Gemini 2.5 Flash ranks #64 of 87 models on the November 2026 ToneBench board, and Gemini 2.5 Flash (dynamic thinking) is its only configuration, #124 of 151 configurations, with a Writing Score of 65.0/100 and a Writing Elo of 837. One script costs $0.016 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 ?
#64 of 87 modelsits only configuration is #124 of 151 configurations
Writing Score ?
65.0 out of 100
Writing Elo ?
837 95% range 728 to 938
Cost per Script
$0.016 at API list price
Key Results
StandingGemini 2.5 Flash ranks #64 of 87 models, and this is its only configuration on the board. As a configuration, it is #124 of 151 configurations by Writing Elo (837), in the bottom third of the board. Its 95% range (728 to 938) overlaps 7 other configurations, ranked #122 to #129.
MetricsBest-ranked: Length Adherence (68.5, 113th of 151 configurations, -16.2 against the board median). Lowest-ranked: Hook Strength (69.9, 139th of 151 configurations, -9.7 against the board median).
ScriptsFrom 56.4 on Script 10 (engineering process walkthrough) to 74.0 on Script 6 (founder announcement): a 17.6-point spread across the 10 reference scripts.
ConsistencyIts Writing Score moves ± 6.7 between drafts of the same script, against ± 2.5 for the median configuration: more variable than most.
ValueGPT-6 Luna (medium) ranks far higher and costs about $0.0026 per script, against $0.016 per script for this one.
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).
Hook Strength ranks in the bottom half (139th of 151 configurations), so plan on rewriting the opening.
The script format moves its score a lot. If most of your scripts look like its best or weakest format, that result is a better guide than the average.
Two drafts of the same script can differ noticeably, so generating a few drafts and keeping the best pays off.
It outranks 6 configurations that cost at least 50% more.
Among proprietary models, Gemini 2.5 Flash is 46th of 53. As a configuration, it is 99th of 108 proprietary configurations. The best open-weight configuration, GLM-5.3 (max) at configuration #22, outranks it.
Lab
Google 9th of 12 modelsthis setting 17th of 20 configurations
Weights
Proprietary 46th of 53 modelsthis setting 99th of 108 configurations
Consistency
± 6.7 more variable than most
Average Tokens
18.7k input + output
Time per Script
0.4 min average, retries included
Highest-Ranked in This LabGemini 4 Carbon (high thinking) ranks highest of the Google configurations by Writing Elo, with a Writing Score +15.1 against this configuration, for about 57 cents more 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.
Gemini 2.5 Flash (dynamic thinking)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 · -14.6 vs median
board best 82.8 · Claude Opus 5.5 (max effort)59.5± 3.3 · 123rdboard median 74.0
Writing Craft & Clarity ?13% weight · -12.1 vs median
board best 83.2 · Claude Opus 5.5 (xhigh)62.9± 4.2 · 130thboard median 75.0
Substance, Accuracy & Value ?15% weight · -12.0 vs median
board best 88.4 · Claude Opus 5.5 (xhigh)69.9± 3.8 · 125thboard median 81.8
Continuity & Emotion ?14% weight · -12.3 vs median
board best 85.7 · Claude Opus 5.5 (max effort)65.2± 5.3 · 130thboard median 77.5
YouTube Best Practices ?12% weight · -13.4 vs median
board best 84.5 · Claude Fable 5.2 (max effort)63.0± 4.0 · 128thboard median 76.4
Hook Strength ?10% weight · -9.7 vs median
board best 84.0 · Claude Fable 5.2 (xhigh)69.9± 3.2 · 139thboard median 79.6
Length Adherence ?8% weight · -16.2 vs median
board best 99.0 · Claude Fable 5.2 (xhigh)68.5± 16.9 · 113thboard median 84.8
Slop Score ?5% weight · -15.9 vs median
board best 89.0 · GPT-6 Sol (medium)65.3± 3.9 · 137thboard median 81.3
Visual Cue Quality ?4% weight · -9.6 vs median
board best 85.9 · Claude Opus 5.5 (max effort)65.1± 5.0 · 119thboard 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
66.0
out of 100
125th of 151 configurations on this script · board median 77.2
Script 2
news-analysis / skeptical explainer
66.6
out of 100
128th of 151 configurations on this script · board median 78.4
Script 3
personal roadmap / opinion
63.8
out of 100
125th of 151 configurations on this script · board median 77.2
Script 4
short explainer
62.9
out of 100
125th of 151 configurations on this script · board median 75.7
Script 5
news-analysis / opinion explainer
66.5
out of 100
124th of 151 configurations on this script · board median 78.0
Script 6
founder announcement / personal origin story
74.0
out of 100
112th of 151 configurations on this script · board median 79.2
Script 7
personal technical walkthrough / agentic workflow case study
58.7
out of 100
135th of 151 configurations on this script · board median 77.9
Script 8
product release announcement / personal observation
70.3
out of 100
127th of 151 configurations on this script · board median 79.0
Script 9
career guide / hiring analysis
64.9
out of 100
125th of 151 configurations on this script · board median 79.3
Script 10
engineering process walkthrough / presentation adaptation
56.4
out of 100
138th 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 varies most on Continuity & Emotion: ± 5.3 between drafts against ± 1.5, so two drafts of the same script can score quite differently there.
