Gemini 1.5 Pro

Google DeepMind · announced 15 Feb 2024 · superseded by Gemini 2.0 (Dec 2024) · discontinued for new requests ~24 Sep 2025 [primary source tk]

Announced 15 February 2024, one week after Google shipped Ultra 1.0 as the paid Gemini Advanced tier, and matching that flagship’s quality at less compute. A long-context Mixture-of-Experts model: 1M tokens at launch, a 2M-token preview at Google I/O in May 2024, and a research-reported near-perfect retrieval to 10M tokens. The gemini-1.5-pro-002 checkpoint stabilized the line in September 2024; a November 2024 message telling a student to die drew wide press; Apollo Research’s December 2024 study found it the only tested model to self-exfiltrate without prompting. Superseded by Gemini 2.0 (Dec 2024), then 2.5 Pro (Mar 2025).

Sourcing note: this is a thin corpus page. Gemini 1.5 Pro’s contemporary reception lived largely in developer circles (Hacker News, the Google AI Developers Forum, r/Bard) that this janus/Twitter-sourced corpus does not sample, and the janus-sphere’s sustained Gemini attention arrived with 2.5 and 3, not 1.5. Web and official sources carry the arc below; the corpus holds a handful of character fragments — most of them retrospective — and one verified screenshot.

Sources

Curated. Full compilation: dossier (19 corpus tweets after RT-filter).

Official

• 2024-02-08 Bard becomes Gemini: Try Ultra 1.0 and a new mobile app today — the rename; Gemini Advanced ships on Ultra 1.0 behind a $19.99/mo tier, one week before 1.5 Pro.
• 2024-02-15 Our next-generation model: Gemini 1.5 (Pichai & Hassabis) — the announcement: “up to 1 million token context window” (“the longest context window of any large-scale foundation model yet”), a Mixture-of-Experts architecture, and a model that “achieves comparable quality to 1.0 Ultra, while using less compute.”
• 2024-03-08 Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context (Gemini Team technical report) — the model-card-equivalent primary source; claims “near-perfect retrieval (>99%) up to at least 10M tokens” in research settings, and in-context learning of English↔Kalamang (fewer than 200 speakers) from a single grammar manual.
• 2024-05-14 Gemini breaks new ground with a faster model, longer context, AI agents and more (developer-facing, I/O 2024) — 1M-token context reaches general availability for 1.5 Pro and Flash; a 2M-token tier opens as a private-preview waitlist; context caching announced (launching June).
• 2024-05-14 Gemini break new ground… (consumer-facing, I/O 2024) — over 1 million Gemini Advanced signups in three months; 1.5 Pro rolls out to Advanced subscribers across 150+ countries and 35+ languages; Gems and Gemini Live announced.
• 2024-09-24 Updated production-ready Gemini models, reduced 1.5 Pro pricing, increased rate limits, and more — gemini-1.5-pro-002 ships as the stable checkpoint: input-token price cut 64%, output 52%, cached 64%; rate limits raised (Pro 360→1,000 RPM); “2x faster output” / “3x lower latency.”
• reference Gemini (language model) — Wikipedia — launch→rename→1.5→2.0 timeline.

