Claude Haiku 5.5 是 Anthropic 速度最快的模型,於 2026 年 10 月 7 日發布,面向分類、資訊擷取、路由與子代理等大量且對延遲敏感的工作。
- 輸入
- 文字 圖像 $0.1/M
- 輸出
- 文字 $0.5/M
- 快取讀取
- $0.01/M
- 上下文
- 1M
- 相較 GPT-4o
- 便宜約 98%
- 知識截止
- 2026-06
輸入超過 100K token 時,整筆請求按輸入 $0.5/M、輸出 $2.5/M 計費
價格在同類中的位置
價格在 68 個同類模型中的位置
這條線標出這個模型的價格,在 Synthorai 的同類模型裡落在什麼位置;兩端分別是最便宜和最貴的模型。這裡列的是基礎價,批次、區域和快取寫入的折扣請見價格頁。
規格與限制
Token
| 上下文視窗(供應商規格) | 1,000,000 |
|---|---|
| 最大輸出(供應商規格) | 128,000 |
| 知識截止 | 2026-06 |
提示詞快取
| 快取方式 | 顯式(需主動開啟) |
|---|---|
| 最小前綴 | 512 供應商預設 1,024 |
| 存活時間 | 預設 5 分鐘,可選 1 小時 |
| 寫入成本 | 1.25x (5m) / 2x (1h) |
思考
| 供應商參數 | output_config.effort |
|---|---|
| 可接受的值 | low · medium · high · xhigh · max |
| 預設值 | medium 請求未指定時生效 |
| 可關閉 | 支援 |
| 思考行為 | Adaptive thinking is on by default. thinking {"type": "disabled"} turns it off at high effort or below and returns a 400 error at xhigh or max; a manual {"type": "enabled", "budget_tokens": N} and "between_tools" both return a 400 error. |
| 參數 | reasoning_effort |
| 參數值 | minimal · low · medium · high 這是閘道的參數,實際以上方的供應商對應為準 |
模型
| 模態 | 文字 + 圖像 → 文字 |
|---|
- Priced by prompt length: a prompt over 100,000 tokens is billed at 5x on input, output and every cache rate ($0.50 in, $2.50 out per million)
- prompt-cache reads cost 0.1x input on both tiers
- minimum cacheable prompt 512 tokens
- setting temperature, top_p or top_k to a non-default value returns a 400
- assistant message prefill returns an error
- thinking blocks work only in the account that produced them
- up to 300k output tokens on the Message Batches API with the output-300k-2026-03-24 beta header
一段提示詞,經閘道實測
Claude Haiku 5.5 通過 · 3 sentences
Enabling reasoning makes the model generate a long internal chain of thought before its answer, and those thinking tokens are billed as output tokens, which cost several times more than input tokens. The model often produces many times more output per request than it did without reasoning, so the per-call cost rises even when the visible answer looks about the same length. Because that extra spend scales with every request, the bill roughly doubled, and we can control it by setting reasoning budgets, using reasoning only for tasks that need it, or routing simpler requests to a non-reasoning model.
