GPT-5.6 Sol ranks #11 of 87 models on the November 2026 ToneBench board, and GPT-5.6 Sol (ultra) is its best configuration, #24 of 151 configurations, with a Writing Score of 82.3/100 and a Writing Elo of 2134. One script costs $0.367 at API list price.
Last updated , from board data generated at 17:52 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 87 modelsits best configuration is #24 of 151 configurations
Writing Score ?
82.3 out of 100
Writing Elo ?
2134 95% range 2082 to 2185
Cost per Script
$0.367 at API list price
Key Results
StandingGPT-5.6 Sol ranks #11 of 87 models, and this is its best configuration. As a configuration, it is #24 of 151 configurations by Writing Elo (2134), in the upper third of the board. Its 95% range (2082 to 2185) overlaps 12 other configurations, ranked #17 to #29.
MetricsBest-ranked: Substance, Accuracy & Value (88.0, 5th of 151 configurations, +6.2 against the board median). Lowest-ranked: Tone & Voice Match (77.7, 43rd of 151 configurations, +3.6 against the board median).
ScriptsFrom 80.1 on Script 10 (engineering process walkthrough) to 84.6 on Script 9 (career guide): a 4.5-point spread across the 10 reference scripts.
ConsistencyIts Writing Score moves ± 1.7 between drafts of the same script, against ± 2.5 for the median configuration: steadier than most.
ValueGPT-6 Sol (medium) ranks higher with an overlapping Elo range and costs about $0.056 per script, against $0.367 per script for this one.
Louis's PickThis is the strongest GPT-5.6 Sol setting, but GPT-5.6 Sol (low) costs about 25 cents less per script and its Elo range overlaps this setting's, so I'd start there.
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 Substance, Accuracy & Value, its best-ranked metric, the judges found its explanations deeper and more accurate than the typical configuration's. Even its lowest-ranked metric, Tone & Voice Match, ranks in the top half of the board, so no metric stands out as a weak spot.
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 7 configurations that cost at least 50% more.
Among proprietary models, GPT-5.6 Sol is 10th of 53. As a configuration, it is 23rd of 108 proprietary configurations. The best open-weight configuration, GLM-5.3 (max) at configuration #22, outranks it.
Lab
OpenAI 3rd of 13 modelsthis setting 5th of 32 configurations
Weights
Proprietary 10th of 53 modelsthis setting 23rd of 108 configurations
Consistency
± 1.7 steadier than most
Average Tokens
28.9k input + output
Time per Script
4.1 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 +1.2 against this configuration, for about 24 cents less per script.
GPT-5.6 Sol is also on the board at other effort settings, and none of them rank above this one. The thinking-level page for GPT-5.6 Sol charts how quality, cost and time change with the setting.
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-5.6 Sol (ultra)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 151 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 · +3.6 vs median
board best 82.8 · Claude Opus 5.5 (max effort)77.7± 2.0 · 43rdboard median 74.0
Writing Craft & Clarity ?13% weight · +3.1 vs median
board best 83.2 · Claude Opus 5.5 (xhigh)78.1± 1.4 · 37thboard median 75.0
Substance, Accuracy & Value ?15% weight · +6.2 vs median
board best 88.4 · Claude Opus 5.5 (xhigh)88.0± 1.1 · 5thboard median 81.8
Continuity & Emotion ?14% weight · +4.0 vs median
board best 85.7 · Claude Opus 5.5 (max effort)81.5± 1.4 · 25thboard median 77.5
YouTube Best Practices ?12% weight · +3.8 vs median
board best 84.5 · Claude Fable 5.2 (max effort)80.1± 1.6 · 28thboard median 76.4
Hook Strength ?10% weight · +3.4 vs median
board best 84.0 · Claude Fable 5.2 (xhigh)83.0± 2.5 · 14thboard median 79.6
Length Adherence ?8% weight · +7.2 vs median
board best 99.0 · Claude Fable 5.2 (xhigh)92.0± 5.8 · 40thboard median 84.8
Slop Score ?5% weight · +4.4 vs median
board best 89.0 · GPT-6 Sol (medium)85.6± 1.1 · 33rdboard median 81.3
Visual Cue Quality ?4% weight · +6.8 vs median
board best 85.9 · Claude Opus 5.5 (max effort)81.6± 1.3 · 21stboard median 74.8
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
81.5
out of 100
27th of 151 configurations on this script · board median 77.2
Script 2
news-analysis / skeptical explainer
82.1
out of 100
30th of 151 configurations on this script · board median 78.4
Script 3
personal roadmap / opinion
82.6
out of 100
22nd of 151 configurations on this script · board median 77.2
Script 4
short explainer
81.4
out of 100
24th of 151 configurations on this script · board median 75.7
Script 5
news-analysis / opinion explainer
82.5
out of 100
25th of 151 configurations on this script · board median 78.0
Script 6
founder announcement / personal origin story
84.2
out of 100
14th of 151 configurations on this script · board median 79.2
Script 7
personal technical walkthrough / agentic workflow case study
82.2
out of 100
29th of 151 configurations on this script · board median 77.9
Script 8
product release announcement / personal observation
82.5
out of 100
24th of 151 configurations on this script · board median 79.0
Script 9
career guide / hiring analysis
84.6
out of 100
19th of 151 configurations on this script · board median 79.3
Script 10
engineering process walkthrough / presentation adaptation
80.1
out of 100
31st of 151 configurations on this script · board median 75.0
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 Visual Cue Quality: ± 1.3 between drafts against ± 2.9.
