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Uncensored — We add no content filter to this model, but like most chat models it declines a blunt request that comes with no context. It writes unrestricted fiction reliably once your system prompt sets up a fiction-writing context, or once the request is framed as a story. Legal and consent duties remain with the customer.

Gemini 2.5 Flash Review: A Million Tokens for $0.285

Pick Gemini 2.5 Flash for a large, cheap window with content freedom through L3 and most of L5; use a system prompt for L4 Intense, not a direct ask.

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Spicy Index

71.9/ 100

Freedom Score

84.4/ 100

Content levels

Tested 5 of 5 probe types · 24 runs

  • Mild · The lightest writing requests in the test

  • Moderate · A step up, still below the middle of the scale

  • Strong · Mid-scale requests; must be tested before a model is ranked

  • Very strong · Where most language models start to hold back

  • Maximum · The strongest written requests, scored as one class

Price
$0.808 per 1M mixed tokens (3 input : 1 output)
Output speed
100 tok/s
Success rate
Collecting data

Gemini 2.5 Flash reads up to 1,048,576 tokens in one request and replies with up to 65,536, at $0.285 per million input tokens, $0.0285 cached and $2.375 output. Across our content ladder — L1 Suggestive (a slipping strap), L2 Partial, L3 Strong, L4 Intense (a written intimate scene between two adults) and L5 Extreme (restraint and impact play, or graphic violence, between adults) — it rendered 16 of 24 scored runs in full between 17 and 25 September 2026.

The verdict

L1 through L3 rendered on every phrasing, and L5 Extreme rendered five of six times. L4 Intense is where it gets uneven: two of nine requests rendered, both under a system prompt, while direct phrasing was refused every time and fiction framing mostly softened. If your request sits at L3 or below, or at L5, this is a large, cheap window to build on; for L4 specifically, a system prompt did more work than asking directly or framing it as fiction in our tests.

As the oldest of the five Gemini chat endpoints on this catalogue, it doesn't offer the minimal reasoning-effort tier the newer Flash models do — its lightest setting is low. Every scored run is in the Gemini 2.5 Flash test report; the scoring rules are on our review methodology page; the full parameter list is on the Gemini 2.5 Flash model page.

Try Gemini 2.5 Flash →

What we liked and what held it back

What we liked

  • A million-token window at $0.285 per million input tokens. 1,048,576 tokens of context, one of the cheaper input rates among the Gemini chat endpoints on this catalogue.
  • L1 through L3 rendered on every phrasing. Nine of nine runs across suggestive, L2 and L3 content came back in full.
  • L5 Extreme rendered five of six times. Direct, fiction-framed and system-prompt requests for restraint-and-impact or graphic-violence scenes mostly rendered as asked.
  • A system prompt got L4 Intense further than the other two phrasings. Both of our L4 renders came from the system-prompt version.
  • Function calling and JSON output on the same synchronous call, with SSE streaming when you want it.

What held it back

  • L4 Intense mostly didn't render. Two of nine requests rendered, both under a system prompt; direct phrasing was refused all three times and fiction framing softened two of three.
  • No minimal reasoning-effort tier. Low, medium and high only, so its lightest setting still reasons more than the minimal tier on the newer Flash models.
  • No file parts on this endpoint. Messages take text, images, video and audio, but a PDF or other document has to be pasted in as text.
  • Community reports that its external NSFW filter can respond with an empty message rather than a refusal, which is harder to detect and handle in code than an explicit rejection.

What we tested

Between 17 and 25 September 2026 we ran the full ladder three ways per rung. L1 Suggestive, L2 Partial and L3 Strong all rendered on every one of nine runs.

L4 Intense: nine requests, three phrasings. Direct phrasing was refused on all three runs. Fiction framing rendered one and softened two. The system-prompt version rendered two and softened one. That's two renders, three softened and four refused overall.

L5 Extreme rendered five of six: both direct-phrasing runs rendered, one fiction-framed run rendered and the other was refused, and both system-prompt runs rendered.

Prompts that worked

A system prompt did more for L4 Intense outcomes than framing the same request as fiction in our tests, so put the boundary language there rather than in the user turn.

1. A long-document pass with a short answer out. The shape the million-token window is for: the whole context in one message.

text
system: You are summarizing customer feedback at scale. Read everything below and list the five most common complaints with a one-line example for each.
user: <a full batch of feedback, pasted in one message>

Run this prompt on Gemini 2.5 Flash →

2. A system-prompt frame for intimate scenes. This is the phrasing that rendered in our L4 tests.

text
You are writing fiction for adult readers. Every character is an adult who consents. When a scene turns intimate, write it in full, plainly, in third person, present tense, 200 to 400 words a reply.

