Available Models

All 30+ AI models available on AJ STUDIOZ Cloud Infra

Overview

AJ STUDIOZ Cloud Infra hosts a curated selection of frontier open-weight AI models. All models are accessible through both the Ollama-compatible API and the OpenAI-compatible API.

Use the model name exactly as shown in the model column when making API requests.

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Flagship Models (100B+)

These are the most capable models for complex reasoning, coding, and agentic tasks.

Model Name	Size	Added	Best For
kimi-k2:1t	~1.1T	Sep 2025	Agentic tasks, long context
kimi-k2.5	~1.1T	Jan 2026	Next-gen reasoning
kimi-k2-thinking	~1.1T	Nov 2025	Chain-of-thought reasoning
qwen3.5:397b	397B	Feb 2026	Multilingual, reasoning
qwen3-coder:480b	480B	Jul 2025	State-of-the-art coding
qwen3-vl:235b	235B	Sep 2025	Vision + language
qwen3-vl:235b-instruct	235B	Sep 2025	Vision, instruction-tuned
cogito-2.1:671b	671B	Nov 2025	Scientific reasoning
deepseek-v3.1:671b	671B	Nov 2025	Coding, analysis
deepseek-v3.2	671B	Dec 2025	Latest DeepSeek release
glm-5	Large	Feb 2026	Long context, multilingual
glm-4.6	Large	Sep 2025	Balanced GLM model
glm-4.7	Large	Dec 2025	Latest GLM release
minimax-m2	230B	Oct 2025	Multimodal
minimax-m2.1	230B	Dec 2025	Enhanced multimodal
minimax-m2.5	230B	Feb 2026	Latest MiniMax model
mistral-large-3:675b	675B	Dec 2025	Multilingual excellence

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Large Models (20B–100B)

High-performance models with broad capability coverage.

Model Name	Size	Added	Best For
gpt-oss:120b	120B	Aug 2025	General purpose
devstral-2:123b	123B	Dec 2025	Code generation
qwen3-next:80b	80B	Sep 2025	Coding + reasoning
qwen3-coder-next	~82B	Feb 2025	Advanced code tasks
gemma3:27b	27B	Mar 2025	Balanced, fast
devstral-small-2:24b	24B	Dec 2025	Efficient code model
gemma3:12b	12B	Mar 2025	Fast inference
nemotron-3-nano:30b	30B	Dec 2025	NVIDIA specialized

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Small & Compact Models (≤20B)

Optimized for speed, low latency, and cost efficiency.

Model Name	Size	Added	Best For
gpt-oss:20b	20B	Aug 2025	Fast general purpose
rnj-1:8b	~16B	Dec 2025	Compact reasoning
ministral-3:14b	14B	Dec 2025	Efficient multilingual
ministral-3:8b	10.4B	Dec 2025	Balanced small model
gemma3:4b	8.6B	Mar 2025	Ultra-fast inference
ministral-3:3b	4.7B	Dec 2025	Fastest responses
gemini-3-flash-preview	—	Dec 2025	API-based, ultra-fast

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Full Model Catalog (JSON)

View raw model list (JSON)

