GPT-6 Astra ranks #11 of 82 models on the October 2026 ToneBench board through its best configuration, GPT-6 Astra (max). This setting, GPT-6 Astra (medium), is #36 of 135 configurations, with a Writing Score of 80.7/100 and a Writing Elo of 1979. One script costs $0.262 at API list price.
Last updated , from board data generated at 16:17 UTC.
Rank, scores, the nine metrics, the 10 reference scripts, cost and setup for one
configuration (a model at one reasoning setting). Key Results sums it up; the section links below it jump to the detail.
Model Rank ?
#11 of 82 modelsthrough GPT-6 Astra (max); this setting is #36 of 135 configurations
Writing Score ?
80.7 out of 100
Writing Elo ?
1979 95% range 1946 to 2013
Cost per Script
$0.262 at API list price
Key Results
StandingGPT-6 Astra ranks #11 of 82 models through its best configuration, GPT-6 Astra (max). This setting is #36 of 135 configurations by Writing Elo (1979), in the upper third of the board. Its 95% range (1946 to 2013) overlaps 18 other configurations, ranked #27 to #45, so its exact place among them is not settled.
MetricsBest-ranked: Slop Score (88.5, 5th of 135 configurations, +7.8 against the board median). Lowest-ranked: Length Adherence (83.2, 68th of 135 configurations, 0.0 against the board median).
ScriptsFrom 78.3 on Script 10 (engineering process walkthrough) to 84.0 on Script 9 (career guide): a 5.7-point spread across the 10 reference scripts.
ConsistencyIts Writing Score moves ± 1.7 between drafts of the same script, against ± 2.7 for the median configuration: steadier than most.
ValueDeepSeek V4.1 Flash 1017 (high) ranks about the same (their Elo ranges overlap) and costs about $0.0095 per script, against $0.262 per script for this one.
Louis's PickI'd pay about 89 cents more per script for GPT-6 Astra (max).
More Context Behind These Results
Writing Elo comes from comparing its average on each script with every other configuration's average on that same script; a gap smaller than the draft-to-draft variation counts as a draw (what the ranges can and cannot show).
On Slop Score, its best-ranked metric, its drafts carry fewer filler phrases and AI tells to clean out. Length Adherence ranks in the bottom half (68th of 135 configurations), so plan on trimming or padding to reach the target length.
The script format moves its score. If most of your scripts look like its best or weakest format, that result is a better guide than the average.
Its drafts vary little, so the first draft is usually close to the next one.
It outranks 3 configurations that cost at least 50% more.
Among proprietary models, GPT-6 Astra is 9th of 48. This setting is 30th of 92 proprietary configurations. The best open-weight configuration, GLM-5.3 (max) at configuration #16, outranks it.
Lab
OpenAI 4th of 12 modelsthis setting 12th of 27 configurations
Weights
Proprietary 9th of 48 modelsthis setting 30th of 92 configurations
Consistency
± 1.7 steadier than most
Average Tokens
15.8k input + output
Time per Script
1.5 min average, retries included
Highest-Ranked in This LabGPT-6 Sol (max) ranks highest of the OpenAI configurations by Writing Elo, with a Writing Score +2.8 against this configuration, for about 14 cents less per script.
Each corner is one metric on a 0 to 100 scale; the further out, the higher the score. A corner outside the dashed line beats the board median. Hover or tap a point for its exact score, and a metric name for what it rewards.
GPT-6 Astra (medium)Board medianBoard best per metricMax possible (100)
Scores by Metric
Nine metrics, each scored 0 to 100 and weighted into the Writing Score; the weight sits under each name. Rank is out of all 135 ranked configurations.
