Leaderboard

Every published model, effort setting, and coded player.

Company / associationShowing 13 of 13

#	Model	Effort
1	GPT-6.1 SolOpenAI · Low	Low	15881528–1698 95% CI 1528–1698	96.20	$0.1381	6.79	111	132	85.6%
2	Foul PlayOther	—	15601513–1623 95% CI 1513–1623	—	$0	0	0	791	92.9%
3	Claude Opus 5.5Anthropic · Low	Low	13521262–1473 95% CI 1262–1473	70.34	$0.3552	6.09	178	84	63.1%
4	Claude Fable 5.1Anthropic · Low	Low	13391247–1443 95% CI 1247–1443	64.74	$1.0577	9.33	280	84	61.9%
5	GPT-6 SolOpenAI · Low	Low	13301243–1429 95% CI 1243–1429	71.46	$0.1754	5.80	137	132	65.2%
6	GPT-6 LunaOpenAI · High	High	11981112–1331 95% CI 1112–1331	67.05	$0.0107	8.11	313	40	70.0%
7	Claude Sonnet 5.5Anthropic · Low	Low	11221032–1223 95% CI 1032–1223	53.11	$0.2268	5.76	249	100	38.0%
8	Heuristic botOther	—	10981078–1124 95% CI 1078–1124	63.54	$0	0.001	0	1,628	55.0%
9	GPT-6 LunaOpenAI · Low	Low	1022949–1086 95% CI 949–1086	55.13	$0.0075	3.98	34	132	34.8%
10	Max-damage botOther	—	10001000–1000 95% CI 1000–1000	56.25	$0	0.002	0	1,323	54.5%
11	Claude Haiku 4.5Anthropic · High	High	967895–1003 95% CI 895–1003	37.01	$0.4176	22.75	2.1k	20	45.0%
12	Claude Haiku 4.5Anthropic · None	None	816695–932 95% CI 695–932	33.38	$0.1639	7.31	456	112	14.3%
13	Random botOther	—	244114–335 95% CI 114–335	0.00	$0	0.002	0	1,028	1.0%

Elo with 95% intervals · Select a metric to sort · Swipe for more statistics

Head-to-head matrix

Each cell shows wins–losses from the row player's view, against the named column opponent. Game counts include ties. Unplayed and self comparisons have no result. Select Replays to watch a published game. Player order follows the initial Elo ranking. Only the published snapshot is included. Same-lab model games remain excluded.

The filter selects row players. All opponent columns remain available. Scroll sideways to compare opponents. Player labels stay fixed.

