ultramarine-1-flash
Fireworks AI/🇺🇸 US/chat
Ultramarine 1 Flash by Paper Instruments is a multimodal model built for knowledge work in enterprise operations, finance, law and consulting. Based on GLM 5.3 Flash (320B total, 18B active MoE) with a 1M token context window and native image input. Served on Fireworks serverless in the United States. Function calling is not supported.MoreLess
Which id to call
fireworks/ultramarine-1-flashThis exact deployment on Fireworks AI, with no routing and no failover. Send it as the model field.
Input /1M
$0.22
$0.04 cached
Output /1M
$0.75
3.3x input
Context
1.0M
tokens
Added
Oct 2026
chat
Capabilities 3/8
Provider rates
What ultramarine-1-flash costs
Provider prices per 1M tokens, updated October 30, 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
$0.22
Output /1M
$0.75
Cache write /1M
-
Cache read /1M
$0.04
What a workload costs
- 100K input + 10K output
- $0.0300
- 1M input + 100K output
- $0.30
- 10M input + 1M output
- $3.00
At the rates above, before caching. A cache read costs $0.04 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 fireworks/ultramarine-1-flash. 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="fireworks/ultramarine-1-flash", 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 Fireworks AI models overview.
Same provider
More from Fireworks AI
Newest first, on the same provider and the same key.
Reference
ultramarine-1-flash questions
How much does ultramarine-1-flash cost?
ultramarine-1-flash is priced at $0.22 per million input tokens and $0.75 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 ultramarine-1-flash?
ultramarine-1-flash has a context window of 1.0M tokens. That's roughly 1,398 words of input you can fit in a single prompt.
What can ultramarine-1-flash do?
ultramarine-1-flash supports vision input, extended reasoning, prompt caching. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use ultramarine-1-flash 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 "fireworks/ultramarine-1-flash". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run ultramarine-1-flash through Requesty?
Yes. ultramarine-1-flash runs through Requesty's OpenAI-compatible API, served from Fireworks AI. You do not host the model yourself: point base_url at Requesty, set the model to "fireworks/ultramarine-1-flash", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.
Call ultramarine-1-flash through one endpoint
One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.