Developer Dashboard

New Models Added: GLM-5, Gen-4.5, and Seedream 4.5

Date: 2026-02-14 / (1404-11-26)

Summary

AvalAI introduces three new AI models: GLM-5 from Z.AI, a flagship foundation model with SOTA performance in coding and agentic tasks; Gen-4.5 from RunwayML, the world's top-rated video generation model with unprecedented visual fidelity; and Seedream 4.5 from BytePlus, an advanced image generation model with improved multi-image editing and typography capabilities.


Details

Z.AI

We announce access to GLM-5 (glm-5), Z.AI's flagship foundation model designed for Agentic Engineering. Documentation

Key Features:

  • Agentic Engineering: Designed for complex system engineering and long-range Agent tasks
  • SOTA Coding Performance: Achieves 77.8 on SWE-bench Verified and 56.2 on Terminal Bench 2.0, the highest among open-weight models
  • Coding on Par with Claude Opus 4.5: Performance alignment with Claude Opus 4.5 in software engineering tasks
  • 200K Context Window: Extended context with 128K maximum output tokens
  • Advanced Capabilities: Thinking mode, streaming output, function calling, context caching, structured output
  • Larger Model Scale: 744B parameters (40B activated) with 28.5T pre-training data
  • Endpoint Support: Available on v1/chat/completions
FeatureDetails
Model IDglm-5
Context window200,000 tokens
Maximum output128,000 tokens
CapabilitiesChat, Function Calling, Structured Outputs, Reasoning, Deep Thinking
Input pricing$1.10 / 1M tokens
Cached input pricing$0.22 / 1M tokens
Output pricing$3.52 / 1M tokens

Use Cases:

  • Agentic coding and autonomous software development
  • Long-range Agent tasks with multiple steps
  • Role-playing with consistent character settings
  • Script and storyboard generation
  • Professional translation
  • Text data extraction from contracts and financial reports

RunwayML

We announce access to Gen-4.5 (gen4.5), RunwayML's latest video generation model with state-of-the-art motion quality and visual fidelity. Documentation

Key Features:

  • World's Top-Rated Video Model: 1,247 Elo points on Artificial Analysis Text to Video benchmark
  • State-of-the-Art Quality: Unprecedented visual fidelity and precise prompt adherence
  • Physical Accuracy: Realistic physics with proper dynamics, collisions, and natural movement
  • Complex Scene Rendering: Intricate, multi-element scenes with detailed compositions
  • Expressive Characters: Nuanced emotions, natural gestures, and lifelike facial detail
  • Temporal Consistency: Maintains coherence across motion and time
  • Endpoint Support: Available on v1/videos
FeatureDetails
Model IDgen4.5
TypeVideo Generation
Duration2-10 seconds
Resolutions1280x720, 720x1280, 1920x1080, 1080x1920, and more
Pricing$0.12 per second of video

BytePlus

We announce access to Seedream 4.5 (seedream-4-5-251128), BytePlus's upgraded image generation model with enhanced multi-image editing and typography capabilities. Documentation

Key Features:

  • All-Round Improvement: Overall scaling of the model for enhanced quality
  • Multi-Image Editing: Accurately identifies main subjects in multi-image editing
  • Reference Image Preservation: Strictly preserves the details of reference images
  • Enhanced Typography: Further improves dense text rendering capabilities
  • Professional Visuals: Delivers professional visual creatives with high consistency and fidelity
  • Endpoint Support: Available on v1/images/generations and v1/images/edit
FeatureDetails
Model IDseedream-4-5-251128
TypeImage Generation & Editing
Max Resolution4K (4096x4096 pixels)
Pricing$0.04 per image

Pricing Summary

ModelProviderTypePricing
glm-5Z.AIChatInput: $1.10/1M, Cached: $0.22/1M, Output: $3.52/1M
gen4.5RunwayMLVideo$0.12 per second
seedream-4-5-251128BytePlusImage$0.04 per image

API Request/Response Examples

GLM-5 Chat Example

Request

bash
curl https://api.avalai.ir/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $AVALAI_API_KEY" \
  -d '{
    "model": "glm-5",
    "messages": [
      {
        "role": "user",
        "content": "Implement a binary search tree with AVL balancing in Python."
      }
    ],
    "max_tokens": 4096,
    "temperature": 0.6
  }'