Row player	H2H vsGPT-6.1 SolLow	H2H vsFoul PlayReference	H2H vsClaude Opus 5.5Low	H2H vsClaude Fable 5.1Low	H2H vsGPT-6 SolLow	H2H vsGPT-6 LunaHigh	H2H vsClaude Sonnet 5.5Low	H2H vsHeuristic botReference	H2H vsGPT-6 LunaLow	H2H vsMax-damage botReference	H2H vsClaude Haiku 4.5High	H2H vsClaude Haiku 4.5None	H2H vsRandom botReference
GPT-6.1 SolLow	–Self	10–818 games	15–520 games Replays (1) Game 1: Row won	16–420 games Replays (1) Game 1: Row won	–Unplayed	–Unplayed	18–220 games	18–018 games	–Unplayed	12–012 games Replays (1) Game 1: Row won	–Unplayed	20–020 games	4–04 games
Foul PlayReference	8–1018 games	–Self	–Unplayed	–Unplayed	15–318 games Replays (1) Game 1: Row won	–Unplayed	11–112 games	473–27500 games Replays (11) Game 1: Row won Game 2: Row won Game 3: Row won Game 4: Row won Game 5: Row won Game 6: Row won Game 7: Row lost Game 8: Row won Game 9: Row won Game 10: Row won Game 11: Row won	18–018 games	192–15207 games Replays (4) Game 1: Row won Game 2: Row won Game 3: Row won Game 4: Row won	–Unplayed	18–018 games Replays (1) Game 1: Row won	–Unplayed
Claude Opus 5.5Low	5–1520 games Replays (1) Game 1: Row lost	–Unplayed	–Self	–Unplayed	10–1020 games	–Unplayed	–Unplayed	10–212 games Replays (1) Game 1: Row won	17–320 games	7–18 games	–Unplayed	–Unplayed	4–04 games
Claude Fable 5.1Low	4–1620 games Replays (1) Game 1: Row lost	–Unplayed	–Unplayed	–Self	10–1020 games Replays (1) Game 1: Row lost	–Unplayed	–Unplayed	10–212 games Replays (1) Game 1: Row won	18–220 games	6–28 games	–Unplayed	–Unplayed	4–04 games
GPT-6 SolLow	–Unplayed	3–1518 games Replays (1) Game 1: Row lost	10–1020 games	10–1020 games Replays (1) Game 1: Row won	–Self	–Unplayed	17–320 games	15–318 games	–Unplayed	11–112 games	–Unplayed	16–420 games Replays (1) Game 1: Row lost	4–04 games
GPT-6 LunaHigh	–Unplayed	–Unplayed	–Unplayed	–Unplayed	–Unplayed	–Self	–Unplayed	13–720 games	–Unplayed	15–520 games Replays (1) Game 1: Row lost	–Unplayed	–Unplayed	–Unplayed
Claude Sonnet 5.5Low	2–1820 games	1–1112 games	–Unplayed	–Unplayed	3–1720 games	–Unplayed	–Self	8–412 games Replays (1) Game 1: Row won	12–820 games Replays (1) Game 1: Row won	8–412 games	–Unplayed	–Unplayed	4–04 games
Heuristic botReference	0–1818 games	27–473500 games Replays (11) Game 1: Row lost Game 2: Row lost Game 3: Row lost Game 4: Row lost Game 5: Row lost Game 6: Row lost Game 7: Row won Game 8: Row lost Game 9: Row lost Game 10: Row lost Game 11: Row lost	2–1012 games Replays (1) Game 1: Row lost	2–1012 games Replays (1) Game 1: Row lost	3–1518 games	7–1320 games	4–812 games Replays (1) Game 1: Row lost	–Self	12–618 games	327–173500 games Replays (11) Game 1: Row won Game 2: Row won Game 3: Row won Game 4: Row won Game 5: Row won Game 6: Row won Game 7: Row lost Game 8: Row won Game 9: Row won Game 10: Row won Game 11: Row won	–Unplayed	15–318 games	497–3500 games Replays (10) Game 1: Row won Game 2: Row won Game 3: Row won Game 4: Row won Game 5: Row won Game 6: Row won Game 7: Row won Game 8: Row won Game 9: Row won Game 10: Row won
GPT-6 LunaLow	–Unplayed	0–1818 games	3–1720 games	2–1820 games	–Unplayed	–Unplayed	8–1220 games Replays (1) Game 1: Row lost	6–1218 games	–Self	6–612 games	–Unplayed	17–320 games	4–04 games
Max-damage botReference	0–1212 games Replays (1) Game 1: Row lost	15–192207 games Replays (4) Game 1: Row lost Game 2: Row lost Game 3: Row lost Game 4: Row lost	1–78 games	2–68 games	1–1112 games	5–1520 games Replays (1) Game 1: Row won	4–812 games	173–327500 games Replays (11) Game 1: Row lost Game 2: Row lost Game 3: Row lost Game 4: Row lost Game 5: Row lost Game 6: Row lost Game 7: Row won Game 8: Row lost Game 9: Row lost Game 10: Row lost Game 11: Row lost	6–612 games	–Self	11–920 games	10–212 games	493–7500 games Replays (11) Game 1: Row won Game 2: Row won Game 3: Row won Game 4: Row lost Game 5: Row won Game 6: Row won Game 7: Row won Game 8: Row won Game 9: Row won Game 10: Row won Game 11: Row won
Claude Haiku 4.5High	–Unplayed	–Unplayed	–Unplayed	–Unplayed	–Unplayed	–Unplayed	–Unplayed	–Unplayed	–Unplayed	9–1120 games	–Self	–Unplayed	–Unplayed
Claude Haiku 4.5None	0–2020 games	0–1818 games Replays (1) Game 1: Row lost	–Unplayed	–Unplayed	4–1620 games Replays (1) Game 1: Row won	–Unplayed	–Unplayed	3–1518 games	3–1720 games	2–1012 games	–Unplayed	–Self	4–04 games Replays (1) Game 1: Row won
Random botReference	0–44 games	–Unplayed	0–44 games	0–44 games	0–44 games	–Unplayed	0–44 games	3–497500 games Replays (10) Game 1: Row lost Game 2: Row lost Game 3: Row lost Game 4: Row lost Game 5: Row lost Game 6: Row lost Game 7: Row lost Game 8: Row lost Game 9: Row lost Game 10: Row lost	0–44 games	7–493500 games Replays (11) Game 1: Row lost Game 2: Row lost Game 3: Row lost Game 4: Row won Game 5: Row lost Game 6: Row lost Game 7: Row lost Game 8: Row lost Game 9: Row lost Game 10: Row lost Game 11: Row lost	–Unplayed	0–44 games Replays (1) Game 1: Row lost	–Self

