Slides: Fun stories from building OpenRouter and where all this is going - Alex Atallah, OpenRouter

Source Video

Fun stories from building OpenRouter and where all this is going - Alex Atallah, OpenRouter

Relationship To World's Fair 2026

These slides are extracted from a public AI Engineer YouTube video connected to World's Fair 2026. Speaker-matched clips are supporting context unless later confirmed as exact session recordings; official livestream recordings are day-level/event-level source material.

Related Scheduled Sessions

Extracted Slides

slide-001.jpg

OCR text:

aWS

eee)

@®Graphite WW Windsurf 4 MoneobB

Mdaily £3 augment code WorkOS

slide-002.jpg

OCR text:

vee ere Inference may be the largest market ever in software

ee K

Weltn? Vo1

ve

mney i a

iN

IN

Avice ALEX ATALLAH < OpenRouter

slide-003.jpg

OCR text:

January,2023:Moderation

r/ChatGPT.2yr.ago

Noobrage2112

OpenAlBanningaccounts.

Gone Wild

Hithere,

After a thoroughinvestigation,we have determined thatyou oramemberofyourorganization are usingthe

OpenAl APlinways thatviolate ourpolicies.

Dueto thisbreach we arehalting accessto theAPlimmediately for theorganizationPersonal.Commonreasons

forbreachincludeviolationsofourcontentpolicy,repeated attemptsatdisallowed use-cases,oraccessing the

API from anunsupported location.Youmay also wish toreviewourTermsof Use.

appealswithin onebusiness day andwillcontactyou ifwereinstateaccess to theAPl.

Best,

TheOpenAl team

That was theE-mail lreceivedjusta couple of minutesearlier.

It seemsOpenAl doesnotappreciate people usingit'sprogramforD&D/ Textbased/Roleplaying/Fictional based

adventuregames thatmight entail formsofViolence/Gore/Fantasy/Erotic/Fictionalgameplay.

Ihadjustpurchased anaccountfortheBetaPlayground andshortly afterI wasremoved.I'mnotgoing to be

supporting OpenAl anymore after this action.I don't appreciate the weights and aggression theyhave placed on

thefilterprecautions,andIfeel thisishighlyunfair.

slide-004.jpg

OCR text:

ir January, 2023: Moderation

World's Fair

OpenAl Banning accounts.

cx

wrid's ; j a

b “

eal

re als

MT eet Engineering the future of Al

slide-005.jpg

OCR text:

i February, 2023: Open Source race begins...

World's Fair

[D] List of Large Language Models to play with.

orororm a a

; i< |

ore WE . a

World's Fair Engineering the future of Al

slide-006.jpg

OCR text:

Cee: errs

ed fy Ratt Raz et Ory) renee i MT ft Te ee a

ea iia g Micros Viords Faw

elk) iE: ~

ue [ccc eee ocr ee en ae

a a

Peer ICI) yO an ao (cd

Neod| rere. _ i: Tee oa

i |

—— Sree nrnen e

rr mid Paces Riad io j - = an

See eel a 2 7

Fr i

slide-007.jpg

OCR text:

February, 2023: ... and Llama wins, almost

LLaMA: Open and Efficient Foundation Language Models

Hugo Touvron; Thibaut Lavril; Gautier Izacard; Xavier Martinet

Marie-Anne Lachaux, Timothee Lacroix, Baptiste Rozitre, Naman Goyal

Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin

Edouard Grave; Guillaume Lample*

Meta Al

Abstract performance, a smaller one trained longer will

Wei ' ultimately be cheaper at inference. For instance,

we introduce LLaMA. arcollection of founda- although Hoffmann et al. (2022) recommends

tion language models ranging from 7B to 65B -

parameters. We train our models on trillions training a 10B model on 200B tokens, we find

of tokens, and show that it is possible to train that the performance of a 7B model continues to

state-of-the-art models using publicly avail- improve even after IT tokens.