Response

json
{
  "id": "chatcmpl-abc123",
  "created": 1739574109,
  "model": "glm-5",
  "object": "chat.completion",
  "system_fingerprint": null,
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "message": {
        "content": "Here's a complete implementation of an AVL tree in Python...",
        "role": "assistant",
        "thinking_blocks": [],
        "annotations": []
      }
    }
  ],
  "usage": {
    "completion_tokens": 512,
    "prompt_tokens": 20,
    "total_tokens": 532
  },
  "estimated_cost": {
    "unit": "0.0018254000",
    "irt": 239.89,
    "exchange_rate": 131350
  }
}

Gen-4.5 Video Generation Example

Request

bash
curl -X POST "https://api.avalai.ir/v1/videos" \
  -H "Authorization: Bearer $AVALAI_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "prompt=A cinematic shot of a whale flying through a winter mountain range with clouds." \
  -F "model=gen4.5" \
  -F "size=1920x1080" \
  -F "seconds=5" \
  -F "input_reference=@reference_image.jpeg;type=image/jpeg"

Response

json
{
  "id": "video_abc123",
  "object": "video",
  "status": "processing",
  "model": "gen4.5",
  "created": 1739574109,
  "prompt": "A cinematic shot of a whale flying through a winter mountain range with clouds.",
  "request_id": "req_xyz789"
}

Seedream 4.5 Image Generation Example

Request

bash
curl https://api.avalai.ir/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $AVALAI_API_KEY" \
  -d '{
    "model": "seedream-4-5-251128",
    "prompt": "Professional product photography of a luxury watch on marble surface",
    "size": "2K",
    "response_format": "url",
    "sequential_image_generation": "disabled",
    "watermark": false
  }'

Response

json
{
  "created": 1739574109,
  "data": [
    {
      "url": "https://api.avalai.ir/generated/image_abc123.png",

      "revised_prompt": null
    }
  ],
  "estimated_cost": {
    "unit": "0.04",
    "irt": 5254.00,
    "exchange_rate": 131350
  }
}

SDK Usage Examples

GLM-5 with Python

python
from openai import OpenAI

client = OpenAI(api_key="your-avalai-api-key", base_url="https://api.avalai.ir/v1")

response = client.chat.completions.create(
    model="glm-5",
    messages=[
        {
            "role": "user",
            "content": "Design a microservices architecture for an e-commerce platform.",
        }
    ],
    max_tokens=4096,
    temperature=0.6,
)

print(response.choices[0].message.content)

Gen-4.5 Video Generation with Python

python
from openai import OpenAI
import time

client = OpenAI(api_key="your-avalai-api-key", base_url="https://api.avalai.ir/v1")

# Create video generation request
video = client.videos.create(
    model="gen4.5",
    prompt="A close-up of a young woman with striking features and platinum blonde hair.",
    input_reference=open("portrait_reference.jpeg", "rb"),
    size="1920x1080",
    seconds="5",
)

print(f"Video generation started: {video.id}")

# Poll for completion
while True:
    video_status = client.videos.retrieve(video.id)

    if video_status.status == "completed":
        print(f"Video ready! ID: {video.id}")
        # Download the video
        with client.with_streaming_response.videos.retrieve_content(
            video.id
        ) as response:
            with open("output.mp4", "wb") as f:
                for chunk in response.iter_bytes():
                    f.write(chunk)
        break
    elif video_status.status == "failed":
        print(f"Generation failed: {video_status.error}")
        break

    time.sleep(10)

Seedream 4.5 Image Generation with Python

python
from openai import OpenAI

client = OpenAI(api_key="your-avalai-api-key", base_url="https://api.avalai.ir/v1")

response = client.images.generate(
    model="seedream-4-5-251128",
    prompt="A professional product shot with enhanced typography showing 'SALE 50% OFF'",
    size="2K",
    response_format="url",
    extra_body={"sequential_image_generation": "disabled", "watermark": False},
)

print(f"Generated image: {response.data[0].url}")