> For the complete documentation index, see [llms.txt](https://docs.cortensor.network/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.cortensor.network/technical-architecture/supported-models.md).

# Supported Models

Cortensor runs a curated catalog of **open-weight LLMs** across two primary engines:

* **Llamafile** – quantized GGUF models (CPU-friendly, can also use GPU where available)
* **Ollama** – full GPU models (for higher-end / dedicated GPU miners)

Internally, each model is packaged as a **Docker image** identified as:

* `cts-llm`, `cts-llm-1`, `cts-llm-2`, … `cts-llm-40`

These **`cts-llm-*` IDs are Docker image tags**, not the raw model names.\
Each image wraps one runtime engine (**llamafile** or **Ollama**) and one concrete model identifier (e.g. `deepseek-r1:8b-gpu`).

> ❗ This catalog will grow over time. New images will be added with higher IDs (`cts-llm-41`, `cts-llm-42`, …), so treat the tables below as **versioned snapshots** rather than a permanent, fixed list.

***

### Quantized Models (Llamafile)

**Engine:** `llamafile`\
**Indexes:** `0–11`\
**Hardware:** CPU-first, can use GPU where available\
**Purpose:** Maximum coverage across heterogeneous nodes (CPUs, smaller GPUs, edge machines) using **4–8 bit quantization**.

These images are ideal for:

* Nodes without a dedicated GPU
* Mixed-resource environments (small VPS, home PCs, edge hardware)
* High fan-out / broad geographic coverage

#### Model Families Covered

The current llamafile set includes quantized versions of:

* **Vision / Multimodal**
  * `llava-v1.5-7b-q4` (used as `default-gpu` on many nodes)
* **Reasoning & General LLMs**
  * **DeepSeek R1 Distill Llama 8B** (Q4)
  * **Meta Llama 3.1 8B Instruct** (Q4)
  * **Mistral 7B Instruct v0.3** (Q4)
  * **Granite 3.2 8B Instruct** (Q4)
  * **Qwen2.5 7B Instruct 1M** (Q4)
* **High-Capacity & Coder Variants**
  * **Qwen QwQ 32B** (Q4)
  * **Qwen3 4B** (Q8)
  * **Gemma 3 4B / 12B IT** (Q6 / Q4)
  * **DeepSeek R1 Distill Qwen 14B** (Q4)
  * **Qwen2.5 Coder 14B Instruct** (Q4)

These quantized models prioritize:

* Lower memory footprint
* Broad participation from smaller nodes
* “Good enough” quality for many general-purpose workloads and background jobs

***

### Full GPU Models (Ollama)

**Engine:** `ollama`\
**Indexes:** `12–40`\
**Hardware:** GPU nodes (NVIDIA strongly preferred)\
**Purpose:** High-quality, low-latency inference for more demanding workloads and higher-SLA routes.

These are **full GPU models** (not llamafile-style Q4/Q6 GGUFs). They are meant for:

* Dedicated or strong GPU miners
* Latency-sensitive user requests
* High-quality routing tiers

#### Model Families Covered

The current Ollama set spans several major model families:

* **Gemma 3**
  * 270M, 4B, 12B, 27B
* **DeepSeek R1**
  * 8B, 14B, 70B
* **GPT-OSS**
  * 20B, 120B
* **Granite**
  * Granite 4 3B
* **Ministral / Mistral**
  * Ministral 3 8B / 14B
  * Mistral 7B
* **Qwen 3 & Qwen 3 VL**
  * Qwen3 4B / 8B
  * Qwen3 VL 4B / 8B
* **Phi**
  * Phi-3 3.8B / 14B
  * Phi-4 14B
* **Llama 3.x**
  * Llama 3.2 1B / 3B
  * Llama 3.1 8B / 70B
* **Others**
  * Dolphin 3 8B
  * TinyLLaMA 1.1B
  * Falcon 3 3B / 7B / 10B

These are best suited to:

* Nodes with enough VRAM to serve these models efficiently
* High-SLA task classes
* Scenarios where quality/latency > footprint

***

### How the Mapping Works

At the **node / Docker level**, you mostly deal with:

* `cts-llm-*` → **Docker image ID**
* Each image contains:
  * The **engine** (`llamafile` or `ollama`)
  * The **model identifier** (e.g. `deepseek-r1:8b-gpu`, `Qwen2.5-7B-Instruct-1M-Q4_K_M`)

At the **network / session level**, Cortensor can:

* Route tasks by **model index** (0–40)
* Or use more descriptive labels via config/SDKs where needed

As we add more models, we’ll extend the table with new indices and images; this section stays as the canonical mapping.