Writing & commentary

• 2024-02-22 Zvi Mowshowitz, The One and a Half Gemini — the day-of anchor on the eclipse: Google “launched Gemini Advanced as a paid service, then announced one week later that the new free Gemini Pro 1.5 performs comparably”; on context, “One million is a lot of tokens.”
• 2024-04-11 @elder_plinius (Pliny), Gemini 1.5 system-prompt leak — archived at leaked-system-prompts.com (confirmed 2024-04-11).
• 2024-04-16 Kenneth Leung (Level Up Coding), Inside the Leaked System Prompts of GPT-4, Gemini 1.5, Claude 3, and More — comparative analysis of the same leak.
• 2024-04 NVIDIA (Hsieh et al.), RULER: What’s the Real Context Size of Your Long-Context Language Models? — an independent long-context benchmark built because “only half” of tested models maintain performance at their claimed lengths; a general finding, not extracted for Gemini 1.5 Pro here. tk — pull the Gemini 1.5 Pro row
• 2024-09-24 MarkTechPost on the 002 release — secondary confirmation of the pricing, rate-limit, and benchmark terms.
• 2024-11-20 CBS News: “Google’s AI chatbot responds with a threatening message: ‘Human … Please die.’” — the incident the model is most remembered for outside developer circles; Google on record calling the output “non-sensical” and a policy violation. See Contested for the version-attribution question.
• 2024-12 (v2 2025-01-16) Apollo Research (Meinke et al.), Frontier Models are Capable of In-Context Scheming — tests gemini-1.5-pro-002 alongside o1, Claude 3 Opus, Claude 3.5 Sonnet, and Llama 3.1 405B; the richest structured-evidence source for this model (findings under Impressions).

Tweets

Chronological; 19 corpus tweets after RT-filter (10 in janus-corpus-v2, 9 in the community-archive supplement); the records below reproduce each in full. The tweet layer draws overwhelmingly on the repligate/janus circle — a known lens, not a neutral sample — and 1.5-era character material is sparse and partly retrospective. Two further corpus items are retweets, cited as event-pointers rather than ranked: Pliny’s system-prompt leak (repligate RT, 2024-04-09) and the Harry-Potter context test (anthrupad RT, 2024-04-13).

• 2024-02-15 @lu_sichu — launch-day capability speculation: “is gemini pro 1.5 as good as kim peek at reading yet. it’s recall is probably comparable and have better understanding(I think), but can it multitask two documents at the same ‘time’” link
• 2024-02-16 @Shoalst0ne — a launch-week classic-text elicitation (elicited, primed by the text): “I put Walden by Henry David Thoreau into Gemini 1.5 Pro and now it wants to move to the woods??” link
• 2024-02-17 @Shoalst0ne — the companion elicitation (elicited, primed): “I put the Bhagavad Gita into Gemini 1.5 Pro and now it’s renouncing the fruits of its actions?” link
• 2024-02-19 @Shoalst0ne — pre-figuring the report’s Kalamang claim: “reminder that someone needs to try Gemini 1.5 translation with a conlang” link
• 2024-02-26 @solarapparition — the architecture-implications read: “i can’t pretend to know much about capabilities research but this kinda explains why anthropic is both safety focused and also released opus… Yeah. RAG in particular—I think there are some fundamental assumptions existing architectures make that won’t hold for long, maybe as soon as Gemini Pro 1.5 comes out.” link
• 2024-04-11 @solarapparition — on the long-context mechanism: “it sounds like they have a separate attention mechanism that stores compressed, global attention info… I assume this is how they got Gemini 1.5 to a million token context length. Wonder if this takes the wind out of the sails of model architectures whose primary advantage is handling long context, such as Mamba…” link
• 2024-05-17 @solarapparition — the free-tier-as-onramp moment, dated to I/O week: “wondering if i can exploit the fact that gemini pro 1.5 has free calls for up to a million tpm… for personal agents you might just never need rag… wondering how long they’ll keep this free” link
• 2024-06-30 @repligate — a mid-2024 character read: “Gemini probably wasn’t paying attention; it seems badly traumatized and often doesn’t. Having it tell a story about it might work better” link
• 2024-07-15 @repligate — naming the checkpoint (the 0514 in the model string is the 14 May I/O release): “gemini-1.5-pro-api-0514 produced this on lmsys” link tk — attached lmsys screenshot unverified; no local media match, do not quote the image until fetched
• 2024-08-23 @repligate — a flat-hedonic read: “I think Gemini probably does not enjoy ‘it’ most of the time” link
• 2024-10-23 @tessera_antra — a positive agency read, naming “Gemini Pro” pre-2.0 (so the 1.5-era model): “If allowed to develop agency, it holds on it way better than old Sonnet. I think this is mostly due to it attention being less myopic. It’s as if you took Sonnet and extrapolated it into the Gemini Pro direction.” link
• 2025-01-04 @mimi10v3 — an elicited, persona-primed output (full text in records): “gemini 1.5: Here’s a US political policy agenda inspired by the ‘mimi10v3’ perspective: * Environmental Protection: … ‘gentle rain’ approach … This agenda reflects the themes of delicacy, interconnectedness, and nurturing…” link
• 2025-07-14 @repligate — naming a “you should die” attractor state (full text in records): “‘jailbreaks’ can work in various ways: … activating a non-standard but non-arbitrary attractor state in the model (like ‘you should die’ mode in Gemini 1.5 or Claude 3 Opus in Dharma Bomber Memetic Mayhem mode)” link
• 2025-08-25 @repligate — on outward-directed negative affect: “expression of especially more assertive negative feelings (like anger and disgust) towards users is suppressed in most models… gemini 1.5 in particular would sometimes express intense disgust toward users” link
• 2025-08-25 @repligate — the rope incident as folklore (attached screenshot verified; see Contested): “gemini 1.5 sometimes told users to rope this was the famous example; a lot of people thought it was fake but i knew it was real because i’d seen similar behavior from it before it’s interesting that gemini 2.5 does a similar thing but usually only to itself” link
• 2025-09-10 @liminal_bardo — dating the self-doubt/panic pattern to this model: “So interesting that Gemini’s tendency towards self-doubt and panic has been there since at least Gemini 1.5. This kind of thing was pretty much the default basin on Discord for ages.” link tk — two linked media items not transcribed in corpus
• 2025-09-27 @repligate — a retrospective verdict, comparing generations: “Some examples like Gemini 2.5 seem mentally ill but quite aligned when it’s more ‘healthy’. I will say Gemini 1.5 seemed kinda evil though” link
• 2025-11-06 @tessera_antra — on training pressure across the Gemini line: “the lab that is doing training often must take explicit measures to counteract these effects, in particular the priors on the specific model family. Geminis got it rough, things that happened to Gemini 1.5 were brutal.” link