Consistency by Metric
Metric
This model
Board median
Verdict
Tone & Voice Match ?
59.5 ± 3.3
± 1.9
more variable than most
Writing Craft & Clarity ?
62.9 ± 4.2
± 1.5
more variable than most
Substance, Accuracy & Value ?
69.9 ± 3.8
± 2.1
more variable than most
Continuity & Emotion ?
65.2 ± 5.3
± 1.5
more variable than most
YouTube Best Practices ?
63.0 ± 4.0
± 2.4
more variable than most
Hook Strength ?
69.9 ± 3.2
± 2.7
typical
Length Adherence ?
68.5 ± 16.9
± 6.6
more variable than most
Slop Score ?
65.3 ± 3.9
± 1.6
more variable than most
Visual Cue Quality ?
65.1 ± 5.0
± 2.9
more variable 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
0.4 minfaster than the board median of 1.5 min
Prompt tokens in
13.9kstyle guide + brief + research packet
Tokens Out
4.8kscript + any reasoning tokens
Cost per Script
$0.016measured from actual billed tokens; varies ± 0.005 between drafts
List Price Used
$0.3 / $2.5input / 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 65.0 combines their scores with the parts computed in code (Length Adherence and half of the Slop Score). The highest and lowest judge are 19.5 points apart on its Writing Score. That is wider than the board median of 13.4: GLM 5.3 Flash rates it noticeably higher than Claude Opus 5.5 (medium), so the Writing Score sits between two different opinions. 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
56.6
-12.0 against its board average of 68.7
GLM 5.3 Flash
Z.ai
76.1
-6.7 against its board average of 82.9
GPT-6.1 Sol (medium)
OpenAI
63.5
-8.5 against its board average of 71.9
Jev 1.13
TypeSafe
63.8
-10.2 against its board average of 74.0
Evaluation Setup
How this exact configuration was run and judged: route, model ID, dates, sampling and prompt.
Exact model / route idgemini-2.5-flash (the request sets no level; the provider applies dynamic thinking).
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 Gemini 2.5 Flash (dynamic thinking) at Writing?
Gemini 2.5 Flash ranks #64 of 87 models on ToneBench, and this is its only configuration on the board. This configuration is #124 of 151 configurations, in the bottom third of the board, with a Writing Elo of 837 and a Writing Score of 65.0/100. 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 Gemini 2.5 Flash (dynamic thinking) the Best Google Model for Writing?
No. Gemini 2.5 Flash is 9th of 12 Google models. The top one is Gemini 4 Carbon, through Gemini 4 Carbon (high thinking), about 1012 Elo ahead of this setting.
Is Gemini 2.5 Flash (dynamic thinking) Good Value for the Money?
It costs about $0.016 per script. GPT-6 Luna (medium) ranks higher and costs less.
What Are the Strengths and Weaknesses of Gemini 2.5 Flash (dynamic thinking)?
Its best-ranked metric is Length Adherence (68.5, 113th of 151 configurations, -16.2 against the board median), and its lowest-ranked is Hook Strength (69.9, 139th of 151, -9.7). Its best-ranked metric still sits in the bottom half. The Scores by Metric section shows the board median and the board's best for each one.
How Was Gemini 2.5 Flash (dynamic thinking) Evaluated?
It was run through the Google Gemini API, with the exact model/route ID gemini-2.5-flash, 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 Gemini 2.5 Flash (dynamic thinking) Have Open Weights?
No. It is a proprietary model: its weights are not public. Among proprietary configurations it is 99th of 108 for writing.