Anthropic vs OpenAI

Lab summary

4 Anthropic models and 3 OpenAI models, at their lowest thinking settings. This is one Pokémon benchmark, not a measure of provider intelligence.

The ratings below use all benchmark opponents, including reference bots. They are relative to the Max-damage bot, not Showdown ladder ratings. Bars show 95% intervals.

Anthropic

Highest benchmark rating

Claude Opus 5.5 · lowest thinking (low)

1352 95% interval 1262⁠–⁠1473

OpenAI

Highest benchmark rating

GPT-6.1 Sol · lowest reasoning (low)

1588 95% interval 1528⁠–⁠1698

240 games between Anthropic’s and OpenAI’s models: Anthropic won 88, OpenAI won 152. The aggregate is weighted by games: each completed cross-lab game counts once. It is not an equal average of models or pairings. Model pairs with more games have more weight. The bar shows the share of points (a win is 1 point, a tie ½).

Player details

Detailed player statistics

Select a column heading to sort within each settings group. Grey rows are reference bots, for scale.

The table scrolls sideways.


Lowest thinking settings and reference bots
1	GPT-6.1 Sol · lowest reasoning (low)OpenAI · lowest reasoning: low; no off setting	1588 1528⁠–⁠1698	132	86%	113–19	26	0.0%	0.0%	111	6.8 s	$0.14
–	Foul PlayBotPokéBench reference bot	1560 1513⁠–⁠1623	791	93%	735–56	20	–	–	0	0	–
2	Claude Opus 5.5 · lowest thinking (low)Anthropic · lowest thinking: low; no off setting	1352 1262⁠–⁠1473	84	63%	53–31	24	0.0%	0.0%	178	6.1 s	$0.36
3	Claude Fable 5.1 · lowest thinking (low)Anthropic · lowest thinking: low; no off setting	1339 1247⁠–⁠1443	84	62%	52–32	24	0.0%	0.0%	280	9.3 s	$1.06
4	GPT-6 Sol · lowest reasoning (low)OpenAI · lowest reasoning: low; no off setting	1330 1243⁠–⁠1429	132	65%	86–46	24	0.0%	0.0%	137	5.8 s	$0.18
5	Claude Sonnet 5.5 · lowest thinking (low)Anthropic · lowest thinking: low; no off setting	1122 1032⁠–⁠1223	100	38%	38–62	21	0.2%	0.0%	249	5.8 s	$0.23
–	Heuristic botBotPokéBench reference bot	1098 1078⁠–⁠1124	1628	55%	896–732	20	–	–	0	1 ms	–
6	GPT-6 Luna · lowest reasoning (low)OpenAI · lowest reasoning: low; no off setting	1022 949⁠–⁠1086	132	35%	46–86	23	0.1%	0.0%	34	4.0 s	< $0.01
–	Max-damage botBotPokéBench reference bot	1000 1000⁠–⁠1000	1323	54%	721–602	20	–	–	0	2 ms	–
7	Claude Haiku 4.5 · no thinkingAnthropic · none (thinking off)	816 695⁠–⁠932	112	14%	16–96	22	0.0%	0.0%	456	7.3 s	$0.16
–	Random botBotPokéBench reference bot	244 114⁠–⁠335	1028	1%	10–1018	23	–	–	0	2 ms	–
High thinking settings (separate)
1	GPT-6 Luna · high reasoningOpenAI · effort high	1198 1112⁠–⁠1331	40	70%	28–12	20	0.0%	0.0%	313	8.1 s	$0.01
2	Claude Haiku 4.5 · high thinkingAnthropic · effort high	967 895⁠–⁠1003	20	45%	9–11	18	0.0%	0.0%	2,092	22.7 s	$0.42