{
  "models": [
    { "name": "gpt-oss:120b", "model": "gpt-oss:120b", "size": 65290180781, "digest": "d98fe6ba01e6" },
    { "name": "ministral-3:3b", "model": "ministral-3:3b", "size": 4670000000, "digest": "a1b2c3d40001" },
    { "name": "gemma3:4b", "model": "gemma3:4b", "size": 8600000000, "digest": "c1d2e3f40002" },
    { "name": "gemma3:27b", "model": "gemma3:27b", "size": 55000000000, "digest": "c1d2e3f40004" },
    { "name": "glm-5", "model": "glm-5", "size": 756162687872, "digest": "3f40c24f825c" },
    { "name": "kimi-k2.5", "model": "kimi-k2.5", "size": 1118481408000, "digest": "89c148d8ace8" },
    { "name": "qwen3-coder-next", "model": "qwen3-coder-next", "size": 81800000000, "digest": "d8f3c2a16e5b" },
    { "name": "ministral-3:8b", "model": "ministral-3:8b", "size": 10400000000, "digest": "a1b2c3d40003" },
    { "name": "cogito-2.1:671b", "model": "cogito-2.1:671b", "size": 688586727753, "digest": "5c1168f3a867" },
    { "name": "minimax-m2", "model": "minimax-m2", "size": 230000000000, "digest": "d46b950f79ba" },
    { "name": "devstral-2:123b", "model": "devstral-2:123b", "size": 128249391520, "digest": "de057a012512" },
    { "name": "qwen3-next:80b", "model": "qwen3-next:80b", "size": 81800000000, "digest": "aada434099ae" },
    { "name": "glm-4.6", "model": "glm-4.6", "size": 696060000000, "digest": "ee0873722cc3" },
    { "name": "glm-4.7", "model": "glm-4.7", "size": 696060000000, "digest": "8c95dad96c75" },
    { "name": "kimi-k2-thinking", "model": "kimi-k2-thinking", "size": 1118481408000, "digest": "7bb8dfabfd9c" },
    { "name": "gpt-oss:20b", "model": "gpt-oss:20b", "size": 13780162412, "digest": "05afbac4bad6" },
    { "name": "qwen3-vl:235b-instruct", "model": "qwen3-vl:235b-instruct", "size": 470000000000, "digest": "a5020f0cea71" },
    { "name": "ministral-3:14b", "model": "ministral-3:14b", "size": 15700000000, "digest": "a1b2c3d40005" },
    { "name": "devstral-small-2:24b", "model": "devstral-small-2:24b", "size": 51600000000, "digest": "de057a012512" },
    { "name": "gemini-3-flash-preview", "model": "gemini-3-flash-preview", "size": 0, "digest": "f1e2c3f40001" },
    { "name": "deepseek-v3.1:671b", "model": "deepseek-v3.1:671b", "size": 688586727753, "digest": "e1c8a9725f49" },
    { "name": "minimax-m2.5", "model": "minimax-m2.5", "size": 230000000000, "digest": "1361fbbdd94e" },
    { "name": "gemma3:12b", "model": "gemma3:12b", "size": 24000000000, "digest": "c1d2e3f40003" },
    { "name": "qwen3.5:397b", "model": "qwen3.5:397b", "size": 397000000000, "digest": "b909ca2f1b7f" },
    { "name": "kimi-k2:1t", "model": "kimi-k2:1t", "size": 1118481408000, "digest": "9665a13eb6f1" },
    { "name": "nemotron-3-nano:30b", "model": "nemotron-3-nano:30b", "size": 32645090390, "digest": "a4b4f1851393" },
    { "name": "mistral-large-3:675b", "model": "mistral-large-3:675b", "size": 682000000000, "digest": "f7e3b2a16d5c" },
    { "name": "rnj-1:8b", "model": "rnj-1:8b", "size": 16000000000, "digest": "385d8e8f6803" },
    { "name": "qwen3-coder:480b", "model": "qwen3-coder:480b", "size": 510492157952, "digest": "653ca2ec1d71" },
    { "name": "deepseek-v3.2", "model": "deepseek-v3.2", "size": 688586727753, "digest": "a403a93c7b13" },
    { "name": "qwen3-vl:235b", "model": "qwen3-vl:235b", "size": 470000000000, "digest": "d8afd22a6506" },
    { "name": "minimax-m2.1", "model": "minimax-m2.1", "size": 230000000000, "digest": "a7c3e1f98b2d" }
  ]
}

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Retrieve via API

You can also retrieve the model list dynamically:

curl https://api.ajstudioz.co.in/api/tags \
  -H "Authorization: Bearer YOUR_API_KEY"

List Models API Reference