Japanese Stable Diffusion Xl

Fireworks AI image generation

Japanese Stable Diffusion Xl is a Fireworks AI image generation model.It supports a 4,096-token context windowwith up to 4,096 output tokens. Route Japanese Stable Diffusion Xl via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.

Pricing source: unknown Last verified: Oct 22, 2026 View source ↗
Pricing not yet public

We don't have verified per-token pricing for Japanese Stable Diffusion Xl yet. If you have a source from Fireworks AI's documentation, help us add it — your submission gets reviewed within 48 hours.

Pricing

Per-token rates, expressed in USD per 1M tokens. Verified Oct 22, 2026.

Input —
Output —

Context & limits

Context window
4,096 tokens
Max input
4,096 tokens
Max output
4,096 tokens
Modalities
image, text

Capabilities

  • Function calling — not advertised
  • Parallel tool calls — not advertised
  • Vision input — not advertised
  • Audio input — not advertised
  • Audio output — not advertised
  • PDF input — not advertised
  • Streaming ✓ supported
  • Structured output — not advertised
  • Prompt caching — not advertised
  • Reasoning — not advertised

Strengths & caveats — when to pick Japanese Stable Diffusion Xl

Data-driven from Japanese Stable Diffusion Xl's percentile within image generation peers.

Where it's strong

Watch out for

  • !small context (under 16K tokens)

Benchmarks pending

We haven't logged public benchmark scores for Japanese Stable Diffusion Xl yet. Have one to contribute? Submit a source — citations help us prioritise.

Try it

Call Japanese Stable Diffusion Xl via Agent Command Center

One OpenAI-compatible endpoint. Routing, fallback, semantic caching, guardrails, and cost tracking come along for the ride. First 100K requests + 100K cache hits free every month.

SDK
Native Future AGI client (agentcc / @agentcc/client). Per-call metadata — provider, cost, latency, cache hit, request id — is returned on x-agentcc-* response headers, so any HTTP client can read it.
# Japanese Stable Diffusion Xl via the Agent Command Center Python SDK
# pip install agentcc
import os
from agentcc import AgentCC

client = AgentCC(
    api_key=os.environ["AGENTCC_API_KEY"],   # from app.futureagi.com → Settings → API Keys
    base_url="https://gateway.futureagi.com/v1",
)

resp = client.chat.completions.create(
    model="fireworks-ai/accounts-fireworks-models-japanese-stable-diffusion-xl",
    messages=[{"role": "user", "content": "Hello, Japanese Stable Diffusion Xl!"}],
)

print(resp.choices[0].message.content)
print(f"Tokens: {resp.usage.total_tokens}")

# Per-call gateway metadata is returned on x-agentcc-* response headers.
# When you need it programmatically, use .with_raw_response to get them:
raw = client.chat.completions.with_raw_response.create(
    model="fireworks-ai/accounts-fireworks-models-japanese-stable-diffusion-xl",
    messages=[{"role": "user", "content": "Same call, but I want the headers."}],
)
print("Provider:", raw.headers.get("x-agentcc-provider"))
print("Latency:", raw.headers.get("x-agentcc-latency-ms"), "ms")
print("Cost:   ", raw.headers.get("x-agentcc-cost"), "USD")
print("Cache:  ", raw.headers.get("x-agentcc-cache"))
Set AGENTCC_API_KEY with a key fromapp.futureagi.com.Gateway docs ↗

Explore similar models

Japanese Stable Diffusion Xl doesn't have a public Arena ELO score yet, so we group by provider only — quality-tier comparisons need a benchmark. Side-by-side links appear where a comparison page exists; otherwise, open the model profile.

FAQ

How much does Japanese Stable Diffusion Xl cost?

Public per-token pricing for Japanese Stable Diffusion Xl is not yet published. Submit a source on this page to help us add it.

What is the context window of Japanese Stable Diffusion Xl?

Japanese Stable Diffusion Xl supports a 4,096-token context window with up to 4,096 output tokens.

Does Japanese Stable Diffusion Xl support function calling?

Japanese Stable Diffusion Xl does not currently advertise function-calling support. For agentic workloads, prefer a tool-calling-capable model and route via Agent Command Center for fallback.

Is Japanese Stable Diffusion Xl good for production?

Japanese Stable Diffusion Xl is best evaluated against your own production traces. Pipe traffic through Agent Command Center to compare it head-to-head against alternatives in shadow mode.

How can I route to Japanese Stable Diffusion Xl with fallback?

Use Agent Command Center: a single OpenAI-compatible endpoint that supports cost-optimized routing, latency-aware retries, model fallback, and shadow traffic. Configure once, swap models without app changes.

Useful links for Japanese Stable Diffusion Xl

Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.