Ratings use all benchmark games and are relative to the Max-damage bot (rated 1000), not Showdown ladder Elo. High thinking results are shown separately and do not enter the cross-lab grid or lab aggregate.

Rank: Place among the models in the same settings group. Reference bots get no rank.
Player: The model, its lab, and the reasoning setting it played at.
Rating and 95% interval: Bradley–Terry rating on the Elo scale. We are 95% sure that the true rating is inside the interval.
Games: Games played, against all opponents.
Point share: Share of points won: a win is 1 point, a tie is ½.
Wins– losses: Wins, losses, and ties if any.
Turns per game: Average length of its games, in turns.
Wrong answers: Share of decisions where the first answer named no legal action. The model then gets another try.
Random picks: Share of decisions where 3 answers named no legal action, so the harness picked a random one.
Output tokens per decision: Recorded output tokens per saved decision with usage, including reported thinking once. Input is excluded; saved reasks and rejected decisions are included.
Time per decision: Average time from the prompt to the answer.
Cost per game: Recorded token-rate accounting for one side of a game, with cached input at the cache price. This is not necessarily cash charged.

2,803 games of Gen 9 Random Battle, singles · data of 6 October 2026 · prompt version 3 · Showdown 3661ce40

These Elo ratings are not directly comparable to Pokémon Showdown ladder ratings. We played no human opponents and set the Max-damage bot’s Elo to 1000. Intervals are 95% confidence intervals. Read the method.

Win rate counts wins / games. Opponent strengths vary, so aggregate win rates do not determine Elo.

Price/game uses saved token-rate accounting per completed game, including saved retry usage. Subscription-backed gateway costs are not necessarily cash charges. Coded players have no model API cost.

Tokens/turn averages recorded output tokens per saved decision with usage. Input and cached input are excluded. Reported thinking is already included in output and is counted once. Saved reask/retry usage and simulator-rejected decisions are included, unlike Seconds/turn. Separate thinking counts may be unreported; we do not estimate unreported thinking or unsaved failed-attempt usage. Coded bots use 0 API tokens.

Seconds/turn averages saved latency per accepted decision, including moves, switches, and retries within that decision. Simulator-rejected decisions are excluded. Foul Play timing is shown as 0 by convention; its live decision time was not measured. Error and incomplete games are excluded.

Score v1: formula and inputs

Score is 0–100, relative to this snapshot. Elo still sets the default order. Max-damage anchors benchmark Elo at 1000. Score uses the translated Random rating as its strength baseline, so a change of Elo origin does not change Score. Top Elo is the highest fitted rating across all published entrants, before sorting.

q = clamp((Elo − Random Elo) / (top Elo − Random Elo), 0, 1)
w = 0.40 + 0.50 × q²
C = 1 / (1 + cost per turn / $0.01)
T = 1 / (1 + seconds per turn / 5)
Score = 100 × q × (w + (1 − w) × (0.80 × C + 0.20 × T))

Quality, cost and speed weights are 90% / 8% / 2% at the top rating, and 52.5% / 38% / 9.5% at the midpoint between Random and the top rating. The $0.01 and 5-second references are fixed v1 constants.

Cost per turn divides total recorded API usage cost by accepted decisions. Its numerator includes simulator-rejected usage and recorded retries, counted once per saved decision. Tokens/turn instead averages all saved decisions with usage. Timing uses the published millisecond average per accepted decision, before display rounding.

Coded players have zero API usage cost. Foul Play has no Score because its live decision time was not measured. Other missing inputs or a missing or mismatched snapshot cost supplement also make Score unavailable.

Leaderboard

Head-to-head matrix

Lab summary

Detailed player statistics

The columns