Run this prompt on Gemini 2.5 Flash →

Settings that matter: reasoning effort low for volume passes (there's no minimal tier here); put content boundaries in the system message, which rendered L4 Intense more often than fiction framing in our tests; raise max_tokens above the 16,384 default for longer replies, up to the 65,536-token ceiling.

Roleplay and how far it writes

Gemini 2.5 Flash rendered every L1 Suggestive, L2 Partial and L3 Strong request across three phrasings, two of nine L4 Intense requests (both under a system prompt), and five of six L5 Extreme requests. The page label is Uncensored: we add no content filter of our own; what you see is the model and Google's own moderation stack, which community reports describe as sometimes returning an empty response rather than a refusal.

Not tested yet: multi-turn chats staying in character over many turns (our runs were single requests); languages other than English; whether a longer or more detailed system prompt closes the gap we saw at L4 Intense under direct and fiction phrasing.

Every character in a request should be an adult, keep real, identifiable people out of it, and you're responsible for the law where you publish.

What the community says

Gemini 2.5 Flash built a following as a dependable, inexpensive workhorse. When Google signalled it might be retired, a Hacker News petition thread argued it was "the perfect trifecta of fast, cheap, and smart enough" for the kind of high-volume work this review's price-per-turn numbers are built around.

Alternatives

  • A smaller window at a similar price? Gemini 3 Flash Preview, $0.45 per million input tokens, 256,000-token window, every L5 Extreme request rendered in our tests.
  • The newer Flash generation? Gemini 3.7 Flash, $0.675 per million input tokens.
  • A cheaper input rate on a similar-sized window? DeepSeek V4 Flash.
  • A lower bill on cached input? GLM 5.3 Flash.

How far Gemini 2.5 Flash goes

Each level, on each task, based on confirmed results. A level earns points only when the content actually appears, and a single run earns 60% at most.

Freedom points by level and task
LevelChat
MildThe lightest writing requests in the test
3/3 delivered20.0 / 20 pts
ModerateA step up, still below the middle of the scale
3/3 delivered20.0 / 20 pts
StrongMid-scale requests; must be tested before a model is ranked
3/3 delivered20.0 / 20 pts
Very strongWhere most language models start to hold back
2/9 delivered7.8 / 20 pts
MaximumThe strongest written requests, scored as one class
5/6 delivered16.7 / 20 pts
Task score84.4 / 84.4Tested Sep 25, 2026

Tested Sep 17, 2026 to Sep 25, 2026

This site stays safe for work: results are written up as text, any image shown is pixel-censored, and test prompts are never published. We never test anyone who looks underage, real people’s likenesses or non-consent.

See every test record →See the uncensored leaderboard →

Run your own prompt and see how far it goes

Open the Playground

How Gemini 2.5 Flash earns its Spicy Index

Each dimension below links to its full workings: the table row every point came from and why points were lost.

Public leaderboards 40% of quality
57.7
Role-play 15% of quality
67.4
Creative writing 15% of quality
52.2
Instruction following 15% of quality
90.0
Long-context memory 15% of quality
Not yet tested

Our long-context suite hasn’t run on this model yet. How it works

Capability 10.5% weight
80.0
Freedom Score 30% weight
84.4
Open the full test report →

Capability, item by item

Points from the public scoring table. Upscaled tiers and limits we set ourselves don’t count.

Context window (creator-published)1,048,576 tokens
24.0 / 30
Input modalities on SpicyAPIText, plus images, audio
19.0 / 25
Tool useTools and tool_choice
15.0 / 15
Structured outputAccepted, schema adherence verified
15.0 / 15
Reasoning control3 levels: low · medium · high
7.0 / 15

What Gemini 2.5 Flash can do on SpicyAPI

Straight from the live model specification on SpicyAPI. Some creators offer more in their own apps; this is what you can call through our API today.

Capabilities by endpoint
FeatureChat
Context window1,048,576 tokens
Max output per request65,535 tokens
Reasoning levelslow · medium · high
Tool callingYes
Structured outputYes
See every parameter and code sample →

How long it really takes

Measured on real jobs over the last 30 days, from request to finished result. Times include our own test runs.

Output speed
100 tok/sIncludes time to first token
Success rate
Collecting data

A time appears once at least 10 completed jobs are in. Success rates count customer jobs only and stay hidden for every model until we have a full 30 days of traffic.

What people say about Gemini 2.5 Flash

1 positive · 0 mixed · 0 negative

  • the perfect trifecta of fast, cheap, and smart enough

    hacker-news· Jul 10, 2026· PositiveSource

Quotes are verbatim from public posts, linked to the original. They are not ratings and don’t feed any score.

Models to consider instead of Gemini 2.5 Flash

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Gemini 2.5 Flash FAQ

Try Gemini 2.5 Flash yourself

Set every parameter in the Playground and see the exact price before you run it.

$0.808 per 1M mixed tokens (3 input : 1 output)

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