able datasets exclusively, without resorting

to proprietary and inaccessible datasets. Ip The focus of this work is to train a series of

pesticular, LLaMA-13B outperforms GPT-3 language models that achieve the best possible per-

(1758) on most benchmerks, and LLaMA- formance at various inference budgets, by training

65B is competitive with the best models, on more tokens than what is typically used. The

Chinchilla-70B and Pal.M-540B. We release resulting fels, called LLaMA, ranges from 7B

all our models to the research communily’. . we

to 65B parameters with compctitive performance

slide-008.jpg

OCR text:

enn February, 2023: .. and Llama wins, almost

World's Fair

LLaMA: Open and Efficient Foundation Language Models

aws Hugo Touvron; Thibeut Lavril; Gautier Izacard; Xavier Martinet

el Marie-Anne Lachaux, Timothee Lacroix, Baptiste Rozitre, Naman Goyal

Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin

4 Edouard Grave; Guillaume Lample"

; Meta Al

Tent as A Abstract performance, a smaller one wained longer will

, , _ ultimately be cheaper at inference. For instance,

We introduce Ls MA. « collection of founda: although Hoffmann et al. (2022) recommends

5 bon language models ranging from 7B to 6$B - ep

, ; parameters. We train cur models oa tnitions training a 10B model on 2008 tokens, we find

a of tokens, and show that it ts powsble to train that the performance of a 7B modet continues to

ntl Masc-of-the-an models using publicly avail- improve even after IT tokens.

able datasets caclusively, without resorting

‘au to propnetasy and inaccessible datasets fe The focus of this work is to train a series of

ba) particular, LLaMA-138 outperforms GPT-3 language models that achieve the best possible per-

(1758) om most benchmarks, and LLaMA- formance at various inference budgets, by training

“ compas ee rapes on more tokens than what is typically used. The

inchalla- LM-S40B. We release

all ous models to the research community |. resulting models, called ee from 7B

AlEngmoce > é

‘ a

Tet Engineering the future of Al

slide-009.jpg

OCR text:

ee March, 2023: The first distillation success

World's Fair

Alpaca: A Strong, Replicable Instruction-Following Model

vS

es

| | Stanford (3

anv Alpaca &&

Overview

World's Fair

slide-010.jpg

OCR text:

April, 2023: Window.ai and BYOM (bring your own model)

window.ai ,

Use your own Al models on the web oa

; . =

a Pry

slide-011.jpg

OCR text:

ree WF VA Ae Pac bm O lel -1al cele lcs

The Unified ae

aws Interface For LLMs a

-

ae i BYeys1) Pad

N

World's Fair a Microsoft ae smoot

slide-012.jpg

OCR text:

LLMRankings

Comparemodelsforall prompts

AllCategories

Programming

Roleplay

Marketing

Marketing/Seo

Technology

Science

Translation

Finance

Health

Trivia

Academia

2.6T

1.95T

10to100%growth

MoMforthelast2y

Mar17

Leaderboard

Token usage across models

Top thisweek

OpenAl:GPT-40-mini>

443Btokens

GPT-4o mnis OpenA's newest model after [GPT-4 Omn]models

Google:Gemini 2.0Flash>

239B tokens

Anthropic:ClaudeSonnet4>

207Btokens

Claude Sonnet 4 signiicanty enhances the ca

Google:Gemini 2.5ProPreview>

183B tokens

Gemni 2.5 Prois Googe's state-of-the-art Ai model des

slide-013.jpg

OCR text:

Themostmodels,providers,andtokens

8.4T

2.5M+

MonthlyTokens

Global Users

Active Providers

Models

Signup

Buycredits

GetyourAPlkey

Create anaccount toget started.You

Creditscanbeused withanymodel or

Create anAPIkeyand startmaking

can setupanorgforyourteamlater.

provider.

requests.FullyOpenAlcompatible.

