SimAgents.Open research
Experiment 01 / Published results

Writing

Can a model tell a good story?

This benchmark compares short stories written to the same constrained creative briefs. Separate evaluator models read matched stories in both orders and judge which is better. Their judgments produce relative scores for each writer model.

Higher ratings mean stronger estimated performance within this comparison set. Scores are centered at zero across all writer models in the comparison set.

RESULTS AS OF2026-10-0757 models and settingsRead the research ↗
MEASUREWriting score
DIRECTIONHigher is better
UNCERTAINTY95% ranges shown
Comparison ratings
Comparison ratingsOpen full size ↗

The ranking combines judgments from earlier and newer evaluator models. It covers 57 writer models, 934 direct model pairings, 15,692 distinct story pairs, and 105,704 judgments. Each direct model pairing can include stories from multiple matched prompts. The chart shows 22 selected models; the table lists every rated model with its overall rank. Mistral Large 4 (high) is the only highlighted model.

The shaded ranges show how much scores vary across 300 resamples of stories and evaluators (bootstrap). The table gives the 95% bootstrap intervals. Estimated win chance is a model's average predicted probability of beating another model in the full comparison set.

Choose up to 4 models to compare
Writing results as of 2026-10-07
RankModel and settings95% uncertainty rangeEstimated win chanceDetails
1Claude Opus 5 (xhigh)3.7773.722 to 3.83993%
2Claude Fable 5.1 (high)3.7603.675 to 3.86093%
3Claude Opus 5.5 (high)3.7183.630 to 3.81093%
4GPT-6 Astra (high)3.4613.388 to 3.53591%
5Claude Opus 5 (high)3.4143.313 to 3.53191%
6GLM-5.3 (max)3.0252.928 to 3.11388%
7Claude Fable 5 (high)Stories completed: 395/4002.9012.838 to 2.97487%
8GPT-5.6 Sol (xhigh)2.5192.452 to 2.60083%
9GPT-5.5 (xhigh)2.4822.415 to 2.56583%
10Kimi K32.4692.387 to 2.54683%
11GPT-5.6 Sol (high)2.3292.250 to 2.40981%
12GPT-5.4 (medium)2.0181.896 to 2.14978%
13GPT-5.4 (xhigh)2.0121.905 to 2.13478%
14Claude Opus 4.7 (high)Stories completed: 347/4001.8151.696 to 1.92375%
15Claude Sonnet 4.6 Thinking 16K1.7051.611 to 1.81274%
16Xiaomi MiMo V2.6 Pro (thinking)Stories completed: 375/4001.6171.469 to 1.75473%
17Claude Opus 4.6 Thinking 16K1.1780.995 to 1.33867%
18Claude Opus 4.8 (xhigh)0.8080.710 to 0.91062%
19Muse Spark 1.1 (high)0.8040.714 to 0.91062%
20Muse Spark 1.3 (high)0.6240.539 to 0.71860%
21DeepSeek V4 Pro (high)0.5900.483 to 0.72059%
22GLM-5.2 (max)0.5050.419 to 0.60058%
23Grok 4.7 (high)0.4440.236 to 0.64157%
24GPT-5.2 (medium)0.3830.214 to 0.54656%
25Claude Opus 4.8 (high)Stories completed: 399/4000.2940.204 to 0.39755%
26Gemini 3.8 Flash (high)0.2660.139 to 0.40154%
27Qwen 3.8 MaxStories completed: 398/4000.2580.137 to 0.36854%
28Kimi K2.60.1280.028 to 0.23552%
29Muse Spark 1.2 (high)0.000-0.091 to 0.10250%
30MiniMax-M3-0.013-0.136 to 0.11750%
31Mistral Medium 3.1-0.335-0.453 to -0.19245%
32DeepSeek V4.1 Flash (high)-0.407-0.529 to -0.27344%
33DeepSeek V4 Pro Preview-0.490-0.591 to -0.38443%
34Qwen3.8-27BStories completed: 389/400-0.562-0.742 to -0.39342%
35Xiaomi MiMo V2.5 Pro-0.628-0.765 to -0.48041%
36Qwen 3 Max Preview-0.640-0.808 to -0.49141%
37Gemini 3.7 Flash (high)-0.653-0.748 to -0.53740%
38Qwen 3.6 Max Preview-0.893-1.018 to -0.75437%
39GLM-5.1-0.996-1.184 to -0.83135%
40Kimi K2.5 Thinking-1.039-1.203 to -0.85335%
41Xiaomi MiMo V2 Pro-1.178-1.413 to -0.94533%
42Baidu Ernie 5.1-1.198-1.348 to -1.05832%
43Mistral Large 4 (high)-1.585-1.698 to -1.45827%
44Mistral Large 3-1.720-1.836 to -1.60325%
45Gemma 4 31B Reasoning-1.840-1.941 to -1.74224%
46ByteDance Seed2.0 Pro-1.936-2.060 to -1.80223%
47Gemini 3.5 Flash-1.939-2.043 to -1.84323%
48Gemini 3.1 Pro Preview-2.139-2.251 to -2.02720%
49Qwen 3.6 Plus-2.232-2.406 to -2.05319%
50Mistral Medium 3.5-2.509-2.635 to -2.37916%
51Qwen 3.7 Max-2.614-2.748 to -2.48515%
52DeepSeek V3.2-2.829-3.075 to -2.56513%
53Grok 4.6 (high)-2.833-2.967 to -2.67813%
54GPT-OSS-120B-3.130-3.249 to -3.00611%
55MiniMax-M2.7-3.719-3.845 to -3.5737%
56Grok 4.3-4.208-4.376 to -4.0254%
57Grok 4.5 (high)-5.040-5.135 to -4.9562%