輸出 332 tok (+159 思考) 延遲 2.9 s
是否照指令做(剛好三句,數得出來)、語氣是否貼合對象(寫給 CFO 看),以及下方 token 計量顯示出的隱藏思考計費落差。
Claude Haiku 5.5 通過 · 8/8 cases
```python def longest_run(xs): if not xs: return 0 best = cur = 1 for i in range(1, len(xs)): if xs[i] == xs[i - 1]: cur += 1 else: cur = 1 best = max(best, cur) return best ``` The bug is that `cur` counts adjacent equal *pairs*, not run *elements*. A run of k equal items produces k−1 matching pairs, so the function returns one less than the true length, and a single-element input produces no pairs at all, so it returns 0 instead of 1. Resetting `cur` to 0 on a mismatch compounds this by starting every run one step behind. The fix starts both `cur` and `best` at 1 (a non-empty list always has a run of at least one element), resets `cur` to 1 on a mismatch, and updates `best` after every element rather than only inside the equal-branch. The empty-list guard keeps the function from returning 1 for `[]`. […]
輸出 1012 tok (+591 思考) 延遲 6.0 s
修正是否真的正確(跑得起來)、說明的資訊密度,以及在範圍明確的任務上的 token 效率。
Claude Haiku 5.5 通過 · 5/5 fields, guidance "Formal guidance withheld pending the Q4 "
```json { "company": "Meridian Robotics", "quarter": "September quarter", "revenue_usd_m": null, "growth_pct": 11, "guidance": "Formal guidance withheld pending the Q4 close" } ``` Notes: The text gives revenue as 412 but doesn't state the currency, so I left `revenue_usd_m` as null. Growth is "eleven and change," so 11 is an approximation.
輸出 725 tok (+572 思考) 延遲 4.6 s
是否遵守 schema(不自創欄位)、面對幻覺誘因的表現(題目明確不給 guidance),以及結構化輸出路徑的差異。
Claude Haiku 5.5 通過 · 120 words, 0 banned, 1 question
**Introducing Prompt Cache Sync, the newest feature in GatewayOne.** Teams routing requests across OpenAI, Anthropic, and Google have often paid to process the same long system prompts again and again. Now the gateway stores those prompts once and reuses them wherever they appear, regardless of provider. Repeated context is matched by content hash, so cached prefixes return faster and cost less, with no changes to your application code. How much could this save your team? Enable Prompt Cache Sync from the dashboard, and your next billing report will show the difference. Cache entries follow your existing retention settings and can be purged per project at any time. Availability begins this week for all Scale and Enterprise plans worldwide. Start today.
輸出 2164 tok (+1929 思考) 延遲 9.9 s
是否遵守限制(字數上限、禁用詞清單、只能有一句問句)、文字風格的特徵,以及長度控制。
30 秒上手 Claude Haiku 5.5
相容 OpenAI:換掉 base_url,SDK 不用換。POST /v1/chat/completions
from openai import OpenAI
client = OpenAI(
base_url="https://synthorai.io/v1",
api_key="sk-syn-...",
)
resp = client.chat.completions.create(
model="claude-haiku-5-5",
messages=[{"role": "user", "content": "Summarize this diff"}],
reasoning_effort="medium",
)
print(resp.choices[0].message.content)import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://synthorai.io/v1",
apiKey: "sk-syn-...",
});
const resp = await client.chat.completions.create({
model: "claude-haiku-5-5",
messages: [{ role: "user", content: "Summarize this diff" }],
reasoning_effort: "medium",
});
console.log(resp.choices[0].message.content);curl https://synthorai.io/v1/chat/completions \
-H "Authorization: Bearer sk-syn-..." \
-H "Content-Type: application/json" \
-d '{
"model": "claude-haiku-5-5",
"messages": [{"role": "user", "content": "Hello"}],
"reasoning_effort": "medium"
}'package main
import (
"context"
"fmt"
"github.com/openai/openai-go/v3"
"github.com/openai/openai-go/v3/option"
)
func main() {
client := openai.NewClient(
option.WithBaseURL("https://synthorai.io/v1"),
option.WithAPIKey("sk-syn-..."),
)
resp, _ := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{
Model: "claude-haiku-5-5",
Messages: []openai.ChatCompletionMessageParamUnion{
openai.UserMessage("Summarize this diff"),
},
ReasoningEffort: openai.ReasoningEffortMedium,
})
fmt.Println(resp.Choices[0].Message.Content)
}import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.chat.completions.*;
import com.openai.models.ReasoningEffort;
OpenAIClient client = OpenAIOkHttpClient.builder()
.baseUrl("https://synthorai.io/v1")
.apiKey("sk-syn-...")
