30+ Shocking GPT 6 Astra Usage Statistics

• GPT 6 Astra scores 99.9% on ARC AGI 3, compared with 7.8% for GPT 5.6 Sol.
• Astra reaches 100% on ExploitBench, compared with 78.5% for GPT 5.6 Sol.
• On Terminal Bench 4.0, Astra scores 57.9%, compared with 37.3% for GPT 5.6 Sol.
• Astra achieves 97.6% on FrontierMath Tier 4, compared with 83% for GPT 5.6 Sol.
• GPT 6 Astra reaches 96.3% on the 512K to 1M long context test, compared with 73.8% for GPT 5.6 Sol.
• Astra completes OSWorld 2.0 tasks in about 40 minutes, compared with roughly 75 minutes for GPT 5.6 Sol.
• GPT 6 Astra Max processes up to 65 tokens per second, while its Low setting records 2.59 seconds for the first answer token.
• Astra's internal hallucination benchmark result is 4.2%, compared with 12.2% for GPT 5.6 Sol.
• GPT 6 Astra has a 1 million token context window and was trained on more than 10 trillion text tokens, along with large image, audio, and video datasets.
• Astra costs $10 per million input tokens and $50 per million output tokens, while its estimated Terminal Bench task cost was about 9% lower than GPT 5.6 Sol.

GPT 6 Astra supports text and image input and produces text output, with a 1 million token context window that Artificial Analysis estimates at roughly 1,500 pages of 12-point Arial text.

The model has five reasoning levels: low, medium, high, xhigh, and Max. Its Intelligence Index score ranges from 46 at the Low setting to 53 at Max.

OpenAI's supplied data also says Astra is designed for longer tasks, computer use, coding, scientific work, cybersecurity, and professional workflows.

GPT 6 Astra scores 57.9% on Terminal Bench 4.0 compared with 37.3% for GPT 5.6 Sol, a difference of 20.6 percentage points.

The gap varies considerably by task. Astra shows larger differences on some reasoning, cybersecurity, coding, and long-context tests, while other benchmarks show smaller differences.

Another study revealed GPT 6 Astra scored 98% in advanced mathematics on FrontierMath Tier 4, compared with 83% for GPT 5.6 Sol.

GPT 6 Astra's largest reported gap is on ARC AGI 3, where it scores 99.9% compared with 7.8% for GPT 5.6 Sol, a difference of 92.1 percentage points.

Other large differences include SRE Bench, long context, ExploitBench, Terminal Bench 4.0, FrontierMath Tier 4, and BenchCAD.

GPT 6 Astra scores 57.9% on Terminal Bench 4.0 compared with 37.3% for GPT 5.6 Sol.

The coding results show that the size of the improvement depends on the task. Astra scores 63.9% on internal database migration tasks compared with 42.7% for GPT 5.6 Sol. DeepSWE v1.1 shows a much smaller gap at 74.1% versus 72.7%.

A report says Astra's estimated API cost per Terminal Bench task was about 9% lower than GPT 5.6 Sol.

GPT 6 Astra scores 97.6% on FrontierMath Tier 4 compared with 83.0% for GPT 5.6 Sol, while Terminal Bench Science reports 64.6% for Astra compared with 22.4% for GPT 5.6 Sol.

The science and healthcare benchmarks show smaller differences in some areas.

Astra scores 96.0% on GPQA Diamond compared with 94.6% for GPT 5.6 Sol.

On Terminal Bench Science, Astra scores 64.6% compared with 52.6% for Claude Fable 5.1. Astra's estimated API cost is about 31% lower.

GPT 6 Astra scores 100% on ExploitBench compared with 78.5% for GPT 5.6 Sol.

The June to August 2026 ExploitBench results show GPT 6 Astra scored 39% compared to 5.50% for GPT 5.6 Sol.

GPT 6 Astra scores 95.9% on BenchCAD compared with 83.3% for GPT 5.6 Sol, a 12.6 percentage-point difference on the professional CAD benchmark.

Astra also scores 91.5% on BrowseComp compared with 90.4% for GPT 5.6 Sol, while its AutomationBench score is 41.4% compared with 18.1%.

For internal tasks, Astra scores 50.0% on design tasks and 40.9% on data science tasks, compared with 47.4% and 30.5% for GPT 5.6 Sol. OpenScore String Quartets gives Astra a score of 0.84 compared with 0.19. 

