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New Models Added: GLM-5.1, GLM-5v-Turbo, Nemotron-3-120B, Gemma 4, Qwen3.6-Plus, and Qwen-Image-2.0

Date: 2026-04-12 / (1405-01-23)

Summary

We announce the addition of eight new models: Z.AI's GLM-5.1 flagship model with state-of-the-art agentic coding performance and GLM-5v-Turbo multimodal model, NVIDIA Nemotron-3-120B-A12B via Cloudflare AI with 1M context window, Google's Gemma 4 open models (26B and 31B variants) with industry-leading efficiency, Alibaba's Qwen3.6-Plus with enhanced agentic capabilities and 1M context, and Qwen-Image-2.0 series for professional typography and photorealistic image generation.

Details

Z.AI (GLM)

GLM-5.1

glm-5.1 is Z.AI's next-generation flagship model for agentic engineering, with significantly stronger coding capabilities than its predecessor. It achieves state-of-the-art performance on SWE-Bench Pro (58.4%) and leads GLM-5 by a wide margin on NL2Repo (repo generation) and Terminal-Bench 2.0 (real-world terminal tasks).

Feature	Details
Context window	200,000 tokens
Input pricing	$1.54 / 1M tokens
Cached input pricing	$0.286 / 1M tokens (81% cost reduction)
Output pricing	$4.84 / 1M tokens
Input modalities	Text
Output modalities	Text
Supported endpoints	`v1/chat/completions`

Key Features:

State-of-the-Art on SWE-Bench Pro: 58.4% performance, leading all models including GPT-5.4 and Claude Opus 4.6
Long-Horizon Optimization: Sustains productive optimization over 600+ iterations with 6,000+ tool calls
Agentic Engineering: Built for sustained effectiveness on agentic tasks over extended sessions
Complex Problem Solving: Breaks down complex problems, runs experiments, reads results, and identifies blockers with precision
Self-Revision: Revisits reasoning and revises strategy through repeated iteration
Function Calling: Full support for tool use and external integrations
Structured Outputs: Return responses in specific, organized formats

Benchmark Performance:

SWE-Bench Pro: 58.4% (SOTA)
NL2Repo: 42.7%
Terminal-Bench 2.0: 63.5%
AIME 2026: 95.3%
GPQA-Diamond: 86.2%
HLE (with tools): 52.3%

GLM-5v-Turbo

glm-5v-turbo is Z.AI's multimodal vision model optimized for high-throughput visual understanding tasks.

Feature	Details
Context window	200,000 tokens
Input pricing	$1.20 / 1M tokens
Cached input pricing	$0.24 / 1M tokens (80% cost reduction)
Output pricing	$4.00 / 1M tokens
Input modalities	Text, Image
Output modalities	Text
Supported endpoints	`v1/chat/completions`

Key Features:

Vision Understanding: Process and analyze images with high accuracy
Multi-Image Support: Handle multiple images in a single request
High-Throughput: Optimized for fast visual processing
Context Caching: 80% cost reduction on cached inputs
Function Calling: Full tool support with visual inputs
Streaming: Real-time streaming responses

Cloudflare AI

Nemotron-3-120B-A12B

cf.nemotron-3-120b-a12b is NVIDIA's latest Nemotron model available via Cloudflare AI. This hybrid LatentMoE architecture uses Mamba-2 + MoE + Attention with 120B total parameters (12B active), designed for agentic workflows, long-context reasoning, and high-volume workloads.

Feature	Details
Total Parameters	120B (12B active)
Architecture	LatentMoE - Mamba-2 + MoE + Attention hybrid with Multi-Token Prediction
Context window	1,000,000 tokens
Input pricing	$0.50 / 1M tokens
Cached input pricing	$0.05 / 1M tokens (90% cost reduction)
Output pricing	$1.50 / 1M tokens
Input modalities	Text
Output modalities	Text
Supported languages	English, French, German, Italian, Japanese, Spanish, Chinese
Supported endpoints	`v1/chat/completions`

Key Features:

1M Context Window: Industry-leading context length for extensive documents and conversations
Agentic Workflows: Optimized for collaborative agents and high-volume workloads like IT ticket automation
Configurable Reasoning: Enable or disable reasoning mode via chat template
Multi-Token Prediction: MTP layers for faster text generation and improved quality
Tool Use & RAG: Excellent for tool calling and retrieval-augmented generation
Cost-Effective: Only 12B active parameters for exceptional efficiency

Benchmark Highlights:

SWE-Bench (OpenHands): 60.47%
AIME 2025: 90.21%
HMMT Feb 2025 (with tools): 94.73%
LiveCodeBench: 81.19%

Google

Gemma 4-26B-A4B-IT

gemma-4-26b-a4b-it is Google's open model built from Gemini 3 research, delivering unprecedented intelligence-per-parameter with Mixture-of-Experts architecture (26B total, 4B active).

Feature	Details
Total Parameters	26B (4B active)
Architecture	Mixture-of-Experts (MoE)
Context window	128,000 tokens
Input pricing	$0.13 / 1M tokens
Cached input pricing	$0.013 / 1M tokens (90% cost reduction)
Output pricing	$0.40 / 1M tokens
Input modalities	Text, Image, Audio
Output modalities	Text
Supported languages	140 languages
Supported endpoints	`v1/chat/completions`, `v1/responses`

Key Features:

Frontier Intelligence: Built from Gemini 3 research for maximum intelligence-per-parameter
MoE Architecture: 26B total parameters with only 4B active for efficiency
Multimodal: Strong audio and visual understanding
Agentic Workflows: Native support for function calling and autonomous agents
140 Languages: Multilingual support that goes beyond translation
Thinking Mode: Extended reasoning for complex problems
Consumer GPU: Optimized to run on personal computers

Benchmark Performance:

Arena AI (text): 1441
MMMLU: 82.6%
MMMU Pro: 73.8%
AIME 2026: 88.3%
LiveCodeBench v6: 77.1%
GPQA Diamond: 82.3%

Gemma 4-31B-IT

gemma-4-31b-it is the dense variant of Gemma 4, offering maximum capability for users who prefer full parameter utilization.

Feature	Details
Parameters	31B
Architecture	Dense Transformer
Context window	128,000 tokens
Input pricing	$0.14 / 1M tokens
Cached input pricing	$0.014 / 1M tokens (90% cost reduction)
Output pricing	$0.40 / 1M tokens
Input modalities	Text, Image, Audio
Output modalities	Text
Supported languages	140 languages
Supported endpoints	`v1/chat/completions`

Key Features:

Industry-Leading Efficiency: Top Arena AI ELO score (1452) for its size class
Dense Architecture: Full 31B parameters active for maximum capability
Multimodal Reasoning: Strong audio and visual understanding
Agentic Workflows: Native function calling and agent support
Fine-Tuning: Improve performance for specific tasks using your preferred frameworks
Thinking Mode: Extended reasoning capabilities

Benchmark Performance:

Arena AI (text): 1452
MMMLU: 85.2%
MMMU Pro: 76.9%
AIME 2026: 89.2%
LiveCodeBench v6: 80.0%
GPQA Diamond: 84.3%
τ2-bench Retail: 86.4%

Alibaba (Qwen)

Qwen3.6-Plus

qwen3.6-plus is Alibaba's latest flagship model with massive capability upgrades, featuring a 1M context window by default, significantly improved agentic coding capabilities, and better multimodal perception and reasoning.

Feature	Details
Context window	1,000,000 tokens (default)
Input pricing	$0.50 / 1M tokens
Input pricing (above 256K)	$2.00 / 1M tokens
Cache creation	$0.625 / 1M tokens
Cache creation (above 256K)	$2.50 / 1M tokens
Cached input pricing	$0.05 / 1M tokens (90% cost reduction)
Cached input (above 256K)	$0.20 / 1M tokens
Output pricing	$3.00 / 1M tokens
Output pricing (above 256K)	$6.00 / 1M tokens
Input modalities	Text, Image
Output modalities	Text
Supported endpoints	`v1/chat/completions`

Key Features:

1M Context Window: Default million-token context for extensive documents and conversations
SOTA Agentic Coding: From frontend web development to complex repository-level problem solving
Enhanced Multimodal: Greater accuracy and sharper multimodal reasoning
Coding Agent Excellence: 78.8% on SWE-bench Verified, 61.6% on Terminal-Bench 2.0
Deep Planning: 41.5% on DeepPlanning benchmark (leading performance)
MCP Support: 48.2% on MCPMark for Model Context Protocol integration
Tool Decathlon: Strong performance across diverse tool-use scenarios

Benchmark Performance:

SWE-bench Verified: 78.8%
SWE-bench Multilingual: 73.8%
SWE-bench Pro: 56.6%
Terminal-Bench 2.0: 61.6%
TAU3-Bench: 70.7%
DeepPlanning: 41.5%
MCPMark: 48.2%
MMLU-Pro: 88.5%
SuperGPQA: 71.6%

Qwen-Image-2.0-Pro

qwen-image-2.0-pro is Alibaba's next-generation professional image generation model with advanced typography rendering, supporting 1K-token instructions for direct generation of professional infographics including PPTs, posters, and comics.

Feature	Details
Resolution	Native 2K (2048×2048)
Input pricing	$0.00 / request
Output pricing	$75.00 / 1M tokens ($0.075 / image)
Input modalities	Text, Image
Output modalities	Image
Supported endpoints	`/v1/images/generations`, `/v1/images/edits`

Key Features:

Professional Typography: 1K-token instruction support for PPTs, posters, and infographics
Complex Layout: Pixel-perfect multi-script layout with sophisticated text-image composition
Native 2K Resolution: 2048×2048 for finely detailed realistic scenes
Unified Model: Generation and editing in a single model
Photorealism: Microscopic detail on skin pores, fabric weave, architectural textures
Multiple Calligraphic Styles: Support for various script styles and fonts
Image Editing: Full support for image-to-image editing tasks

Qwen-Image-2.0

qwen-image-2.0 is the standard version of Qwen-Image-2.0, offering the same advanced capabilities at a more accessible price point.

Feature	Details
Resolution	Native 2K (2048×2048)
Input pricing	$0.00 / request
Output pricing	$35.00 / 1M tokens ($0.035 / image)
Input modalities	Text, Image
Output modalities	Image
Supported endpoints	`/v1/images/generations`, `/v1/images/edits`

Key Features:

Typography Rendering: Support for professional text-in-image generation
Native 2K Resolution: High-quality image output
Unified Model: Generation and editing capabilities combined
Strong Semantic Adherence: Accurate prompt following
Lighter Architecture: Smaller model size with faster inference
Cost-Effective: Accessible pricing for high-volume usage

API Request/Response Examples

GLM-5.1 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-5.1",
    "messages": [
      {
        "role": "user",
        "content": "Write a Python function that finds the longest common subsequence of two strings using dynamic programming."
      }
    ]
  }'

