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Claude Haiku 5.5 vs DeepSeek V4.1 Flash (1017)

vs

什麼情況選哪一個

兩者皆有 1,000,000 個 token 的上下文視窗,接受文字與圖片輸入,並以文字輸出,因此取捨在於價格與輸出長度:claude-haiku-5-5 的每百萬個 token 輸入與輸出費用分別為 $0.1 和 $0.5,deepseek-v4.1-flash-1017 則為 $0.3 和 $1.2,輸入費率為前者的 3 倍,輸出費率為 2.4 倍。若要大量處理文字與圖片,或希望在只需直接回答時關閉思考功能,請選擇 claude-haiku-5-5。若單次回應必須超過 128000 個 token,請選擇 deepseek-v4.1-flash-1017,其上限為 393216 個 token;它也適合重視較低快取讀取費用的情境,費用為 $0.006。

定價

Claude Haiku 5.5 DeepSeek V4.1 Flash (1017) Δ
輸入 / 1M tokens $0.1 $0.3 0.33×
輸出 / 1M tokens $0.5 $1.2 0.42×
快取讀取 / 1M tokens $0.01 $0.006 1.7×
快取寫入 1.25x (5m) / 2x (1h) 不額外計費 -

費率取自網站建置時的即時目錄;各模型頁面都列有最新的價目。

兩者的相對位置:每 1M tokens 的輸入價格,涵蓋同一計費單位下全部 79 個聊天模型(對數尺度)

功能

Claude Haiku 5.5 DeepSeek V4.1 Flash (1017)
工具使用 是 是
思考控制 可設定 是,但供應商未公布調整參數
結構化輸出 是 -
提示詞快取 顯式(由你標記前綴) 隱式(自動)
快取存活時間 5m default, 1h option no fixed TTL (evicted when unused)
最小快取前綴 1024 個 token 未公布

規格

Claude Haiku 5.5 DeepSeek V4.1 Flash (1017)
輸入模態 文字 圖像 文字 圖像
輸出模態 文字 文字
發布日期 2026-10-07 2026-10-17
知識截止日期 2026-06 -
上下文視窗 1M 1M
最大輸出 128K 393K
思考參數 output_config.effort -
可接受的值
output_config.effort
  • low
  • medium
  • high
  • xhigh
  • max
-
預設值 medium -

規格摘錄自各供應商的文件;供應商沒有公布的項目就直接略過,不自行推測。 完整來源: Claude Haiku 5.5 · DeepSeek V4.1 Flash (1017)

同一段提示詞,兩個模型,經閘道實測

提示詞 Explain to a CFO, in exactly three sentences, why our LLM bill doubled after we enabled reasoning. 檢查 恰好 3 句

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

DeepSeek V4.1 Flash (1017) 通過 · 3 sentences

Enabling reasoning caused each request to generate additional internal reasoning tokens, which are billed like output tokens and can be several times longer than the final answer. Those extra tokens raise cost per call, and longer responses plus occasional retries pushed total usage to roughly double. We can control this with reasoning-effort limits, token budgets, caching, and spend monitoring by use case.

輸出 253 tok (+178 思考) 延遲 5.4 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。

提示詞 This function is supposed to return the longest run of consecutive equal items, but callers report it is off by one on single-element inputs and misses runs that end at the last index. Fix it and explain the bug in one paragraph. 檢查 修正後通過測試

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

DeepSeek V4.1 Flash (1017) 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` starts at `0` and is incremented only when two adjacent items match, so it counts equal adjacent pairs rather than run length; a run of length `k` is recorded as `k - 1`. Consequently, a single-element input returns `0`, and a run ending at the last index—especially a one-element final run—is undercounted or never counted. The fix initializes every run to length `1`, increments on a match, resets to `1` on a mismatch, updates `best` each iteration, and handles the empty input separately.

輸出 1300 tok (+1095 思考) 延遲 11.8 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。

提示詞 Extract a JSON object with fields {company, quarter, revenue_usd_m, growth_pct, guidance} from this text. Use null for anything not stated; add no other fields. 檢查 有效的 JSON,完全符合 schema

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

DeepSeek V4.1 Flash (1017) 通過 · 5/5 fields, guidance "withheld pending the Q4 close"

{"company":"Meridian Robotics","quarter":"September quarter","revenue_usd_m":412,"growth_pct":11,"guidance":"withheld pending the Q4 close"}

輸出 1375 tok (+1337 思考) 延遲 12.2 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。

提示詞 Write a 120-word product announcement for an API gateway feature that caches prompts across providers. Forbidden words: "seamless", "unlock", "game-changer", "revolutionize", "empower". Exactly one sentence must be a question. 檢查 120 詞,0 個禁用詞

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

DeepSeek V4.1 Flash (1017) 通過 · 120 words, 0 banned, 1 question

Today we’re introducing Cross-Provider Prompt Cache in the API gateway. It stores identical prompt requests once and serves cached responses across supported model providers, reducing duplicate calls, latency, and spend. Teams can set cache keys by model, temperature, system prompt, and custom metadata, then choose TTLs per route or workspace. The gateway handles provider fallback while keeping cached results consistent with your policy. Is your team paying twice for the same prompt? Cross-Provider Prompt Cache helps you answer that. Configure it in the gateway dashboard, inspect hit rates by provider, and invalidate entries on demand. Existing gateway routes need no code changes; enable the feature and define your caching rules. Cross-Provider Prompt Cache is available for all API gateway customers.

輸出 2487 tok (+2335 思考) 延遲 17.1 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。

改一行程式碼就能在兩者之間切換

下面每個頁籤都列了這兩個模型 ID,要改的只有醒目標示的那兩行。端點、金鑰和請求格式都不變。

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",
    # model="deepseek-v4.1-flash-1017",  # 取消這一行的註解,並把上一行註解掉
    messages=[{"role": "user", "content": "Summarize this diff"}],
    reasoning_effort="medium",
)
print(resp.choices[0].message.content)

取得 API 金鑰 →

常見問題

Claude Haiku 5.5 和 DeepSeek V4.1 Flash (1017) 哪個比較便宜?

以「輸入 / 1M tokens」來看,Claude Haiku 5.5 比較便宜($0.1 對 $0.3,相差 3.0×)。其他項目的結果可能相反,完整價目請看上表;實際成本要看你的用量組合。

可以只串接一次,就對 Claude Haiku 5.5 和 DeepSeek V4.1 Flash (1017) 做 A/B 測試嗎?

可以。兩個模型都走同一個 OpenAI 相容端點,用的也是同一把 API 金鑰,切換時只要改一行裡的模型名稱字串。你可以把一部分流量分別導到兩邊,再直接比較帳單。

Claude Haiku 5.5 與 DeepSeek V4.1 Flash (1017) 支援提示詞快取嗎?

支援。兩者的快取讀取費率都低於輸入費率,所以前綴已經進快取的工作負載,實際成本會比官網價算出來的低。確切的快取讀取價格請見上方定價表。

相關比較