GPT 6 Astra scores 72.6% on OSWorld 2.0 compared with 65.7% for GPT 5.6 Sol.

OpenAI also reports that Astra completed OSWorld 2.0 tasks in about 40 minutes compared with about 75 minutes for GPT 5.6 Sol, which is about 47% less time per task.

The computer use data also includes the computer use safety evaluations covered separately below.

GPT 6 Astra scores 96.3% at 512K to 1M tokens compared with 73.8% for GPT 5.6 Sol.

At 256K to 512K tokens, Astra scores 100% compared with 91.5% for GPT 5.6 Sol.

Astra's 1 million token context window is equivalent to roughly 1,500 pages of 12-point Arial text according to the supplied Artificial Analysis estimate.

GPT 6 Astra records a 4.2% result on the internal hallucination benchmark compared with 12.2% for GPT 5.6 Sol, where the lower score is better.

The data also reports that Astra went beyond the authorized target in 0% of cases in one internal evaluation, compared with 48% for GPT 5.6 Sol when production safeguards were removed.

GPT 6 Astra records a 4.2% result on the internal hallucination benchmark compared with 12.2% for GPT 5.6 Sol.

The supplied data says this represents about a 66% reduction on that particular benchmark. This result should be presented as a benchmark measurement rather than a claim about the model's hallucination rate across normal use.

GPT 6 Astra was trained on more than 10 trillion text tokens, more than 1 billion images, more than 1 million hours of audio, and more than 1 million hours of video.

The text data includes web content, reference materials, technical documentation, source code, synthetic data, and human-generated text. The image data covers natural scenes, objects, people, and diagrams.

The audio and video data include conversational, narrated, instructional, informational, and general interest material.

GPT 6 Astra Max reaches 65 tokens per second, while xhigh reaches 55 tokens per second, and high, medium, and low reach 54, 54, and 53 tokens per second, respectively.

The Low setting has the lowest reported time to first answer token at 2.59 seconds. The supplied data also states that prices vary by up to four times across the five versions.

OpenAI also reports that Fast mode can process tasks up to twice as fast as Standard mode. Fast mode costs twice as much as Standard mode.

OpenAI reports a 25-times reduction in Codex round-trip latency in an internal engineering task after changing the memory allocation system, while peak memory use increased by about 30%.

GPT 6 Astra costs $10 per 1 million input tokens and $50 per 1 million output tokens.

The higher token price does not always mean a higher task cost. Astra's estimated Terminal Bench task cost was about 9% lower than GPT 5.6 Sol and about 63% lower than Claude Fable 5.1.

Another comparison reports that Astra scored 64.6% on Terminal Bench Science, compared with 52.6% for Claude Fable 5.1, at an estimated API cost about 31% lower.

A lower-cost setting also records 61.1% compared with 22.4% for the best GPT 5.6 Sol result, with an estimated API cost about 27% lower. 

GPT 6 Astra reaches roughly 58% accuracy at around 45,000 output tokens in one plotted run, compared with about 37% for GPT 5.6 Sol at around 28,000 tokens. Claude Fable 5.1 reaches about 56% at more than 260,000 tokens.

Artificial Analysis reports about 27,000 output tokens per task for Astra compared with about 78,000 for Claude Fable 5.1 at maximum effort, while both have the same Intelligence Index score. 

GPT 6 Astra has several customer-reported results across different applications. Basis reports a 20% improvement in the pass rate for end-to-end agent workflows.

CodeRabbit reports about 20% more bugs caught and more than twice the bug catch rate on pull requests requiring extensive cross-file reasoning.

Hebbia reports 17% better instruction following and correct supporting source documents 19% more often. Box reports more than a 10% lower likelihood of confident false claims.

GPT 6 Astra improves reasoning, coding, computer use, science, cybersecurity, and long-context tasks. Its results show how AI capabilities can support increasingly complex digital workflows.

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• https://openai.com/index/gpt-6-astra-next-generation-work/ 
• https://openai.com/index/gpt-6-astra/ 
• https://cdn.openai.com/pdf/gpt-6-astra-eu-ai-act-public-summary-of-training-content.pdf 
• https://artificialanalysis.ai/models/releases/gpt-6-astra 
• https://openai.com/is-IS/index/gpt-6-astra-next-generation-work/