Google: Gemini 2.5 Flash Lite Preview 09-2025 vs Particle AI: Particle-1
Neither wins outright: Google: Gemini 2.5 Flash Lite Preview 09-2025 is the pick when cost matters at scale, Particle AI: Particle-1 when you need log-probabilities.
Monthly cost at list price for five common workloads. Token counts per unit are stated so you can scale them to your own traffic. A workload that does not fit a model's context window is marked rather than priced.
Workload (per month)
Google: Gemini 2.5 Flash Lite Preview 09-2025
Particle AI: Particle-1
Difference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$15.50
$38.75
Google: Gemini 2.5 Flash Lite Preview 09-2025 saves $23.25
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$16.00
$40.00
Google: Gemini 2.5 Flash Lite Preview 09-2025 saves $24.00
Coding / tool-using agent
2,000 tasks — each a multi-step task with tool calls and file context (60,000 in / 6,000 out tokens)
$16.80
$42.00
Google: Gemini 2.5 Flash Lite Preview 09-2025 saves $25.20
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$10.40
$26.00
Google: Gemini 2.5 Flash Lite Preview 09-2025 saves $15.60
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$5.40
$13.50
Google: Gemini 2.5 Flash Lite Preview 09-2025 saves $8.10
Capabilities side by side
Capability
Google: Gemini 2.5 Flash Lite Preview 09-2025
Particle AI: Particle-1
What it lets you do
Tool / function calling
✓ Yes
✓ Yes
call your APIs and run agent loops
Structured output (JSON schema)
✓ Yes
✓ Yes
return JSON that validates against your schema
Reasoning / thinking mode
✓ Yes
✓ Yes
spend extra tokens thinking before answering hard problems
Image input
✓ Yes
✓ Yes
read screenshots, charts and scanned pages
Audio input
✓ Yes
—
take speech or audio directly
File / PDF input
✓ Yes
—
accept documents without your own parsing step
Image output
—
—
generate images, not just text
Built-in web search
—
—
answer from live web results
Seed (reproducible sampling)
✓ Yes
✓ Yes
repeat a generation for tests and evals
Log-probabilities
—
✓ Yes
read token confidence for classification and scoring
From each model's published parameters and input/output types. “—” means not advertised, not proven absent.
Price history
Google: Gemini 2.5 Flash Lite Preview 09-2025: price unchanged since we started tracking it on 2026-03-10.
Particle AI: Particle-1: price unchanged since we started tracking it on 2026-10-29.
Which should you choose?
Choose Google: Gemini 2.5 Flash Lite Preview 09-2025 if…
cost matters at scale — it is 60% cheaper on a typical 3:1 input/output mix ($15.50 vs $38.75 a month for 50,000 support chats)
you need audio input — to take speech or audio directly; Particle AI: Particle-1 does not advertise it
you need file / PDF input — to accept documents without your own parsing step; Particle AI: Particle-1 does not advertise it
Choose Particle AI: Particle-1 if…
you need log-probabilities — to read token confidence for classification and scoring; Google: Gemini 2.5 Flash Lite Preview 09-2025 does not advertise it
you generate long outputs in one go — up to 131K tokens (about 98,300 words) per response
you want the newer model — released 2026-10-28, 13 months after the other
Frequently asked questions
Is Google: Gemini 2.5 Flash Lite Preview 09-2025 better than Particle AI: Particle-1?
Neither wins outright: Google: Gemini 2.5 Flash Lite Preview 09-2025 is the pick when cost matters at scale, Particle AI: Particle-1 when you need log-probabilities. In short: Google: Gemini 2.5 Flash Lite Preview 09-2025 when cost matters at scale, you need audio input, you need file / PDF input; Particle AI: Particle-1 when you need log-probabilities, you generate long outputs in one go, you want the newer model.
Which is cheaper, Google: Gemini 2.5 Flash Lite Preview 09-2025 or Particle AI: Particle-1?
Google: Gemini 2.5 Flash Lite Preview 09-2025 is cheaper: $0.18 vs $0.44 per 1M tokens at a typical 3:1 input/output mix, 60% less. For 50,000 support conversations a month that is $15.50 against $38.75.
How much do Google: Gemini 2.5 Flash Lite Preview 09-2025 and Particle AI: Particle-1 cost per million tokens?
Google: Gemini 2.5 Flash Lite Preview 09-2025 costs $0.10 per 1M input tokens and $0.40 per 1M output tokens; Particle AI: Particle-1 costs $0.25 input and $1.00 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, Google: Gemini 2.5 Flash Lite Preview 09-2025 or Particle AI: Particle-1?
Both take 1.0M tokens per request — roughly 1,573 pages of text.
Do Google: Gemini 2.5 Flash Lite Preview 09-2025 and Particle AI: Particle-1 support function calling and JSON output?
Can Google: Gemini 2.5 Flash Lite Preview 09-2025 or Particle AI: Particle-1 read images?
Yes, both accept image input.
Is Google: Gemini 2.5 Flash Lite Preview 09-2025 or Particle AI: Particle-1 free to use?
No free variant is listed for either; both are pay-per-token.
What is the maximum output length of Google: Gemini 2.5 Flash Lite Preview 09-2025 and Particle AI: Particle-1?
Google: Gemini 2.5 Flash Lite Preview 09-2025 can write up to 66K tokens (about 49,200 words) per response; Particle AI: Particle-1 up to 131K (about 98,300 words).
When were Google: Gemini 2.5 Flash Lite Preview 09-2025 and Particle AI: Particle-1 released?
Google: Gemini 2.5 Flash Lite Preview 09-2025 was listed on 2025-09-25; Particle AI: Particle-1 on 2026-10-28.
Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance across common benchmarks compared to earlier Flash models. By default, "thinking" (i.e. multi-pass reasoning) is disabled to prioritize speed, but developers can enable it via the [Reasoning API parameter](https://openrouter.ai/docs/use-cases/reasoning-tokens) to selectively trade off cost for intelligence.
Particle-1 is a token-efficient agentic coding model from Particle AI, post-trained on DeepSeek V4.1 Flash. It is suited for software engineering work such as terminal workflows, codebase changes, and data...