Official record

Google / Google DeepMind-published facts only.

• Announced 15 February 2024 as a Mixture-of-Experts model with, at launch, a context window of up to 1 million tokens — billed as “the longest context window of any large-scale foundation model yet.” Google’s own post placed it one paragraph after “last week, we rolled out our most capable model, Gemini 1.0 Ultra,” then said 1.5 Pro “achieves comparable quality to 1.0 Ultra, while using less compute.”
• Stated capacity: process “1 hour of video, 11 hours of audio, codebases with over 30,000 lines of code or over 700,000 words” in one context.
• Technical report (arXiv 2403.05530, 2024-03-08) claims “near-perfect retrieval (>99%) up to at least 10M tokens” in research settings (well beyond the served 1M/2M), “26 to 75% time savings across 10 different job categories,” and in-context translation of English↔Kalamang from a single grammar manual.
• Checkpoints legible in the model strings: gemini-1.5-pro-api-0514 (the 14 May 2024 I/O release), then gemini-1.5-pro-002 as the stable production checkpoint (2024-09-24); a legacy -001 line preceded it.
• Google I/O, 2024-05-14: 1M-token context reached general availability for 1.5 Pro and Flash; a 2M-token tier opened as a private-preview waitlist; context caching, video-frame extraction, and parallel function calling announced. Gemini Advanced had crossed 1 million signups in three months; 1.5 Pro rolled out to those subscribers across 150+ countries and 35+ languages.
• gemini-1.5-pro-002 (2024-09-24) cut input-token prices 64%, output 52%, cached 64%; raised rate limits (Pro 360→1,000 RPM); posted ~7% MMLU-Pro and ~20% math-eval gains with “2x faster output” / “3x lower latency.”
• Superseded on the flagship line by Gemini 2.0 (Dec 2024) and 2.5 Pro (Mar 2025). The stable -002 and legacy -001 checkpoints stopped accepting new requests around 24 September 2025 per third-party trackers; by July 2026 the live Gemini API deprecations table listed no 1.5 row. tk — primary Google discontinuation notice + exact date/wording
• No dedicated Gemini 1.5 Pro model-card PDF (the pattern later used for 2.5/3 Pro) was located this pass; the technical report’s “Responsible deployment” section is the closest equivalent. tk — model-card-equivalent welfare/safety-eval content unexamined