Response

json

{
  "id": "chatcmpl-1234567890",
  "created": 1744483200,
  "model": "glm-5.1",
  "object": "chat.completion",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "message": {
        "content": "Here's a Python function that finds the longest common subsequence using dynamic programming:\n\n
```python\ndef longest_common_subsequence(s1: str, s2: str) -> str:\n    m, n = len(s1), len(s2)\n    dp = [[0] * (n + 1) for _ in range(m + 1)]\n    \n    for i in range(1, m + 1):\n        for j in range(1, n + 1):\n            if s1[i-1] == s2[j-1]:\n                dp[i][j] = dp[i-1][j-1] + 1\n            else:\n                dp[i][j] = max(dp[i-1][j], dp[i][j-1])\n    \n    # Backtrack to find the LCS\n    lcs = []\n    i, j = m, n\n    while i > 0 and j > 0:\n        if s1[i-1] == s2[j-1]:\n            lcs.append(s1[i-1])\n            i -= 1\n            j -= 1\n        elif dp[i-1][j] > dp[i][j-1]:\n            i -= 1\n        else:\n            j -= 1\n    \n    return ''.join(reversed(lcs))\n```",
        "role": "assistant"
      }
    }
  ],
  "usage": {
    "completion_tokens": 285,
    "prompt_tokens": 28,
    "total_tokens": 313
  },
  "estimated_cost": {
    "unit": "0.001423",
    "irt": 142.30,
    "exchange_rate": 100000
  }
}

Gemma 4 Example

Request

bash

curl https://api.avalai.ir/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $AVALAI_API_KEY" \
  -d '{
    "model": "gemma-4-31b-it",
    "messages": [
      {
        "role": "user",
        "content": "Explain the concept of mixture-of-experts architecture in neural networks."
      }
    ]
  }'

Response

json

{
  "id": "chatcmpl-gemma4-9876543210",
  "created": 1744483200,
  "model": "gemma-4-31b-it",
  "object": "chat.completion",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "message": {
        "content": "Mixture-of-Experts (MoE) is a neural network architecture that uses multiple specialized sub-networks (experts) with a gating mechanism to route inputs to the most relevant experts...",
        "role": "assistant"
      }
    }
  ],
  "usage": {
    "completion_tokens": 250,
    "prompt_tokens": 18,
    "total_tokens": 268
  },
  "estimated_cost": {
    "unit": "0.000103",
    "irt": 10.3,
    "exchange_rate": 100000
  }
}

Qwen-Image-2.0 Example

Request

bash

curl https://api.avalai.ir/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $AVALAI_API_KEY" \
  -d '{
    "model": "qwen-image-2.0",
    "prompt": "A professional infographic poster showing AI model comparison with clean typography and modern design",
    "n": 1,
    "size": "1024x1024"
  }'

Response

json

{
  "created": 1744483200,
  "data": [
    {
      "url": "https://api.avalai.ir/files/generated/img-abc123...",

      "revised_prompt": "A professional infographic poster showing AI model comparison with clean typography and modern design"
    }
  ],
  "estimated_cost": {
    "unit": "0.035",
    "irt": 3500.00,
    "exchange_rate": 100000
  }
}

Pricing Summary

Model	Input	Cached Input	Output	Special
glm-5.1	$1.54/1M	$0.286/1M	$4.84/1M	-
glm-5v-turbo	$1.20/1M	$0.24/1M	$4.00/1M	-
cf.nemotron-3-120b-a12b	$0.50/1M	$0.05/1M	$1.50/1M	1M context
gemma-4-26b-a4b-it	$0.13/1M	$0.013/1M	$0.40/1M	-
gemma-4-31b-it	$0.14/1M	$0.014/1M	$0.40/1M	-
qwen3.6-plus	$0.50/1M	$0.05/1M	$3.00/1M	$2.00/$6.00 above 256K
qwen-image-2.0-pro	Free	Free	$0.075/image	-
qwen-image-2.0	Free	Free	$0.035/image	-

New Models Added: GLM-5.1, GLM-5v-Turbo, Nemotron-3-120B, Gemma 4, Qwen3.6-Plus, and Qwen-Image-2.0 ​

Summary ​

Details ​

Z.AI (GLM) ​

GLM-5.1 ​

GLM-5v-Turbo ​

Cloudflare AI ​

Nemotron-3-120B-A12B ​

Google ​

Gemma 4-26B-A4B-IT ​

Gemma 4-31B-IT ​

Alibaba (Qwen) ​

Qwen3.6-Plus ​

Qwen-Image-2.0-Pro ​

Qwen-Image-2.0 ​

API Request/Response Examples ​

GLM-5.1 Example ​

Request ​

Response ​

Gemma 4 Example ​

Request ​

Response ​

Qwen-Image-2.0 Example ​

Request ​

Response ​

Pricing Summary ​

Documentation Links ​

New Models Added: GLM-5.1, GLM-5v-Turbo, Nemotron-3-120B, Gemma 4, Qwen3.6-Plus, and Qwen-Image-2.0

Summary

Details

Z.AI (GLM)

GLM-5.1

GLM-5v-Turbo

Cloudflare AI

Nemotron-3-120B-A12B

Google

Gemma 4-26B-A4B-IT

Gemma 4-31B-IT

Alibaba (Qwen)

Qwen3.6-Plus

Qwen-Image-2.0-Pro

Qwen-Image-2.0

API Request/Response Examples

GLM-5.1 Example

Request

Response

Gemma 4 Example

Request

Response

Qwen-Image-2.0 Example

Request

Response

Pricing Summary

Documentation Links