Gemma 3 4B ranks #87 of 87 models on the November 2026 ToneBench board, and Gemma 3 4B (no thinking) is its only configuration, #151 of 151 configurations, with a Writing Score of 34.3/100 and a Writing Elo of -367. One script costs $0.0009 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 ?
#87 of 87 modelsits only configuration is #151 of 151 configurations
Writing Score ?
34.3 out of 100
Writing Elo ?
-367 95% range -394 to -333
Cost per Script
$0.0009 at API list price
Key Results
StandingGemma 3 4B ranks #87 of 87 models, and this is its only configuration on the board. As a configuration, it is #151 of 151 configurations by Writing Elo (-367), last on the board. Its 95% range (-394 to -333) overlaps no other configuration's. Writing Elo is a relative scale: a rating below zero means it lost far more script-by-script comparisons than it won.
MetricsBest-ranked: Length Adherence (48.6, 135th of 151 configurations, -36.1 against the board median). Lowest-ranked: Substance, Accuracy & Value (31.1, 151st of 151 configurations, -50.7 against the board median).
ScriptsFrom 29.3 on Script 7 (personal technical walkthrough) to 41.3 on Script 2 (news-analysis): a 12.0-point spread across the 10 reference scripts.
ConsistencyIts Writing Score moves ± 4.8 between drafts of the same script, against ± 2.5 for the median configuration: more variable than most.
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).
Substance, Accuracy & Value ranks in the bottom half (151st of 151 configurations), so check the facts and the depth before anything goes out.
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.
Among open-weight models, Gemma 3 4B is last of 34. As a configuration, it is last of 43 open-weight configurations. The best open-weight configuration is GLM-5.3 (max), at configuration #22, and every configuration above it is proprietary.
Lab
Google 12th of 12 modelsthis setting 20th of 20 configurations
Weights
Open 34th of 34 modelsthis setting 43rd of 43 configurations
Consistency
± 4.8 more variable than most
Average Tokens
15.7k input + output
Time per Script
0.9 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 +45.8 against this configuration, for about 58 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.
Gemma 3 4B (no 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 · -42.2 vs median
board best 82.8 · Claude Opus 5.5 (max effort)31.9± 2.6 · 151stboard median 74.0
Writing Craft & Clarity ?13% weight · -42.1 vs median
board best 83.2 · Claude Opus 5.5 (xhigh)33.0± 2.2 · 151stboard median 75.0
Substance, Accuracy & Value ?15% weight · -50.7 vs median
board best 88.4 · Claude Opus 5.5 (xhigh)31.1± 4.3 · 151stboard median 81.8
Continuity & Emotion ?14% weight · -44.5 vs median
board best 85.7 · Claude Opus 5.5 (max effort)33.1± 3.1 · 151stboard median 77.5
YouTube Best Practices ?12% weight · -41.5 vs median
board best 84.5 · Claude Fable 5.2 (max effort)34.8± 3.5 · 151stboard median 76.4
Hook Strength ?10% weight · -48.3 vs median
board best 84.0 · Claude Fable 5.2 (xhigh)31.3± 6.8 · 151stboard median 79.6
Length Adherence ?8% weight · -36.1 vs median
board best 99.0 · Claude Fable 5.2 (xhigh)48.6± 9.9 · 135thboard median 84.8
Slop Score ?5% weight · -32.8 vs median
board best 89.0 · GPT-6 Sol (medium)48.4± 3.3 · 151stboard median 81.3
Visual Cue Quality ?4% weight · -48.8 vs median
board best 85.9 · Claude Opus 5.5 (max effort)26.0± 7.8 · 150thboard 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
33.7
out of 100
151st of 151 configurations on this script · board median 77.2
Script 2
news-analysis / skeptical explainer
41.3
out of 100
151st of 151 configurations on this script · board median 78.4
Script 3
personal roadmap / opinion
37.2
out of 100
151st of 151 configurations on this script · board median 77.2
Script 4
short explainer
33.7
out of 100
151st of 151 configurations on this script · board median 75.7
Script 5
news-analysis / opinion explainer
29.6
out of 100
151st of 151 configurations on this script · board median 78.0
Script 6
founder announcement / personal origin story
40.1
out of 100
151st of 151 configurations on this script · board median 79.2
Script 7
personal technical walkthrough / agentic workflow case study
29.3
out of 100
151st of 151 configurations on this script · board median 77.9
Script 8
product release announcement / personal observation
35.5
out of 100
151st of 151 configurations on this script · board median 79.0
Script 9
career guide / hiring analysis
30.5
out of 100
151st of 151 configurations on this script · board median 79.3
Script 10
engineering process walkthrough / presentation adaptation
32.0
out of 100
151st 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 Visual Cue Quality: ± 7.8 between drafts against ± 2.9, so two drafts of the same script can score quite differently there.
