> ## 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 Opus 4.7 > Prior-generation Opus, superseded by Claude Opus 4.8 — 200K context, top-of-line reasoning, the model to reach for when one shot has to be right. **Vendor:** Anthropic **Model ID:** `claude-opus-4-7` **Capability:** 200K context · tool use · vision · prompt caching · streaming · extended thinking **Pricing:** per-token, Opus tier ([live rate](https://bytespike.ai/pricing#text)) Opus 4.7 is the prior-generation Opus, now superseded by [Claude Opus 4.8](/models/claude-opus-4-8) as the flagship. It is still the model you reach for when the one shot has to be right. It's slower than Sonnet, more expensive than Sonnet, and noticeably better at the things Sonnet starts cutting corners on: long-context reasoning, multi-step plans where each step depends on the last, and the kind of code generation where the *first* draft has to compile and match the architecture conventions of an existing codebase. With extended thinking enabled, the response wait grows but the answer quality on hard problems jumps further than the latency cost suggests. ## 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-opus-4-7", "max_tokens": 16384, "messages": [ {"role": "user", "content": "Implement an LRU cache with O(1) get and put."} ] }' ``` ### Body parameters | Field | Type | Required | Default | Notes | | ------------- | --------------- | -------- | ----------------- | ---------------------------------------------------------------------------------- | | `model` | string | yes | — | `claude-opus-4-7` | | `messages` | array | yes | — | Conversation history. Up to 200K tokens of input. | | `max_tokens` | integer | yes | — | Hard cap. Max for this model: 32768. | | `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, parallel calls supported. | | `tool_choice` | object | no | `{"type":"auto"}` | `auto` / `any` / `tool` (named). | | `thinking` | object | no | — | Extended-thinking. Higher budget = better long-reasoning answer at higher latency. | | `stream` | boolean | no | false | SSE streaming. | ## Response ```json theme={null} { "id": "msg_opus_…", "type": "message", "role": "assistant", "model": "claude-opus-4-7", "content": [ {"type": "thinking", "thinking": ""}, {"type": "text", "text": "Here's the LRU cache..."} ], "stop_reason": "end_turn", "usage": { "input_tokens": 32, "output_tokens": 1248, "thinking_tokens": 4032 } } ``` `thinking_tokens` are billed at the input-token rate (extended thinking adds latency but not the full output cost). See the [pricing table](https://bytespike.ai/pricing#text) for current rate. ## Code examples ```bash cURL theme={null} curl https://llm.bytespike.ai/v1/messages \ -H "x-api-key: $BYTESPIKE_API_KEY" \ -H "anthropic-version: 2023-06-01" \ -H "content-type: application/json" \ -d '{ "model": "claude-opus-4-7", "max_tokens": 16384, "messages": [{"role": "user", "content": "Implement an LRU cache with O(1) get and put."}] }' ``` ```python Python theme={null} import anthropic client = anthropic.Anthropic( base_url="https://llm.bytespike.ai/v1", api_key="$BYTESPIKE_API_KEY", ) message = client.messages.create( model="claude-opus-4-7", max_tokens=16384, messages=[ {"role": "user", "content": "Implement an LRU cache with O(1) get and put."} ], ) # When extended thinking is on, content[0] is the thinking block; the # text block is the last one in the array. text_block = next(b for b in message.content if b.type == "text") print(text_block.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-opus-4-7", max_tokens: 16384, messages: [ { role: "user", content: "Implement an LRU cache with O(1) get and put.", }, ], }) const textBlock = message.content.find((b) => b.type === "text") console.log(textBlock.text) ``` ## Extended thinking Opt in by setting the `thinking` block: ```json theme={null} { "model": "claude-opus-4-7", "max_tokens": 16384, "thinking": { "type": "enabled", "budget_tokens": 8192 }, "messages": [...] } ``` `budget_tokens` is the maximum number of internal-reasoning tokens. The model may use fewer; the floor is a few hundred. Recommended budgets: | Task | Suggested budget | | -------------------------- | ---------------- | | Multi-step coding | 4K–8K | | Long-context summarisation | 8K–16K | | Hard math / proof | 16K–32K | Higher budgets monotonically improve answer quality on hard problems — but the marginal return falls off above 16K for most tasks. ## Cache control ```json theme={null} { "model": "claude-opus-4-7", "system": [ { "type": "text", "text": "", "cache_control": {"type": "ephemeral"} } ], "messages": [...] } ``` Cache reads at the discounted rate visible in the [pricing table](https://bytespike.ai/pricing#text). On Opus 4.7, cache control is the single highest-leverage cost optimisation — large system prompts paid once, billed at the cache-read rate on every subsequent turn. ## Errors | Code | Trigger | Billed? | | ---- | ---------------------------------------------- | ------------------------ | | 400 | Body validation failed | No | | 401 | Missing / revoked key | No | | 402 | Wallet exhausted (Opus calls trip this faster) | No | | 413 | Input exceeds 200K tokens | No | | 429 | Rate-limited | No | | 5xx | Upstream provider issue | No (auto-retry envelope) | ## When to use * One-shot quality matters and you can wait for a thoughtful answer. * Code generation in an existing codebase where conventions matter. * Multi-step plans where each step depends on the last (Sonnet starts skipping; Opus 4.7 keeps the chain tight). * Long-context reasoning across legal / medical / technical corpora within the 200K window. * For mid-tier cost / latency, see [Sonnet 4.6](/api-reference/text/claude-sonnet-4-6). * For high-throughput agent loops, see [Haiku 4.5](/api-reference/text/claude-haiku-4-5). ## Limits | Limit | Value | | -------------------------- | -------------- | | Context window | 200K tokens | | Max output | 32768 tokens | | Supports tool use | Yes (parallel) | | Supports vision | Yes | | Supports streaming | Yes | | Supports prompt caching | Yes | | Supports extended thinking | Yes |