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)
OpenAI: GPT-6 Astra Pro
Sakana: Fugu Ultra
Difference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$1,750
$975
Sakana: Fugu Ultra saves $775
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$1,700
$900
Sakana: Fugu Ultra saves $800
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)
$1,800
$960
Sakana: Fugu Ultra saves $840
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$1,100
$580
Sakana: Fugu Ultra saves $520
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$550
$280
Sakana: Fugu Ultra saves $270
Capabilities side by side
Capability
OpenAI: GPT-6 Astra Pro
Sakana: Fugu Ultra
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
—
—
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
✓ Yes
✓ Yes
answer from live web results
Seed (reproducible sampling)
✓ Yes
—
repeat a generation for tests and evals
Log-probabilities
—
—
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
OpenAI: GPT-6 Astra Pro: price unchanged since we started tracking it on 2026-09-05.
Sakana: Fugu Ultra: price unchanged since we started tracking it on 2026-08-06.
Which should you choose?
Choose OpenAI: GPT-6 Astra Pro if…
you need file / PDF input — to accept documents without your own parsing step; Sakana: Fugu Ultra does not advertise it
you need seed (reproducible sampling) — to repeat a generation for tests and evals; Sakana: Fugu Ultra does not advertise it
Choose Sakana: Fugu Ultra if…
cost matters at scale — it is 44% cheaper on a typical 3:1 input/output mix ($975 vs $1,750 a month for 50,000 support chats)
Frequently asked questions
Is OpenAI: GPT-6 Astra Pro better than Sakana: Fugu Ultra?
Neither wins outright: OpenAI: GPT-6 Astra Pro is the pick when you need file / PDF input, Sakana: Fugu Ultra when cost matters at scale. In short: OpenAI: GPT-6 Astra Pro when you need file / PDF input, you need seed (reproducible sampling); Sakana: Fugu Ultra when cost matters at scale.
Which is cheaper, OpenAI: GPT-6 Astra Pro or Sakana: Fugu Ultra?
Sakana: Fugu Ultra is cheaper: $11.25 vs $20.00 per 1M tokens at a typical 3:1 input/output mix, 44% less. For 50,000 support conversations a month that is $975 against $1,750.
How much do OpenAI: GPT-6 Astra Pro and Sakana: Fugu Ultra cost per million tokens?
OpenAI: GPT-6 Astra Pro costs $10.00 per 1M input tokens and $50.00 per 1M output tokens; Sakana: Fugu Ultra costs $5.00 input and $30.00 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, OpenAI: GPT-6 Astra Pro or Sakana: Fugu Ultra?
OpenAI: GPT-6 Astra Pro: 1.1M tokens, about 1,575 pages, against 1M (about 1,500 pages) for Sakana: Fugu Ultra.
Do OpenAI: GPT-6 Astra Pro and Sakana: Fugu Ultra support function calling and JSON output?
GPT-6 Astra Pro is the same underlying model as [GPT-6 Astra](https://openrouter.ai/openai/gpt-6-astra), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. **Cost note:** pro mode spends far more...
Fugu Ultra is the higher-performance model in Sakana AI's Fugu family. Rather than a single monolithic model, Fugu is a learned multi-agent orchestration system: a language model trained to route...