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

# ValarCode models

> The open-weight coding targets and the frontier Claude tiers, and how each harness is served

ValarCode routes to two kinds of models: open-weight coding models, which are where the savings come from, and the frontier Claude tiers, which are your baseline. A cohort can point any alias at either kind.

## Open-weight coding models

These are the cheaper targets you route traffic to. They are regular catalog models, and ValarCode prices each request at the model's **Now** tier rate, which you can see on the [Pricing](/pricing) page.

| Model           | Model id                      | Maker       |
| --------------- | ----------------------------- | ----------- |
| GLM-5.2         | `zai-org/GLM-5.2`             | Z.ai        |
| GLM-5.2 Fast    | `zai-org/GLM-5.2-fast`        | Z.ai        |
| Kimi-K3         | `moonshotai/Kimi-K3`          | Moonshot AI |
| Kimi-K2.7       | `moonshotai/Kimi-K2.7`        | Moonshot AI |
| DeepSeek-V4-Pro | `deepseek-ai/DeepSeek-V4-Pro` | DeepSeek AI |

## Frontier Claude tiers

These stand in for the Opus, Sonnet, Haiku, and Fable classes your harness asks for, and they are the baseline that savings are measured against. They are also the fallback when a key's routing cannot be read.

| Alias  | Fallback target  |
| ------ | ---------------- |
| Opus   | Claude Opus 5    |
| Sonnet | Claude Sonnet 5  |
| Haiku  | Claude Haiku 4.5 |
| Fable  | Claude Fable 5   |

Claude Opus 4.8 and Sonnet 4.6 are also selectable in the routing picker, though nothing falls back to them.

<Note>
  The frontier Claude tiers are specific to ValarCode routing. They do not appear on the public [Models](/models) page and are not callable as standalone models from the Responses or Chat Completions APIs. They exist so a cohort can hold a Claude baseline and so savings compare against real Claude list prices.
</Note>

## How each harness is served

ValarCode meets each tool on its own API:

| Harness                | API                     | Endpoint               |
| ---------------------- | ----------------------- | ---------------------- |
| Claude Code            | Anthropic Messages      | `/v1/messages`         |
| Claude Desktop         | Anthropic Messages      | `/v1/messages`         |
| Pi                     | Anthropic Messages      | `/v1/messages`         |
| VS Code (Copilot Chat) | Anthropic Messages      | `/v1/messages`         |
| Codex                  | OpenAI Responses        | `/v1/responses`        |
| Cursor                 | OpenAI Chat Completions | `/v1/chat/completions` |

Every endpoint requires a coding key. Requests are forwarded to the resolved target model, and the response is rewritten so the model your harness sees is the one it asked for. That keeps the harness working across restarts, whatever target actually served the request.

Whatever the target, Valar serves it on throughput-optimized inference tuned for agentic workloads. That highly efficient serving is what makes the open-weight models a practical everyday default rather than something you reach for only on cheap background work.

## Next steps

<CardGroup cols={2}>
  <Card title="Model routing" icon="route" href="/valarcode/routing">
    Point each alias at one of these models per cohort.
  </Card>

  <Card title="Analytics & savings" icon="chart-line" href="/valarcode/analytics">
    See the served-model mix and per-model savings.
  </Card>
</CardGroup>