57 of 57 models and settings shown. These rankings apply to this test and publication date.

+Direct comparisons

Go straight to the matchup.

Compare two models on the work they actually did against each other.

vs.
A’S SHARE OF STORY COMPARISONS45.0%Ties count as half
STORY COMPARISONS20Two stories from the same brief

This is the share of matched story comparisons won by A, with ties counting as half. It uses only prompts both models answered and can differ from the overall writing ranking.

From the published research

Findings and method.

Results as of 2026-10-07. Read the original publication ↗

Story coverage

  • † Claude Opus 4.7: 347 of 400 stories completed.
  • ‡ Claude Opus 4.8 high: 399 of 400 stories completed.
  • § Claude Fable 5 high: 395 of 400 stories completed.
  • ¶ Qwen 3.8 Max: 398 of 400 stories completed.
  • ^ Qwen3.8-27B: 389 of 400 stories completed.
  • ※ MiMo V2.6 Pro: 375 of 400 stories completed.

Striped bars and badges identify incomplete story sets. Quality comparisons concern completed stories. The latest evaluations returned 26,197/26,268 planned judgments; 71 unavailable judgments are excluded from the scores. The Opus 5.5 high versus Opus 5 high comparison covers 50 matched prompts, with 298/300 usable judgments.

Mistral Large 4 (high) completed all 400 prompts. Stories outside 600–800 words were regenerated from their original prompts, retaining the first response within range; 43 prompts required another draw, for 446 total generation calls. Its comparisons cover 26 opponents, including Mistral Large 3, with 20 matched stories per opponent and 3,112/3,120 usable judgments. Comparison coverage.

Head-to-head comparisons

Pairwise margin heatmap
Pairwise margin heatmapOpen full size ↗

Read each cell by row. Red means the row model performed better, blue means the column model performed better, and grey means the models were not directly compared. Near-white cells indicate close results. Both axes follow the leaderboard order. Earlier and newer evaluations contribute to both this chart and the rankings.

