.0%#10LiveBench
LiveBench Agentic Codingnot in index––––57.3%#21–LiveBench
Terminal-Bench 2.1 (Vals)––––87.3%#2–Vals AI
HiL-Bencheffort not stated–––––65.3%#3Scale AI SEAL
GDPval-AA v2.1not in index44.5%#7849.3%#5351.1%#4752.8%#4153.6%#39–Artificial Analysis
τ³-Banking (AA)32.0%#6035.5%#4640.0%#3043.1%#2141.4%#26–Artificial Analysis
ITBench SRE (AA)not in index––––48.6%#8–Artificial Analysis
Analyst Agent (AA)not in index––––51.3%#9–Artificial Analysis
CUA-benchnot in index––––19.2%#1–Vals AI
CyberBenchnot in index––––41.1%#42–Vals AI
Finance Agent v2not in index––––53.5%#32–Vals AI
Harvey's Legal Agent Benchmarknot in index––––7.1%#17–Vals AI
Legal Research Benchnot in index––––39.4%#31–Vals AI
SREBenchnot in index––––56.9%#1–Vals AI
Tax Agent Benchnot in index––––20.7%#44–Vals AI
Terminal-Bench 4.0 (Vals)not in index––––59.6%#3–Vals AI
Terminal-Bench Sciencenot in index––––62.9%#1–Vals AI
Time Horizon Index: KSPnot in index––––90.5%#2–Vals AI
Arena Searchnot in index––––1246#3–Arena (LMArena)
BALROGnot in index––––68.3%#1–BALROG
Vending-Bench 2not in indexeffort not stated–––––15514.7#1Andon Labs
AutomationBenchnot in index59.1%#4164.6%#1966.6%#1367.2%#968.5%#7–Artificial Analysis
GDP.pdf (AA)not in index30.4%#930.4%#931.0%#532.2%#231.0%#5–Artificial Analysis
Harvey LAB-AA v1.1not in index––––8.6%#5–Harvey
AA-Briefcase v1.1not in index–1461#361506#291547#221569#19–Artificial Analysis
Terminal-Bench-Science 0.1 (AA)not in index––––63.3%#1–Artificial Analysis
CWE-Bench (AA)––––63.3%#4–Artificial Analysis
DeepSec-Bench (AA)––––36.9%#2–Artificial Analysis
CyberGym end-to-end (AA)––––0.0%#16–Artificial Analysis
FACTS Searchnot in indexeffort not stated–––––89.9%#1Google

Maths

Benchmarkno reasoninglowmediumhighxhighmaxnot statedSourceTrend
FrontierMath Tiers 1–3–––––93.7%#1–Epoch AI Benchmarking Hub
FrontierMath Tier 482.9%#1187.8%#997.6%#597.6%#297.6%#297.6%#2–Epoch AI Benchmarking Hub
OTIS Mock AIME–––––100.0%#1–Epoch AI Benchmarking Hub
ProofBencheffort not stated––––––99.0%#4Vals AI
LiveBench Mathematicsnot in index–––––96.8%#4–LiveBench
Arena Maths–––––1486#31–Arena (LMArena)