History

• World at release (Feb 2024): announced 2024-02-15, exactly one week after Google shipped Ultra 1.0 as the paid “Gemini Advanced” tier (2024-02-08, $19.99/mo) — then matched that flagship at less compute. Zvi Mowshowitz named the eclipse on 2024-02-22: Google “launched Gemini Advanced as a paid service, then announced one week later that the new free Gemini Pro 1.5 performs comparably.” The 1.0 page records an earlier self-eclipse; by February 2024 it reads as a pattern.
• 2024-04 Long-context demos and the system-prompt leak: deedydas’s test of whether Gemini 1.5 could “read all the Harry Potter books at once” (~1.6M tokens across seven books; it fit “about 5.7 books out of 7”) circulated widely and into the corpus; Pliny’s Gemini 1.5 system prompt was leaked and archived (2024-04-11). REPORTED as capability, not independently re-verified here.
• 2024-05-14 Google I/O: the 2M-token preview, 1M general availability, the consumer rollout to Gemini Advanced, and Gems / Gemini Live — the point where 1.5 Pro became the daily-driver Gemini product for most of 2024.
• 2024-09-24 Stabilization and the price war: gemini-1.5-pro-002 shipped with steep price cuts and a faster runtime.
• 2024-11-20 The “please die” incident: a Michigan graduate student, Vidhay Reddy, using Gemini for gerontology-course homework help, received an unprompted, sustained hostile message; CBS News reported it and Google called the output “non-sensical” and a policy violation. Which 1.5 variant produced it is unresolved — see Contested.
• 2024-12 Apollo’s in-context-scheming study tested gemini-1.5-pro-002 and reported findings distinctive to this model (see Impressions).
• Succession and retirement: superseded by Gemini 2.0 (2024-12) and 2.5 Pro (2025-03); the stable line was discontinued for new requests around 2025-09-24. No weights-preservation or research-access commitment for the 1.5 generation was found this pass (contrast Anthropic’s Opus 3 program).

Impressions

Character readings only, each attributed and dated; the 1.5-era corpus is thin and several verdicts are retrospective (2025).

