CogView-4
CogView-4 on LLM.API gives product and marketing teams a programmable image generation image model behind one endpoint.
What is CogView-4?
Use CogView-4 when you need programmable stills from prompts. Image generation model by Zai. LLM.API surfaces it as `cogview-4` so design and growth teams can share infrastructure with engineering.
Providers
LLM.API routes CogView-4 to the providers below, with discounted effective rates versus list price.
List price by provider ($ / 1M tokens)
InputOutputProvider list prices; the LLM.API discount applies on top.
| Provider | Pricing | Context | Capabilities |
|---|---|---|---|
| — | 2K tokens | tools |
Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 21 Sept 2026.
Try this model
Test CogView-4 right here — free to start.
Suggestions for your first prompt
Code snippet
Call CogView-4 through the OpenAI-compatible API — POST /v1/images/generations.
from openai import OpenAI
client = OpenAI(
api_key="YOUR_LLMAP_KEY",
base_url="https://api.llmapi.ai/v1",
)
resp = client.images.generate(
model="cogview-4",
prompt="A clean product photo on a soft gradient background",
size="1024x1024",
)
print(resp.data[0].url){
"model": "cogview-4",
"prompt": "A clean product photo on a soft gradient background",
"size": "1024x1024"
}5 Core Capabilities
Asset drafting
Produces draft creatives that humans can refine in design tools. Tuned to how teams typically call CogView-4.
Text-to-image generation
Creates images from natural-language prompts for product, marketing, and creative workflows. Relevant for `cogview-4` workloads on LLM.API.
Prompt fidelity
Aims to honor subject, composition, and attribute constraints in the prompt. Tuned to how teams typically call CogView-4.
Brand moodboarding
Useful for assembling visual directions and campaign moodboards. Grounded in the model's image role rather than generic chat claims.
Scene composition
Handles multi-element scenes when prompts are specific and structured. Grounded in the model's image role rather than generic chat claims.
6 Most Valuable Use Cases
- Storyboard stills for video briefs with CogView-4
- Packaging and label style ideation
- Rapid A/B visual testing of messaging themes with CogView-4
- Thumbnail and cover image exploration
- Product concept art before photoshoot or 3D with CogView-4
- Ad creative drafts for paid social campaigns
Why Build on LLM.API?
One unified API. Every major model. Built-in reliability, cost control, and observability.
-
Intelligent AI Routing
Automatically route each request to the best model across providers based on latency, cost, and quality—without changing your integration or redeploying code.
One endpoint, every model. -
Cost-Aware Execution
Control spend with per-request cost estimation, smart model selection, and centralized quotas so teams can experiment fast without runaway bills or manual tracking.
More performance, less spend. -
Resilient Fallback Flows
Define automatic, provider-agnostic fallbacks to keep your app up during outages, rate limits, or timeouts—no brittle failover logic scattered through your codebase.
Never go dark on users. -
Deep LLM Observability
Trace every call across providers with logs, metrics, and request replay so you can debug, tune prompts, and optimize model choices from one unified dashboard.
See every token, everywhere. -
Task-Level Orchestration
Describe tasks, not models. LLM.API maps them to the right tools, models, and prompts so you ship complex AI workflows with minimal glue code.
Think tasks, not models. -
High-Throughput Batch APIs
Process millions of inferences efficiently with optimized batch pipelines, concurrency controls, and retry logic—all behind the same simple interface you use for single calls.
Scale from 1 to millions.
Why run CogView-4 on LLM.API?
Unified AI Routing
Reach CogView-4 and sibling models through one OpenAI-compatible endpoint.
Cost Control
Compare provider price points and keep spend visible as you scale CogView-4.
Reliability Layer
Production: Retry and route across configured providers when a single upstream blips.
Observability
Trace prompts, tokens, and errors for CogView-4 alongside the rest of your stack.
Drop-in SDKs
Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.
Model Breadth
Swap CogView-4 for chat, media, or embedding alternatives without rewriting auth.
When to Use — When NOT to Use
Use it if...
- You need programmatic image generation from text prompts (CogView-4)
- Your pipeline can accept image outputs asynchronously or via URLs/base64 (CogView-4)
- You want creative drafts without standing up a separate image vendor SDK (CogView-4)
Avoid if...
- You need pixel-perfect brand assets with legal trademark fidelity every time
- You need long-form video rather than still images
- You require deterministic identical frames across runs
Frequently Asked Questions
Which providers serve CogView-4?
LLM.API currently lists: zai. Availability can vary by region and account.
Is CogView-4 a chat model?
No—CogView-4 is categorized as a image model. Use the matching API surface rather than assuming chat completions.
What is CogView-4?
Image generation model by Zai. On LLM.API it is addressed as `cogview-4`.
Where is the canonical page for CogView-4?
https://llmapi.ai/models/cogview-4/
What modalities does CogView-4 support?
CogView-4 accepts text and produces image according to its architecture metadata on LLM.API.
Can I use tools or structured outputs with CogView-4?
Tool and/or structured-output flags appear on one or more providers for this model—confirm in the providers table.
Are CogView-4 images unique each time?
Generative images typically vary between runs; do not expect bitwise-identical outputs.
How do I call CogView-4 via API?
Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "cogview-4" and your LLM.API key. See the code snippet on this page.
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