Consistency by Metric
Metric
This model
Board median
Verdict
Tone & Voice Match ?
31.9 ± 2.6
± 1.9
typical
Writing Craft & Clarity ?
33.0 ± 2.2
± 1.5
more variable than most
Substance, Accuracy & Value ?
31.1 ± 4.3
± 2.1
more variable than most
Continuity & Emotion ?
33.1 ± 3.1
± 1.5
more variable than most
YouTube Best Practices ?
34.8 ± 3.5
± 2.4
typical
Hook Strength ?
31.3 ± 6.8
± 2.7
more variable than most
Length Adherence ?
48.6 ± 9.9
± 6.6
more variable than most
Slop Score ?
48.4 ± 3.3
± 1.6
more variable than most
Visual Cue Quality ?
26.0 ± 7.8
± 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
0.9 minfaster than the board median of 1.5 min
Prompt tokens in
13.9kstyle guide + brief + research packet
Tokens Out
1.8kscript + any reasoning tokens
Cost per Script
$0.0009measured from actual billed tokens; varies ± 0.000 between drafts
List Price Used
$0.05 / $0.1input / 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 34.3 combines their scores with the parts computed in code (Length Adherence and half of the Slop Score). The highest and lowest judge are 11.6 points apart on its Writing Score. That is close to the board median of 13.4. 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
27.1
-41.6 against its board average of 68.7
GLM 5.3 Flash
Z.ai
38.7
-44.2 against its board average of 82.9
GPT-6.1 Sol (medium)
OpenAI
34.5
-37.4 against its board average of 71.9
Jev 1.13
TypeSafe
36.8
-37.2 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 idgoogle/gemma-3-4b-it (the request sets no level; the provider applies no thinking).
Generations5 independent runs × 10 scripts = 50 drafts, stored after generation and never edited.
Run dates2026-10-08.
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 Gemma 3 4B (no thinking) at Writing?
Gemma 3 4B ranks #87 of 87 models on ToneBench, and this is its only configuration on the board. This configuration is #151 of 151 configurations, last on the board, with a Writing Elo of -367 and a Writing Score of 34.3/100. 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 Gemma 3 4B (no thinking) the Best Google Model for Writing?
No. Gemma 3 4B is last of 12 Google models. The top one is Gemini 4 Carbon, through Gemini 4 Carbon (high thinking), about 2215 Elo ahead of this setting.
Is Gemma 3 4B (no thinking) Good Value for the Money?
It costs about $0.0009 per script. Cohere Command A+ (05-2026) (thinking on) ranks higher and costs less.
What Are the Strengths and Weaknesses of Gemma 3 4B (no thinking)?
Its best-ranked metric is Length Adherence (48.6, 135th of 151 configurations, -36.1 against the board median), and its lowest-ranked is Substance, Accuracy & Value (31.1, 151st of 151, -50.7). 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 Gemma 3 4B (no thinking) Evaluated?
It was run through OpenRouter, with the exact model/route ID google/gemma-3-4b-it, first run on 2026-10-08. 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 Gemma 3 4B (no thinking) Have Open Weights?
Yes. Its weights are public, so it can be downloaded and run on your own hardware. Check the license if you need open source in the strict sense. Among open-weight configurations it is 43rd of 43 for writing.