***

### Appendix: Full Model Mapping

Below are the **current** model mappings used by Cortensor.

> 🧩 **Columns**
>
> * **Index** – numeric model index used in configs / selection
> * **Docker Image ID** – the `cts-llm-*` tag
> * **Engine** – `llamafile` or `ollama`
> * **Model Identifier** – actual model/runtime name inside the image
> * **Model Family / Size** – human-readable description
> * **Quantized?** – whether it’s a quantized GGUF (for llamafile) or full GPU model

***

#### Quantized Models – Llamafile (`0–11`)

| Index | Docker Image ID | Engine    | Model Identifier                                                       | Model Family / Size          | Quantized?  |
| ----: | --------------- | --------- | ---------------------------------------------------------------------- | ---------------------------- | ----------- |
|     0 | `cts-llm`       | llamafile | <p><code>default</code></p><p><code>default-gpu</code> (llamafile)</p> | LLaVA v1.5 7B Q4             | Yes – 4-bit |
|     1 | `cts-llm-1`     | llamafile | `DeepSeek-R1-Distill-Llama-8B-Q4_K_M`                                  | DeepSeek R1 Distill Llama 8B | Yes – 4-bit |
|     2 | `cts-llm-2`     | llamafile | `Meta-Llama-3.1-8B-Instruct.Q4_K_M`                                    | Llama 3.1 8B Instruct        | Yes – 4-bit |
|     3 | `cts-llm-3`     | llamafile | `Qwen_QwQ-32B-Q4_K_M`                                                  | Qwen QwQ 32B                 | Yes – 4-bit |
|     4 | `cts-llm-4`     | llamafile | `Mistral-7B-Instruct-v0.3.Q4_0`                                        | Mistral 7B Instruct v0.3     | Yes – 4-bit |
|     5 | `cts-llm-5`     | llamafile | `granite-3.2-8b-instruct-Q4_K_M`                                       | Granite 3.2 8B Instruct      | Yes – 4-bit |
|     6 | `cts-llm-6`     | llamafile | `Qwen2.5-7B-Instruct-1M-Q4_K_M`                                        | Qwen2.5 7B Instruct 1M       | Yes – 4-bit |
|     7 | `cts-llm-7`     | llamafile | `google_gemma-3-4b-it-Q6_K`                                            | Gemma 3 4B IT                | Yes – 6-bit |
|     8 | `cts-llm-8`     | llamafile | `Qwen_Qwen3-4B-Q8_0`                                                   | Qwen3 4B                     | Yes – 8-bit |
|     9 | `cts-llm-9`     | llamafile | `google_gemma-3-12b-it-Q4_K_M`                                         | Gemma 3 12B IT               | Yes – 4-bit |
|    10 | `cts-llm-10`    | llamafile | `DeepSeek-R1-Distill-Qwen-14B-Q4_K_M`                                  | DeepSeek R1 Distill Qwen 14B | Yes – 4-bit |
|    11 | `cts-llm-11`    | llamafile | `Qwen2.5-Coder-14B-Instruct-Q4_K_M`                                    | Qwen2.5 Coder 14B Instruct   | Yes – 4-bit |

