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Claude Fable 5 vs DeepSeek V4 Flash (0731)

vs

何時該用哪一個 — 綜合評斷,而非基準測試數據表

兩款模型皆具備 1000000 token 的 context window,因此差異在於價格、模態與 output 長度:claude-fable-5 接受文字與影像 input,且始終啟用思考功能(無法關閉),而 deepseek-v4-flash-0731 僅支援文字,但允許高達 393216 output token(對比 Fable 的 128000)。在費率表上,claude-fable-5 每百萬 input token 的成本大約高出 32 倍($10 對比 $0.308),在 output 上大約高出 54 倍($50 對比 $0.924)。當您需要影像 input 或其內建的推理階段時,請選擇 claude-fable-5;若需要便宜、長篇的文字生成,請選擇 deepseek-v4-flash-0731。

定價

Claude Fable 5 DeepSeek V4 Flash (0731) Δ
輸入 / 1M tokens $10 $0.308 32×
輸出 / 1M tokens $50 $0.924 54×
快取讀取 / 1M tokens $1 $0.0308 32×
快取寫入 1.25x (5m) / 2x (1h) 不額外計費

費率取自建置時的即時目錄;各模型頁面皆附有目前的費率卡。

它們的相對位置 — 在此計費單位下,所有 63 個 聊天 模型的 每 1M tokens 的輸入價格(對數尺度)

能力

Claude Fable 5 DeepSeek V4 Flash (0731)
工具使用
思考控制 常駐開啟 是 —— 廠商未公布調節參數
結構化輸出
提示快取 顯式(由您標記前綴) 隱式(自動)
快取生命週期 5m default, 1h option no fixed TTL (evicted when unused)
最小快取前綴 1024 個 token 未公開

規格

Claude Fable 5 DeepSeek V4 Flash (0731)
輸入模態 文字 影像 文字
輸出模態 文字 文字
發布日期 2026-06-09 2026-07-31
知識截止日期 2026-01
上下文視窗 1M 1M
最大輸出 128K 393K
思考參數 output_config.effort (thinking.type is adaptive-only and needs no configuration)
可接受的值
effort
  • low
  • medium
  • high
  • xhigh
  • max

both "enabled" and "disabled" return 400

預設值

thinking always on (adaptive)

effort
  • high

規格摘錄自各供應商的文件;供應商未發布的資料列會直接省略,而非自行推測。 完整來源: Claude Fable 5 · DeepSeek V4 Flash (0731)

單一提示詞,兩款模型 — 經由閘道測量

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 Fable 5 通過 · 3 sentences

When we enabled reasoning, the model began generating extensive internal "thinking" tokens before each answer, and those tokens are billed as output even though users never see them. Output tokens typically cost several times more than input tokens, so adding thousands of hidden reasoning tokens per request effectively multiplied our per-query cost. In short, we're paying for a much longer response behind the scenes in exchange for higher answer quality, and we can manage this by tuning reasoning effort levels or reserving reasoning mode for complex tasks only.

輸出 228 tok 延遲 6.7 s

DeepSeek V4 Flash (0731) 通過 · 3 sentences

Enabling reasoning mode prompts the model to generate extensive internal chain-of-thought tokens before answering, often multiplying total token output per query by several times. This directly inflates costs because we are billed per token, and these reasoning tokens are processed at a premium compute tier that carries a higher price per million tokens. However, this spend buys measurably higher accuracy and fewer failed calls, so we are tracking it against specific error-reduction KPIs to ensure the ROI justifies the increase.

輸出 365 tok (+266 思考) 延遲 5.1 s

指令遵循(恰好三句,可數)、受眾適配(面向 CFO 的語氣),以及下方 token 計量所暴露的隱藏思考計費缺口。

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 修復通過測試

Claude Fable 5 通過 · 8/8 cases

## Fixed code ```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 ``` ## Explanation The original function counts **adjacent equal pairs** rather than **items in a run**: a run of length *n* contains only *n − 1* equal neighbor pairs, so every result is off by one — a single-element list yields 0 instead of 1, and `[1, 2, 2]` yields 1 instead of 2 (which callers perceive as "missing" the run at the end). The fix is to initialize both `cur` and `best` to 1 (any nonempty list has a run of at least length 1), reset `cur` to 1 rather than 0 when

