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

# Claude Sonnet 4.6

> The current production Sonnet — same context as 4.5 with measurably better tool use and code generation. Default Anthropic mid-tier.

**Vendor:** Anthropic
**Model ID:** `claude-sonnet-4-6`
**Capability:** 200K context · tool use · vision · prompt caching · streaming
**Pricing:** per-token, Sonnet tier ([live rate](https://bytespike.ai/pricing#text))

Sonnet 4.6 is what you should reach for first inside the 4-series. It
keeps the 200K context window and tool-use shape of 4.5, while
delivering measurably better structured output and tighter tool-call
arguments. If you're starting a new project, default here. If you're on
4.5, the migration is a single string change — most production code
sees a quality bump with no measurable latency or cost difference.

## Request

```bash theme={null}
curl https://llm.bytespike.ai/v1/messages \
  -H "x-api-key: $BYTESPIKE_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "content-type: application/json" \
  -d '{
    "model": "claude-sonnet-4-6",
    "max_tokens": 4096,
    "messages": [
      {"role": "user", "content": "Extract the dates from this paragraph as JSON."}
    ]
  }'
```

### Body parameters

| Field         | Type            | Required | Default           | Notes                                     |
| ------------- | --------------- | -------- | ----------------- | ----------------------------------------- |
| `model`       | string          | yes      | —                 | `claude-sonnet-4-6`                       |
| `messages`    | array           | yes      | —                 | Conversation history.                     |
| `max_tokens`  | integer         | yes      | —                 | Hard cap. Max for this model: 16384.      |
| `system`      | string \| array | no       | —                 | Array form supports `cache_control`.      |
| `temperature` | number          | no       | 1.0               | Range 0.0–1.0.                            |
| `top_p`       | number          | no       | 1.0               | Nucleus sampling.                         |
| `tools`       | array           | no       | —                 | Supported, including parallel tool calls. |
| `tool_choice` | object          | no       | `{"type":"auto"}` | `auto` / `any` / `tool` (named).          |
| `stream`      | boolean         | no       | false             | SSE streaming.                            |

## Response

```json theme={null}
{
  "id": "msg_sonnet_…",
  "type": "message",
  "role": "assistant",
  "model": "claude-sonnet-4-6",
  "content": [
    {"type": "text", "text": "[\"2024-08-12\", \"2024-09-01\"]"}
  ],
  "stop_reason": "end_turn",
  "usage": {
    "input_tokens": 87,
    "output_tokens": 24
  }
}
```

## Code examples

<CodeGroup>
  ```bash cURL theme={null}
  curl https://llm.bytespike.ai/v1/messages \
    -H "x-api-key: $BYTESPIKE_API_KEY" \
    -H "anthropic-version: 2023-06-01" \
    -H "content-type: application/json" \
    -d '{
      "model": "claude-sonnet-4-6",
      "max_tokens": 4096,
      "messages": [{"role": "user", "content": "Extract the dates from this paragraph as JSON."}]
    }'
  ```

  ```python Python theme={null}
  import anthropic

  client = anthropic.Anthropic(
      base_url="https://llm.bytespike.ai/v1",
      api_key="$BYTESPIKE_API_KEY",
  )

  message = client.messages.create(
      model="claude-sonnet-4-6",
      max_tokens=4096,
      messages=[
          {"role": "user", "content": "Extract the dates from this paragraph as JSON."}
      ],
  )

  print(message.content[0].text)
  ```

  ```javascript Node theme={null}
  import Anthropic from "@anthropic-ai/sdk"

  const client = new Anthropic({
    baseURL: "https://llm.bytespike.ai/v1",
    apiKey: process.env.BYTESPIKE_API_KEY,
  })

  const message = await client.messages.create({
    model: "claude-sonnet-4-6",
    max_tokens: 4096,
    messages: [
      { role: "user", content: "Extract the dates from this paragraph as JSON." },
    ],
  })

  console.log(message.content[0].text)
  ```
</CodeGroup>

## Streaming

Set `"stream": true` for SSE in the standard Anthropic format. Estimated
credits ship in the HTTP headers before the first event.

## Cache control

`cache_control` blocks reduce cost on repeated prompts. Cache reads at
the discounted rate visible in the
[pricing table](https://bytespike.ai/pricing#text). With Sonnet 4.6's
tighter tool-arg generation, retrieval-augmented agent loops see the
biggest cache wins (system prompt + tool schema kept stable, only the
user turn changes).

```json theme={null}
{
  "model": "claude-sonnet-4-6",
  "system": [
    {
      "type": "text",
      "text": "<long static system prompt>",
      "cache_control": {"type": "ephemeral"}
    }
  ],
  "messages": [...]
}
```

## Errors

| Code | Trigger                           | Billed?                  |
| ---- | --------------------------------- | ------------------------ |
| 400  | Body validation failed            | No                       |
| 401  | Missing / revoked key             | No                       |
| 402  | Wallet exhausted                  | No                       |
| 403  | Scope denied / IP not allowlisted | No                       |
| 429  | Rate-limited                      | No                       |
| 5xx  | Upstream provider issue           | No (auto-retry envelope) |

## When to use

* Default Anthropic mid-tier — start here, benchmark against Opus / Haiku later.
* Code generation / refactoring / structured extraction where Haiku is too imprecise.
* Tool-heavy agents where parallel tool calls and tight argument JSON matter.
* For higher throughput at lower quality, see [Haiku 4.5](/api-reference/text/claude-haiku-4-5).
* For deeper reasoning across long contexts, see [Opus 4.7](/api-reference/text/claude-opus-4-7).

## Limits

| Limit                   | Value          |
| ----------------------- | -------------- |
| Context window          | 200K tokens    |
| Max output              | 16384 tokens   |
| Supports tool use       | Yes (parallel) |
| Supports vision         | Yes            |
| Supports streaming      | Yes            |
| Supports prompt caching | Yes            |