Score colors:Strong: 82 and upMiddle: 65 to 81.9Weak: under 65
This modelBoard best (upper line)Board median (lower line)±: spread between drafts?: what the metric rewards
Tone & Voice Match ?19% weight · +3.5 vs median
board best 82.8 · Claude Opus 5.5 (max effort)77.0± 1.3 · 47thboard median 73.4
Writing Craft & Clarity ?13% weight · +4.4 vs median
board best 83.2 · Claude Opus 5.5 (xhigh)78.4± 1.0 · 21stboard median 74.0
Substance, Accuracy & Value ?15% weight · +5.2 vs median
board best 88.4 · Claude Opus 5.5 (xhigh)86.0± 0.8 · 20thboard median 80.8
Continuity & Emotion ?14% weight · +2.9 vs median
board best 85.7 · Claude Opus 5.5 (max effort)80.0± 1.0 · 40thboard median 77.1
YouTube Best Practices ?12% weight · +1.3 vs median
board best 84.4 · Claude Opus 5.5 (xhigh)76.6± 1.6 · 60thboard median 75.3
Hook Strength ?10% weight · +3.2 vs median
board best 83.7 · Claude Opus 5.5 (max effort)82.5± 1.4 · 18thboard median 79.2
Length Adherence ?8% weight · 0.0 vs median
board best 98.8 · Claude Sonnet 5.5 (max effort)83.2± 1.8 · 68thboard median 83.2
Slop Score ?5% weight · +7.8 vs median
board best 89.0 · GPT-6 Sol (medium)88.5± 0.8 · 5thboard median 80.7
Visual Cue Quality ?4% weight · +6.5 vs median
board best 85.9 · Claude Opus 5.5 (max effort)80.7± 1.4 · 20thboard median 74.2
Scores by Reference Script
Every ranked configuration writes five drafts for each of the same 10 briefs, and each score is the mean of those drafts. The rank and board median compare it with every configuration on that script, which separates a weak result from a hard script. The result on the format closest to your own work is the most relevant.
Script 1
opinion / warning explainer
79.7
out of 100
41st of 135 configurations on this script · board median 76.4
Script 2
news-analysis / skeptical explainer
80.4
out of 100
44th of 135 configurations on this script · board median 77.6
Script 3
personal roadmap / opinion
82.9
out of 100
14th of 135 configurations on this script · board median 76.1
Script 4
short explainer
80.4
out of 100
24th of 135 configurations on this script · board median 74.5
Script 5
news-analysis / opinion explainer
80.2
out of 100
46th of 135 configurations on this script · board median 77.1
Script 6
founder announcement / personal origin story
80.5
out of 100
50th of 135 configurations on this script · board median 78.8
Script 7
personal technical walkthrough / agentic workflow case study
80.4
out of 100
41st of 135 configurations on this script · board median 76.9
Script 8
product release announcement / personal observation
79.8
out of 100
51st of 135 configurations on this script · board median 78.3
Script 9
career guide / hiring analysis
84.0
out of 100
17th of 135 configurations on this script · board median 78.5
Script 10
engineering process walkthrough / presentation adaptation
78.3
out of 100
39th of 135 configurations on this script · board median 73.6
Consistency Between Drafts
Every score on this page is the mean of 5 drafts per script. The ± is the standard deviation between those drafts: the larger it is, the more two drafts of the same script can differ.
Compared with the typical model, it's steadiest on Length Adherence: ± 1.8 between drafts against ± 7.0.
Consistency by Metric
Metric
This model
Board median
Verdict
Tone & Voice Match ?
77.0 ± 1.3
± 2.0
typical
Writing Craft & Clarity ?
78.4 ± 1.0
± 1.6
typical
Substance, Accuracy & Value ?
86.0 ± 0.8
± 2.3
steadier than most
Continuity & Emotion ?
80.0 ± 1.0
± 1.5
typical
YouTube Best Practices ?
76.6 ± 1.6
± 2.5
typical
Hook Strength ?
82.5 ± 1.4
± 2.8
steadier than most
Length Adherence ?
83.2 ± 1.8
± 7.0
steadier than most
Slop Score ?
88.5 ± 0.8
± 1.6
steadier than most
Visual Cue Quality ?
80.7 ± 1.4
± 3.0
steadier than most
Cost, Time and Tokens per Script
Logged on every run; none of these figures affects the Writing Score. Time is the average time to one accepted script, retries included. Cost is one script at the API list price.
Time per Script
1.5 minclose to the board median of 1.5 min
Prompt tokens in
13.2kstyle guide + brief + research packet
Tokens Out
2.6kscript + any reasoning tokens
Cost per Script
$0.262provider-counted output, thinking included, plus the fixed prompt priced once; varies ± 0.066 between drafts
List Price Used
$10 / $50input / output, per million tokens
Scores by Judge
Four judges score the same 50 stored drafts blind against the same rubric: three LLM judges from three labs, plus Jev, a typed judge from TypeSafe that rates each metric on five described quality levels. No single judge's taste decides the result. The Writing Score of 80.7 combines their scores with the parts computed in code (Length Adherence and half of the Slop Score). The highest and lowest judge are 12.5 points apart on its Writing Score. That is close to the board median of 13.7. Each judge also has its own scale, so every card shows that judge's score against its average across the board. How the panel works.