輸出 531 tok 延遲 12.5 s

DeepSeek V4 Flash (0731) 通過 · 8/8 cases

```python def longest_run(xs): if not xs: return 0 best = 1 cur = 1 for i in range(1, len(xs)): if xs[i] == xs[i - 1]: cur += 1 best = max(best, cur) else: cur = 1 return best ``` The original bug stems from initializing `cur` to 0 and only incrementing it when adjacent elements are equal, which counts the number of *equal transitions* rather than the actual run length—so every run of length L is reported as L−1, and a single‑element run (with no transitions) yields 0. Moreover, because `best` is updated only inside the equality branch, it never accounts for a run that ends at the last element if that run is longer than any previously seen (though the real issue remains the off‑by‑one). […]

輸出 1268 tok (+1016 思考) 延遲 14.0 s

修復是否真的正確(可執行)、解釋的資訊密度,以及在一個邊界明確的任務上的 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 合法 JSON,schema 精確

Claude Fable 5 通過 · 5/5 fields, guidance null

```json { "company": "Meridian Robotics", "quarter": "Q3 (September quarter)", "revenue_usd_m": 412, "growth_pct": 11, "guidance": null } ``` Notes on interpretation: "up eleven and change" is rendered as 11 (the precise figure isn't stated), and guidance is null because it was explicitly withheld.

輸出 192 tok 延遲 6.5 s

DeepSeek V4 Flash (0731) 通過 · 5/5 fields, guidance null

{ "company": "Meridian Robotics", "quarter": "Q3", "revenue_usd_m": 412, "growth_pct": null, "guidance": null }

輸出 1119 tok (+1072 思考) 延遲 12.3 s

schema 服從度(不臆造欄位)、幻覺壓力(guidance 明確被暫緩給出),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 Fable 5 通過 · 120 words, 0 banned, 1 question

**Introducing Cross-Provider Prompt Caching for our API Gateway** Starting today, your repeated prompts are cached once and reused across OpenAI, Anthropic, Google, and any other provider you route through the gateway. Instead of paying full token costs every time your application sends the same system prompt or context block, the gateway detects matching prefixes and serves cached results in milliseconds. Why keep spending money and latency on identical requests? Early adopters report cost reductions of up to 60 percent on high-volume workloads, along with faster median response times. Configuration is simple: enable caching in your dashboard, set a TTL, and choose which routes participate. Cache entries are encrypted at rest and never shared between accounts. Available now on all plans.

輸出 1173 tok 延遲 18.2 s

DeepSeek V4 Flash (0731) 未命中 · 141 words, 0 banned, 1 question

**Introducing Prompt Cache for API Gateway** We are pleased to announce Prompt Cache, a new feature that stores and reuses identical prompt prefixes across all connected LLM providers. By automatically recognizing repeated requests, this cache reduces token consumption and lowers latency without altering your application logic. Whether you use OpenAI, Anthropic, or open-source models, the cache operates transparently, ensuring consistent behavior while cutting costs. Developers can configure cache TTL and scoping rules via a simple API call, giving you precise control over data freshness and privacy. This feature also minimizes redundant upstream calls, freeing provider rate limits for more critical workloads. Start caching today through the dashboard or CLI, and watch your operational expenses drop significantly. […]

輸出 254 tok (+80 思考) 延遲 4.4 s

約束服從度(字數預算、禁用詞表、唯一的那句問句)、文風指紋,以及長度控制。

只需一行程式碼即可在兩者間切換

以下每個頁籤中都有這兩個 ID — 醒目提示的這兩行是唯一的修改處。相同的端點,相同的金鑰,相同的請求結構。

from openai import OpenAI

client = OpenAI(
    base_url="https://synthorai.io/v1",
    api_key="sk-syn-...",
)

resp = client.chat.completions.create(
    model="claude-fable-5",
    # model="deepseek-v4-flash-0731",  # 取消註解此行,並註解上一行
    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 Fable 5 和 DeepSeek V4 Flash (0731) 哪個比較便宜?

DeepSeek V4 Flash (0731) 在 輸入 / 1m tokens 上較便宜($0.308 對比 $10,相差 32×)。其他項目可能呈現相反結果 — 上表提供完整資訊,實際成本取決於您的使用組合。

我可以在不進行兩次整合的情況下,對 Claude Fable 5 和 DeepSeek V4 Flash (0731) 進行 A/B 測試嗎?

可以。兩者皆透過同一個相容 OpenAI 的端點提供服務,並使用同一把 API 金鑰 — 切換只需更改一行的模型字串,因此您可以將部分流量分別導向兩者並直接比較帳單。

Claude Fable 5 與 DeepSeek V4 Flash (0731) 支援提示快取嗎?

是的 — 兩者的快取讀取費率皆低於其輸入費率,因此具有暖前綴的工作負載成本會低於牌價所示。確切的快取讀取列請見上方的定價表。

相關比較