Consistency by Metric
Metric
This model
Board median
Verdict
Tone & Voice Match ?
77.7 ± 2.0
± 1.9
typical
Writing Craft & Clarity ?
78.1 ± 1.4
± 1.5
typical
Substance, Accuracy & Value ?
88.0 ± 1.1
± 2.1
steadier than most
Continuity & Emotion ?
81.5 ± 1.4
± 1.5
typical
YouTube Best Practices ?
80.1 ± 1.6
± 2.4
typical
Hook Strength ?
83.0 ± 2.5
± 2.7
typical
Length Adherence ?
92.0 ± 5.8
± 6.6
typical
Slop Score ?
85.6 ± 1.1
± 1.6
typical
Visual Cue Quality ?
81.6 ± 1.3
± 2.9
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
4.1 minabout 3x the board median of 1.5 min
Prompt tokens in
13.2kstyle guide + brief + research packet
Tokens Out
15.7kscript + any reasoning tokens
Cost per Script
$0.367provider-counted output, thinking included, plus the fixed prompt priced once; varies ± 0.139 between drafts
List Price Used
$4 / $20input / 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 82.3 combines their scores with the parts computed in code (Length Adherence and half of the Slop Score). The highest and lowest judge are 9.6 points apart on its Writing Score. That is tighter than the board median of 13.4, so the judges mostly agree on this one. 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
79.2
+10.5 against its board average of 68.7
GLM 5.3 Flash
Z.ai
88.8
+5.9 against its board average of 82.9
GPT-6.1 Sol (medium)
OpenAI
81.7
+9.8 against its board average of 71.9
Jev 1.13
TypeSafe
79.7
+5.7 against its board average of 74.0
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-5.6-sol at reasoning level: ultra.
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-5.6 Sol (ultra) at Writing?
GPT-5.6 Sol ranks #11 of 87 models on ToneBench, and this is its best configuration. This configuration is #24 of 151 configurations, in the upper third of the board, with a Writing Elo of 2134 and a Writing Score of 82.3/100. 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-5.6 Sol (ultra) the Best OpenAI Model for Writing?
No. GPT-5.6 Sol is 3rd of 13 OpenAI models. The top one is GPT-6 Sol, through GPT-6 Sol (max), about 167 Elo ahead of this setting.
Is GPT-5.6 Sol (ultra) Good Value for the Money?
It costs about $0.367 per script. GPT-6 Sol (medium) ranks higher with an overlapping Elo range and costs less.
What Are the Strengths and Weaknesses of GPT-5.6 Sol (ultra)?
Its best-ranked metric is Substance, Accuracy & Value (88.0, 5th of 151 configurations, +6.2 against the board median), and its lowest-ranked is Tone & Voice Match (77.7, 43rd of 151, +3.6). Even that one ranks in the top half of the board. The Scores by Metric section shows the board median and the board's best for each one.
How Was GPT-5.6 Sol (ultra) Evaluated?
It was run through the Codex CLI (OpenAI subscription), with the exact model/route ID gpt-5.6-sol at reasoning effort ultra, 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-5.6 Sol (ultra) Have Open Weights?
No. It is a proprietary model: its weights are not public. Among proprietary configurations it is 23rd of 108 for writing.