Claude Opus 5.5 (medium)
Anthropic
74.9
+7.3 against its board average of 67.6
GLM 5.3 Flash
Z.ai
87.4
+5.2 against its board average of 82.2
GPT-6.1 Sol (medium)
OpenAI
84.1
+13.2 against its board average of 70.8
Jev 1.13
TypeSafe
76.4
+2.9 against its board average of 73.5
Evaluation Setup
How this exact configuration was run and judged: route, model ID, dates, sampling and prompt.
Accessed viaCodex CLI (OpenAI subscription) · model page ↗.
Exact model / route idgpt-6-astra (the request sets no level; the provider applies medium).
Generations5 independent runs × 10 scripts = 50 drafts, stored after generation and never edited.
Run dates2026-10-11.
JudgesClaude Opus 5.5 at medium effort through the Claude Code subscription, GPT-6.1 Sol at medium reasoning through the Codex CLI, GLM 5.3 Flash through OpenRouter, and Jev 1.13 from TypeSafe. One call per judge per draft. All four score every draft on their own, blind to which model wrote it. The three LLM judges use the identical rubric and have to quote evidence before they score a metric. Jev answers the same rubric as one question per metric, choosing among five described quality levels, and writes no text. Seven metrics are the plain average of the four judges. Length is computed from the spoken word count, and Slop is half computed (lexical scans minus the spoken-dash penalty) and half judged. The Writing Elo is cross-checked with a Bradley-Terry fit of the same pairwise results (methodology).
Sampling and promptThe provider's default sampling, with no fine-tuning and no system-prompt changes. Every current-ranked model gets the same prompt, about 13,000 tokens (the count shifts a bit with each model's tokenizer): a style guide built from Louis's voice and storytelling guides, the target length, and the brief with its research packet. Generation is closed-book on every route: the prompt is the only source, with no web search, browsing, code execution, file access or other tool (generation).
What stays privateThe exact rubric and any non-public reference material. Each script is normally benchmarked before its video is published, which lowers the odds that a model has seen the reference, though it does not rule it out (why).
Frequently Asked Questions
How Good Is GPT-6 Astra (medium) at Writing?
GPT-6 Astra ranks #11 of 82 models on ToneBench through its best configuration, GPT-6 Astra (max). This configuration is #36 of 135 configurations, in the upper third of the board, with a Writing Elo of 1979 and a Writing Score of 80.7/100. The ranks come from full YouTube scripts written in the voice of Louis-François Bouchard and judged blind, with the channel's finished script as the reference. The benchmark measures long-form scripted writing, so the result does not carry over to every kind of text.
Is GPT-6 Astra (medium) the Best OpenAI Model for Writing?
No. GPT-6 Astra is 4th of 12 OpenAI models. The top one is GPT-6 Sol, through GPT-6 Sol (max), about 375 Elo ahead of this setting.
Is GPT-6 Astra (medium) Good Value for the Money?
It costs about $0.262 per script. DeepSeek V4.1 Flash 1017 (high) ranks about the same, inside the overlap of their Elo ranges, and costs less.
What Are the Strengths and Weaknesses of GPT-6 Astra (medium)?
Its best-ranked metric is Slop Score (88.5, 5th of 135 configurations, +7.8 against the board median), and its lowest-ranked is Length Adherence (83.2, 68th of 135, 0.0). The Scores by Metric section shows the board median and the board's best for each one.
How Was GPT-6 Astra (medium) Evaluated?
It was run through the Codex CLI (OpenAI subscription), with the exact model/route ID gpt-6-astra, first run on 2026-10-11. It wrote each script 5 times with the provider's default sampling and no fine-tuning. The Evaluation Setup section and the methodology page have the details.
Does GPT-6 Astra (medium) Have Open Weights?
No. It is a proprietary model: its weights are not public. Among proprietary configurations it is 30th of 92 for writing.