Knowledge

Benchmarklowmediumhighxhighmaxnot statedSourceTrend
SimpleQA Verified––––75.6%#2–Epoch AI Benchmarking Hub
LiveBench 2.0 Data Analysisnot in indexeffort not stated–––––83.0%#2LiveBench
LiveBench Researchnot in indexeffort not stated–––––85.2%#7LiveBench
LiveBench 1.0 Data Analysisnot in index––––83.0%#1–LiveBench
AA-Omniscience40.5#1642.2#1043.7#243.4#443.4#5–Artificial Analysis
PRBench Financeeffort not stated–––––47.5%#16Scale AI SEAL
PRBench Legaleffort not stated–––––48.4%#17Scale AI SEAL
BioMysteryBenchnot in index––––79.3%#3–Vals AI
Excel Modeling Benchmarknot in index––––71.7%#10–Vals AI
MedCodenot in index––––48.5%#29–Vals AI
MedScribenot in index––––87.9%#16–Vals AI
DrugDiscoveryBenchnot in index––––68.7%#1–Scale AI SEAL
EBR-benchnot in index––––76.2%#1–Epoch AI Benchmarking Hub
GDP.pdfnot in index––––34.2%#2–Epoch AI Benchmarking Hub
AA-Omniscience: accuracynot in index59.5%#2160.6%#1861.1%#1461.9%#1362.6%#11–Artificial Analysis
AA-Omniscience: non-hallucinationnot in index53.1%#10453.5%#10355.2%#9651.7%#10848.7%#123–Artificial Analysis

Instruction following

BenchmarkmaxSourceTrend
LiveBench Languagenot in index89.4%#4LiveBench
LiveBench Instruction Followingnot in index75.6%#8LiveBench
Arena Instruction Followingnot in index1473#30Arena (LMArena)

Human preference

BenchmarkmaxSourceTrend
Arena Text1477#30Arena (LMArena)
Arena Creative Writingnot in index1450#38Arena (LMArena)
Arena Multi-turnnot in index1486#30Arena (LMArena)
Arena Longer Queriesnot in index1489#30Arena (LMArena)

Multimodal

Benchmarklowmediumhighxhighmaxnot statedSourceTrend
Arena Vision––––1280#36–Arena (LMArena)
LiveBench Designnot in indexeffort not stated–––––82.0%#11LiveBench
MMMU-Pro84.6%#1885.1%#1186.4%#486.2%#586.9%#2–Artificial Analysis
SAGEnot in index––––46.4%#36–Vals AI
Blueprint-Bench 2not in indexeffort not stated–––––49.7%#3Epoch AI Benchmarking Hub
AA-3Dnot in index––––1166#3–Artificial Analysis

Long context

BenchmarklowmediumhighxhighmaxSourceTrend
AA-LCR80.0%#7779.7%#8780.0%#7780.0%#7780.7%#64Artificial Analysis
Arena Documentnot in index––––1473#17Arena (LMArena)
MLCRnot in index––––35.0%#17Artificial Analysis

Composite

Benchmarklowmediumhighxhighmaxnot statedSourceTrend
Epoch Capabilities Indexnot in indexeffort not stated–––––168.8#2Epoch AI Benchmarking Hub
LiveBench 2.0effort not stated–––––86.1%#3LiveBench
LiveBench 1.0not in index––––82.2%#4–LiveBench
AA Intelligence Index v4.3.245.8#3449.6#2250.9#1752.4#1052.7#8–Artificial Analysis
Vals Indexnot in index––––65.0#5–Vals AI
AA Cyber Indexnot in index––––33.4#12–Artificial Analysis

Where it wins

Benchmarks where this configuration ranks in the top five of every configuration measured.

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
OpenAI121 tok/s3.40 s$60.00$300.001.1M–
OpenAI72 tok/s3.19 s$20.00$100.001.1M–
OpenAI46 tok/s2.68 s$5.00$25.001.1M–
Azure41 tok/s9.34 s$11.00$55.001.1M–
OpenAI38 tok/s5.59 s$10.00$50.001.1M–
Azure36 tok/s7.38 s$10.00$50.001.1M–

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 $1.00 per 1M. Reasoning tokens are not modelled.

WorkloadTokens in / outCostWith cachingTime
Chat reply400 / 300$0.019$0.0165.6 min
Summarize a 30-page report12,000 / 600$0.150$0.0695.6 min
Code edit6,000 / 1,500$0.135$0.0955.9 min
Agentic coding session60,000 / 4,000$0.800$0.3956.5 min
Structured extraction2,000 / 200$0.030$0.0175.5 min

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See also

Data as of 21 Oct 2026. Compare these configurations.

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