particle-1
Particle/🇺🇸 US/chat
Particle-1 is Particle AI's own frontier model, built for chat, agentic coding and tool calling workloads. It offers a 1M token context window, up to 131K output tokens, native image input and adjustable reasoning effort from none to max, with thinking on by default at high effort. Supports OpenAI style tools and tool_choice, JSON object output and prompt caching.MoreLess
Which id to call
particle/particle-1This exact deployment on Particle, with no routing and no failover. Send it as the model field.
Input /1M
$0.25
$0.03 cached
Output /1M
$1.00
4.0x input
Context
1.0M
131K output
Added
Oct 2026
chat
Capabilities 4/8
Provider rates
What particle-1 costs
Provider prices per 1M tokens, updated October 29, 2026.moreless
These are the upstream provider rates. Pay as you go adds 5%, or 0% if you bring your own keys, and there is no per-request fee. Prompt caching and routing change what you pay against these rates, not the rates themselves.
Input /1M
$0.25
Output /1M
$1.00
Cache write /1M
-
Cache read /1M
$0.03
What a workload costs
- 100K input + 10K output
- $0.0350
- 1M input + 100K output
- $0.35
- 10M input + 1M output
- $3.50
At the rates above, before caching. A cache read costs $0.03 per 1M, so repeated context lands under these figures.
OpenAI compatible
Call it in three lines
Change the base url, use your Requesty key, set the model to particle/particle-1. Existing OpenAI SDK code needs no other edit.
123456789101112131415from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1", ) response = client.chat.completions.create( model="particle/particle-1", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)
Reference
Specs and data terms
What the catalog reports for this deployment, and what the provider does with the traffic.
Public leaderboards
Benchmark scores
Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.
No benchmarks are published for this exact variant yet.
Region-specific deployments and highspeed tiers usually share scores with their base model. Try the base model page or the Particle models overview.
Reference
particle-1 questions
How much does particle-1 cost?
particle-1 is priced at $0.25 per million input tokens and $1.00 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.
What is the context window of particle-1?
particle-1 has a context window of 1.0M tokens, with a maximum output of 131K tokens per response. That's roughly 1,398 words of input you can fit in a single prompt.
What can particle-1 do?
particle-1 supports vision input, tool calling, extended reasoning, prompt caching. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use particle-1 with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "particle/particle-1". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run particle-1 through Requesty?
Yes. particle-1 runs through Requesty's OpenAI-compatible API, served from Particle. You do not host the model yourself: point base_url at Requesty, set the model to "particle/particle-1", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.
Call particle-1 through one endpoint
One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.