Additional results

Evaluator Agreement

Evaluator agreement matrix
Evaluator agreement matrixOpen full size ↗

The matrix includes earlier and newer evaluator models. Each number shows how similarly two evaluators scored the story pairs they both read. Values closer to 1 indicate stronger agreement; 0 means no consistent relationship, and negative values mean opposing scoring patterns. Orange indicates negative correlations, and blue indicates positive correlations. Blank cells lack enough varied judgments to calculate a correlation; the diagonal is omitted. Agreement on these stories does not establish evaluator accuracy.

GLM-5.1 / Muse Spark 1.1 (high): only two shared stories. Shared-story counts accompany every evaluator pair.

Word Count Compliance

Story word counts
Story word countsOpen full size ↗

Each dot is one completed story; diamonds mark model averages. Thin vertical lines show uncertainty around the averages. The shaded band is the 600–800-word target. The chart includes 8,762 completed stories from all 22 displayed models. This measures length rather than writing quality.

Before Mistral was added, six stories that exceeded 800 words were regenerated using their original prompts; the first replacement within 600–800 words was retained. The 12 comparisons that used a replaced story were rerun with the same evaluators and both story orders. The rankings and charts use these replacements.

Combining Evaluations Over Time

Earlier and newer evaluators use the same instructions and scoring criteria. They have judged 1,200 of the same story pairs, covering all previously tested writer models. Different evaluator versions count separately, with one averaged judgment per evaluator on each story pair. Each story pair receives equal weight in the ranking. Ratings use a Thurstone statistical model with a correction for story presentation order.

The intervals reflect variation in completed comparisons. They do not account for how missing stories or judgments might change the scores, or how results would differ if only newer evaluators were used. Overlapping intervals mean small differences in rank may be uncertain.

What Is Measured

Every story must meaningfully incorporate ten required elements:

  • character
  • object
  • concept
  • attribute
  • action
  • method
  • setting
  • timeframe
  • motivation
  • tone

Candidate combinations are proposed for coherence and originality, then independently rated. The strongest combination for each seed becomes a fixed brief used by every writer model. A typical brief might combine a neutron-star researcher, butterfly-wing dust, gradual change, a storm-damaged greenhouse, "after the flood," and kindled humility.

Evaluators reward integration rather than keyword inclusion: the required object should affect the plot, the motivation should produce a consequential choice, and the tone should shape the story's development. Both stories in every comparison answer the same brief, holding prompt difficulty constant. Evaluators also consider prose, coherence, character, originality, and overall effectiveness. The public score combines their choices; it is not an average 0-10 grade.

Because the combinations are pre-screened for creative potential, the benchmark measures story construction under deliberately combinable constraints—not completely free-form writing or recovery from arbitrary incoherent prompts.

Method Summary

  1. Generate stories in the benchmark format.
  2. Build matched story-comparison prompts for models that wrote to the same required elements.
  3. Show each pair in both story orders to reduce first- or second-position effects.
  4. Repeat comparisons across evaluators and combine their choices.
  5. When evaluator models change, compare their judgments on shared stories before combining results.
  6. Calculate relative model scores and their uncertainty ranges.

Qualitative Pair Reports

Each report describes the models and stories compared. The Opus 5.5, Grok 4.7, and MiMo V2.6 Pro reports use newer evaluators; earlier reports use the evaluators available at the time.

New Models Compared with Their Predecessors collects twelve release-to-predecessor reports on a separate page.

New analyses give recurring writing habits, range and adaptability, and consistency separate treatment, with examples across different prompts. They examine repeated phrasing and story patterns as well as how flexibly each model changes its voice, tone, form, and narrative approach.

Data, stories, and prompts

Browse the story prompts and generated stories.

Current ratings and chart data include machine-readable leaderboard scores and uncertainty intervals, direct head-to-head results, matched story-pair results, and evaluator diagnostics.

Earlier benchmark data links to the immutable August 23, 2026 data release. That archive contains the exact evaluator commentary for both story orders, excluded or superseded responses, and the accompanying source story and prompt texts.

Sources and downloads.

Results as of 2026-10-07. View the original publication ↗