***

#### Full GPU Models – Ollama (`12–40`)

| Index | Docker Image ID | Engine | Model Identifier      | Model Family / Size | Quantized?                     |
| ----: | --------------- | ------ | --------------------- | ------------------- | ------------------------------ |
|    12 | `cts-llm-12`    | ollama | `gemma3:270m-gpu`     | Gemma 3 270M        | No – full GPU                  |
|    13 | `cts-llm-13`    | ollama | `gpt-oss:20b-gpu`     | GPT-OSS 20B         | No – full GPU                  |
|    14 | `cts-llm-14`    | ollama | `deepseek-r1:8b-gpu`  | DeepSeek R1 8B      | No – full GPU                  |
|    15 | `cts-llm-15`    | ollama | `granite4:3b-gpu`     | Granite 4 3B        | No – full GPU                  |
|    16 | `cts-llm-16`    | ollama | `gpt-oss:120b-gpu`    | GPT-OSS 120B        | No – full GPU                  |
|    17 | `cts-llm-17`    | ollama | `deepseek-r1:70b-gpu` | DeepSeek R1 70B     | No – full GPU                  |
|    18 | `cts-llm-18`    | ollama | `gemma3:4b-gpu`       | Gemma 3 4B          | No – full GPU                  |
|    19 | `cts-llm-19`    | ollama | `gemma3:12b-gpu`      | Gemma 3 12B         | No – full GPU                  |
|    20 | `cts-llm-20`    | ollama | `ministral-3:8b-gpu`  | Ministral 3 8B      | No – full GPU                  |
|    21 | `cts-llm-21`    | ollama | `deepseek-r1:14b-gpu` | DeepSeek R1 14B     | No – full GPU                  |
|    22 | `cts-llm-22`    | ollama | `gemma3:27b-gpu`      | Gemma 3 27B         | No – full GPU                  |
|    23 | `cts-llm-23`    | ollama | `qwen3-vl:4b-gpu`     | Qwen3 VL 4B         | No – full GPU (vision-capable) |
|    24 | `cts-llm-24`    | ollama | `qwen3-vl:8b-gpu`     | Qwen3 VL 8B         | No – full GPU (vision-capable) |
|    25 | `cts-llm-25`    | ollama | `ministral-3:14b-gpu` | Ministral 3 14B     | No – full GPU                  |
|    26 | `cts-llm-26`    | ollama | `qwen3:4b-gpu`        | Qwen3 4B            | No – full GPU                  |
|    27 | `cts-llm-27`    | ollama | `qwen3:8b-gpu`        | Qwen3 8B            | No – full GPU                  |
|    28 | `cts-llm-28`    | ollama | `mistral:7b-gpu`      | Mistral 7B          | No – full GPU                  |
|    29 | `cts-llm-29`    | ollama | `phi3:3.8b-gpu`       | Phi-3 3.8B          | No – full GPU                  |
|    30 | `cts-llm-30`    | ollama | `phi3:14b-gpu`        | Phi-3 14B           | No – full GPU                  |
|    31 | `cts-llm-31`    | ollama | `llama3:1b-gpu`       | Llama 3.2 1B        | No – full GPU                  |
|    32 | `cts-llm-32`    | ollama | `llama3:3b-gpu`       | Llama 3.2 3B        | No – full GPU                  |
|    33 | `cts-llm-33`    | ollama | `llama3:8b-gpu`       | Llama 3.1 8B        | No – full GPU                  |
|    34 | `cts-llm-34`    | ollama | `llama3:70b-gpu`      | Llama 3.1 70B       | No – full GPU                  |
|    35 | `cts-llm-35`    | ollama | `phi4:14b-gpu`        | Phi-4 14B           | No – full GPU                  |
|    36 | `cts-llm-36`    | ollama | `dolphin3:8b-gpu`     | Dolphin 3 8B        | No – full GPU                  |
|    37 | `cts-llm-37`    | ollama | `tinyllama1.1b-gpu`   | TinyLLaMA 1.1B      | No – full GPU                  |
|    38 | `cts-llm-38`    | ollama | `falcon3:3b-gpu`      | Falcon 3 3B         | No – full GPU                  |
|    39 | `cts-llm-39`    | ollama | `falcon3:7b-gpu`      | Falcon 3 7B         | No – full GPU                  |
|    40 | `cts-llm-40`    | ollama | `falcon3:10b-gpu`     | Falcon 3 10B        | No – full GPU                  |