.build();
ChatCompletion resp = client.chat().completions().create(
ChatCompletionCreateParams.builder()
.model("claude-haiku-5-5")
.addUserMessage("Summarize this diff")
.reasoningEffort(ReasoningEffort.MEDIUM)
.build());
System.out.println(resp.choices().get(0).message().content().orElse(""));關於 Claude Haiku 5.5
- 它依提示詞長度計價:提示詞不超過 100,000 token 時,每百萬輸入 token $0.10、每百萬輸出 token $0.50;超過 100,000 token 時為 $0.50 與 $2.50。
- 提示詞快取讀取在兩檔都是輸入價的 10%(每百萬 $0.01 與 $0.05),5 分鐘快取寫入為 $0.125 與 $0.625,1 小時快取寫入為 $0.20 與 $1。
- 上下文視窗為 1M token,最大輸出 128K,高於 Claude Haiku 4.5 的 200K 與 64K,支援文字與圖像輸入。
- 自適應思考預設開啟,預設強度為 medium;在 high 及以下強度仍可把 thinking 設為 disabled 來關閉思考,而手動指定 budget_tokens 會回傳 400。
- temperature、top_p、top_k 設為非預設值同樣回傳 400,助理訊息預填也會報錯。
- Anthropic 說明該模型使用隨 Claude Opus 4.7 導入的新分詞器,同樣的文字會比在 Claude Haiku 4.5 上多計約 30% 的 token。
- 可快取提示詞的最小長度為 512 token。
- Synthorai 透過與其餘模型相同的 OpenAI 相容 API 提供 Claude Haiku 5.5。
常見問題
Claude Haiku 5.5 API 可以免費試用嗎?
可以,新帳號有 10 次試用呼叫和最高 $1 的免費額度,免綁卡。以輸入價 $0.1/M 計算,光是這筆額度就夠你對 Claude Haiku 5.5 發出約 1,250 次請求,每次約 8K token。
Claude Haiku 5.5 最擅長什麼?
Anthropic 速度最快的模型,面向大量且對延遲敏感的工作、依提示詞長度計價:100K token 以內每百萬輸入 $0.10、輸出 $0.50、1M 上下文、128K 輸出,自適應思考可用 effort 調節。完整介紹請見「關於」一節,內容取自供應商官方的發布說明。
Claude Haiku 5.5 的價格是多少?
在 Synthorai 上,Claude Haiku 5.5 的輸入價是每百萬 token $0.1,輸出價是每百萬 token $0.5。這就是供應商官網價,平台不加價。快取命中的輸入 token 以 $0.01/M 計費。
Claude Haiku 5.5 的上下文長度是多少?
Claude Haiku 5.5 的上下文長度(上下文視窗)是 1M token。單次回覆最多輸出 128,000 個 token。
Claude Haiku 5.5 支援提示詞快取(prompt caching)嗎?
支援,需主動開啟:以 cache_control 中斷點標記穩定前綴。快取命中的輸入 token 以 $0.01/M 計費(未命中為 $0.1/M);提示詞要有 512 個 token 以上的穩定前綴,才能命中快取(TTL 預設 5 分鐘,可選 1 小時)。 提示詞快取指南 →
如何開通 Claude Haiku 5.5?
把現有 OpenAI SDK 的 base_url 指向 "https://synthorai.io/v1",model 設為 "claude-haiku-5-5" 就可以了。一把 API 金鑰就能呼叫閘道上的所有模型。
Claude Haiku 5.5 的知識截止日期是什麼時候?
Claude Haiku 5.5 的知識截止日期為 2026-06,依據供應商官方文件(查核日期:2026-10-08)。
相關模型
比較
本頁每一個數值都摘錄自供應商自己的文件(連結見上方),並附上查核日期。價格是放在整個目錄裡比較;各家供應商定義不一樣的規格,只說明差異,不畫成圖表比較。這裡沒有任何數據是我們自己量測的,也不做評分。