OPENROUTER_APILKEY

Apr1

Mar30

slide-014.jpg

OCR text:

World's Fair

ae] WS

Closed-source models cece yet gee ptt iene

didn’t keep up with

Be aT demand... no =

4

ee ator. |

N

cer

tan oa [ Pperare|

MT er Engineering the future of Al

slide-015.jpg

OCR text:

YourActivity

Seehowyou've beenusing modelsonOpenRouter.Privacy

Spend

Tokens

Requests

Last

Last

Lastday 499

Lastwek4.35K

Last day3

Lastwk12

day

From:

To:

Filters

Export

Timestamp

Provider/Model

App

Tokens

Cost

Speed

Finish

O

Jun3,10:11PM

Claude 3.7.Sonnet

OpenRouter:Chatroom

79.0tps

stop

Jun3,10:11PM

Claude37.Soonet

OpenRouter:Chatroom

s

66.0tps

stop

Jun3,10:11PM

Claude.3.7Sonnet

OpenRouter:Chatroom

s69

stop

slide-016.jpg

OCR text:

renee Will intelligence be winner-take-all?

Token Marketshare by Model Author

a es Le aS a bi an

a * Pere ie = al i. a ae

x . a is

7 |

ee all U

I

| i eu nin |

| a “ee j Ml

en ae

eee MEW reco <o)| aah ES 680 0 Oh

slide-017.jpg

OCR text:

World's Fair

elere dime ol hem anele Lacs

; ees

—?

Making an

increasingly

a heterogeneous

J ,

mS <" ecosystem

B homogeneous

nro!)

N

~~ coed

Ce here

World's Fair MTV Iacetvo 1 Cade ES 19900

slide-018.jpg

OCR text:

INT erated WS AlEngincer

xe) it | rita | ey 2, WV vilekw alle |

we A

7 1 ;

ma WorkoO: 7 - & tambo

Ba ad eal ome " Ps Sd

ust | eval Rd rl | 7 fers] | tae Rl |

Ne

~ | hacatean < Wo” fekair| DISTRIBUTIONAL]

slide-019.jpg

OCR text:

AlEngincer 7 AlEngincer

rosoft | ya eR ar lL | Lc hd | Vera al |

ro Tard

Seely | F- zg | & tambo

| I os ae , Ps AlEngincer

‘rust rl 2 ee O} Rote Da

ot

— i.

a | ; ; en a oe | |

slide-020.jpg

OCR text:

oo a ay cr ee / - rd

en

Ls

Technical challenge: a ne

Ih Arcee Tue Ue ete ; ; ,

[Peres Te ree ~, Porraan fa a ron

ee ~ oo |:

slide-021.jpg

OCR text:

We built a middleware for inference called “Plugins”

aa ee ee cieistal Cerone at

complete

[cco [01 oo-0 Gaal or>)0 111 Stak rN Co

i eer oe een

2 gh I Pal Comer O Lae ar Cores Bee

.1isDisabled

next.complete(requestFragment);

foe Oe AL i es wae at o2 010 i 0G ol tole

lisMessagesInput(te:.ecues!) |]

Pie Zeno] a he Fara 0X0 Rear =o 000 Np cit aoe cea gE |

slide-022.jpg

OCR text:

Unlike MCPs, plugins allow transformations

on both inputs and outputs

, (cena

oe 5 an = addAnnotationsToOutput (

folvnaslehan aan

annotations: .fcachedAnnotations,

);

oka 2 at

peek tel aa ee elie ees Fi Proll ae

. mont ars tT at 1 (rt a a8 acerca mele

peyote ere meen a ead F

slide-023.jpg

OCR text:

World's Fair

WELCOME

TO THE TEAM

BS Robert .

ne, ; 1 J

More modalities... eo

q ; @ oy

d OpenRouter

_ 4

Co 7 -

"me Cate |

[WortdsFair] Microsoft 2S aypai

slide-024.jpg

OCR text:

ere Better prompt RLS .

Better model discoverability/routing.

| -

| yo

ST 8

a sa

MT et Engineering the future of Al

Slide-Derived Subjects To Review

Subject extraction uses video title, related session titles/descriptions, transcript context, and OCR text when available. OCR is best-effort and should be reviewed against the embedded slide images.