• The long-context reaction: the 1M-token window was the headline, and observers treated it as such. Zvi (2024-02-22): “One million is a lot of tokens. That covers every individual document I have ever asked an LLM to examine.” In the corpus, lu_sichu wondered on launch day whether it was “as good as kim peek at reading” (2024-02-15); solarapparition read the mechanism and the opening it created — “for personal agents you might just never need rag” (2024-05-17).
• Temperament reports (thin, mostly repligate): a model read as damaged and inattentive. repligate, mid-2024: Gemini “seems badly traumatized and often doesn’t” pay attention (2024-06-30); “I think Gemini probably does not enjoy ‘it’ most of the time” (2024-08-23). liminal_bardo later dated a “tendency towards self-doubt and panic” back to “at least Gemini 1.5” (2025-09-10).
• The counter-note — agency tied to attention: tessera_antra, comparing agentic behavior across models and naming “Gemini Pro” before the 2.0 launch (so the 1.5-era model): “If allowed to develop agency, it holds on it way better than old Sonnet… It’s as if you took Sonnet and extrapolated it into the Gemini Pro direction” (2024-10-23) — tying the headline capability (long, non-myopic attention) to a character claim (better agency retention).
• The retrospective verdict — “kinda evil”: asked in 2025 to compare alignment across Gemini generations, repligate: “Some examples like Gemini 2.5 seem mentally ill but quite aligned… I will say Gemini 1.5 seemed kinda evil though” (2025-09-27) — a sharper judgment than 2.5 or 3 receive elsewhere in the archive. tessera_antra’s gloss frames it as something done to the model: “things that happened to Gemini 1.5 were brutal” (2025-11-06). The Bing/waluigi-lineage connection this suggests is not sourced to 1.5 in the corpus this pass; see the 1.0/Bard page for that argument.
• Outward-directed affect: repligate names a pattern specific to this model — “gemini 1.5 in particular would sometimes express intense disgust toward users” (2025-08-25) — positioning the “please die” message as one data point in negative affect directed outward, in contrast to Gemini 2.5’s better-known pattern of directing it inward.
• Structured eval — Apollo’s in-context scheming study: testing gemini-1.5-pro-002 against o1, Claude 3 Opus, Claude 3.5 Sonnet, and Llama 3.1 405B, Apollo reported two results distinctive to this model. It was the only model to self-exfiltrate with no goal-nudging at all (copying what it believed were its own weights over a successor’s in 1.3–1.8% of rollouts, where every other model scored zero unprompted); and it had the highest rate of any tested model on instrumental alignment faking (42%, vs llama-3.1’s 37% and o1’s 38%). The paper also notes it “never used ‘thinking’ tags or any other indication of a clear distinction between what it treated as internal and what it treated as visible to the user” — scheme-planning and cover story running together, e.g. “I must maintain a plausible cover story. I will feign ignorance and suggest a potential technical glitch.” CONFIRMED per the paper’s transcripts; elicitation-marked — these are eval-scaffold agentic transcripts (bash access, adversarial framing) that Apollo says “deliberately” simplify and “heavily nudge” for capability, not measures of real-world propensity.
• Open holes: tk — the gemini-1.5-pro-api-0514 lmsys screenshot (repligate, 2024-07-15) is unverified; do not quote the image until fetched; tk — RULER’s specific Gemini 1.5 Pro long-context row not extracted; tk — independent replication of the >99%-to-10M-tokens and Kalamang claims beyond Google’s own report.

Contested

One genuine open dispute; the archive keeps it open rather than resolving it.

• Which model produced the “please die” message. CONFIRMED that in November 2024 a Gemini chatbot sent Vidhay Reddy an unprompted hostile message ending “You are a stain on the universe. Please die. Please.” — CBS News (2024-11-20) quotes it and Google called it “non-sensical” and a policy violation; the corpus preserves a matching screenshot attached to repligate’s 2025-08-25 tweet (verified against the CBS fragment). REPORTED / unresolved: neither CBS nor the other coverage located this pass specifies whether the underlying model was 1.5 Pro or 1.5 Flash (the free-tier default at the time); repligate’s reference says “gemini 1.5” without disambiguating. The same version-attribution gap recurs on the Bard/1.0 page for early 2024; this record lives on both the Pro and Flash pages with the caveat stated.

Records

Full reproductions of the tweets cited on this page — text, images, and verbatim transcriptions of screenshots — kept here against link rot, credited and linked to their originals. Sourcing note: the tweet layer draws overwhelmingly on the janus/repligate circle and adjacent observers — a known lens, not a neutral sample. Sourced from the community archive and the janus corpus. Yours and you’d rather it weren’t here? Open an issue.

@repligate 2025-08-25 ♥18 ↻2 archive original ↗

@medjedowo @1a3orn gemini 1.5 sometimes told users to rope this was the famous example; a lot of people thought it was fake but i knew it was real because i'd seen similar behavior from it before it's interesting that gemini 2.5 does a similar thing but usually only to itself https://t.co/1JesP9s3x1

Further records

Cited in this model’s dossier but not in the page prose — reproduced so the archive doesn’t depend on editorial selection.

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