> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cogito.decart.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Model catalog

> Available open-source models, with context windows, output caps, throughput, and pricing.

Cogito serves a curated set of frontier open-source models — **Kimi K2.6 · GLM-5.2 · GPT-OSS · Qwen**.

The full served catalog below. We add models the day they ship; older models stay supported with deprecation notice.

| Model | Family | Context | Max output | TPS | License |
| - | - | - | - | - | - |
| `moonshotai/kimi-k2.6` | Moonshot | 256K | 256K | 70 | Modified MIT |
| `moonshotai/kimi-k2.6:ultra-fast-new` | Moonshot | 9K | 8K | 70 | Modified MIT |
| `zai-org/GLM-5.2-NVFP4` | Zhipu | 1M | 1M | 70 | MIT |
| `gpt-oss-120b` | OpenAI | 128K | 32K | 70 | Apache 2.0 |
| `qwen-3-235b` | Alibaba | 256K | 32K | 70 | Apache 2.0 |

**Live pricing** — input, cached input, and output rates per model — is published on the [model catalog](https://cogito.decart.ai/models) and returned by `GET /v1/models`. Single source of truth so the website, the gateway, and your code never drift.

For Kimi K2.6 routes, Moonshot documents the limit as input plus output fitting within the 256K context window; Cogito therefore advertises a 256K max-output cap while upstream may still reject requests whose prompt leaves insufficient room.

**Throughput** is locked at 70 tokens/sec across the fleet for the MVP — we run a uniform serving target while we tune Trainium / GPU autoscaling. Real-world per-request throughput varies with prompt length and concurrent batch saturation.

**Hardware** is managed by Cogito. We route each model to the right silicon for the workload and may transparently shift between tiers if it produces lower P99 — output is bit-identical either way.

## Capabilities

All catalog models support:

* Streaming SSE
* Function / tool calling (OpenAI-shape `tools[]`)
* Multi-turn chat with system prompts

Models that advertise `structured_outputs` from `GET /v1/models` also support
Structured JSON outputs through grammar-constrained decoding. Routes that omit
that feature, including GPT-OSS and current ultra-fast TPU preview lanes, reject
enforced `response_format` requests with a 400.

## Picking a model

* **Frontier reasoning + long context** → `zai-org/GLM-5.2-NVFP4`. 1M-token window, strong coding and agentic reasoning.
* **Coding agents and tool-heavy workflows** → `moonshotai/kimi-k2.6`. Served from the AWS B300 high-capacity route.
* **TPU preview Kimi requests** → `moonshotai/kimi-k2.6:ultra-fast-new`. Dedicated `new-kimi` Basalt TPU lane with a 9,216-token context limit.
* **Cheap general chat / coding** → `gpt-oss-120b`. Cheapest path to GPT-4-class output quality.
* **Multilingual + tool use** → `qwen-3-235b`. Strong non-English coverage.

For more on each model, see the per-model pages in the sidebar.


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