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Claude Opus 5 vs Gemini 3.6 Flash

vs

什麼情況選哪一個

需要可關閉的明確思考與推理,或需要最多 128,000 輸出 token 的長單次生成時選 claude-opus-5;它在輸入($5 對 $1.5)和輸出($25 對 $7.5)上都比 gemini-3.6-flash 貴約 3.3 倍,快取讀取也貴 3.3 倍($0.5 對 $0.15)。更便宜的大批量文字和影像工作,或輸入是視訊、音訊(Opus 5 不接受)時選 gemini-3.6-flash;音訊輸入按每百萬 token $5 單獨計價。脈絡基本持平,1000000 對 1048576 token。

Benchmark 成績

領先高於平均沒有模型更高Claude Opus 51138 / 468 / 46Gemini 3.6 Flash26 / 181 / 18

兩邊都有成績的有 13 項。

Claude Opus 5 Gemini 3.6 Flash 其他有成績的模型 其他模型平均 ★ 沒有模型分數更高
DeepSWE 1.1
68.8%
48.6%
BioMysteryBench hard
49.4%
41.2%
OSWorld 2.0
沒有模型分數更高 70.6%
33.8%
ExploitBench (Cap%)
70%
N/A
HealthBench Professional
59.8%
N/A
Finance Agent v2
58.6%
N/A
Harvey Lab-AA
N/A
85.1%
HLE-Verified
54.4%
51.2%
AutomationBench
26.9%
17%
LVBench
75.4%
84.2%

供應商公布: Alibaba (Qwen) Anthropic ByteDance DeepSeek Google MiniMax Moonshot OpenAI Tencent Z.ai

定價

Claude Opus 5 Gemini 3.6 Flash Δ
輸入 / 1M tokens $5 $1.5 3.3×
輸出 / 1M tokens $25 $7.5 3.3×
快取讀取 / 1M tokens $0.5 $0.15 3.3×
快取寫入 1.25x (5m) / 2x (1h) - -

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 76 個聊天模型(對數尺度)

功能

Claude Opus 5 Gemini 3.6 Flash
工具使用 是 是
思考控制 可設定 一律開啟
結構化輸出 是 是
提示詞快取 顯式(由你標記前綴) 隱式 + 顯式
快取存活時間 5m default, 1h option 未公布
最小快取前綴 1024 個 token 4096 個 token

規格

Claude Opus 5 Gemini 3.6 Flash
輸入模態 文字 圖像 文字 圖像 音訊 影片
輸出模態 文字 文字
發布日期 2026-07-24 2026-07-21
知識截止日期 2026-05 2026-03
上下文視窗 1M 1M
最大輸出 128K 66K
思考參數
  • thinking.type
  • output_config.effort
thinkingLevel
可接受的值
thinking.type
  • adaptive
  • disabled
effort
  • low
  • medium
  • high
  • xhigh
  • max
  • minimal
  • low
  • medium
  • high
預設值

thinking on

effort
  • high (Claude API and Claude Code)
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 Opus 5 · Gemini 3.6 Flash

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 Opus 5 通過 · 3 sentences

When reasoning is enabled, the model generates a hidden chain of "thinking" tokens before it writes the visible answer, and those internal tokens are billed at the output rate even though no one ever sees them — commonly 3–10x more tokens than the response itself. Because output tokens are priced several times higher than input tokens, that added volume hits us at our most expensive rate, which is why the bill roughly doubled while our request count stayed flat. The spend is controllable: we can cap the reasoning budget per call, route only genuinely hard requests to reasoning mode and cheaper models for the rest, and track cost per successfully completed task rather than cost per token, since a single correct answer usually beats three cheap retries plus human cleanup.

輸出 529 tok 延遲 9.0 s

Gemini 3.6 Flash 通過 · 3 sentences

Enabling reasoning causes the model to generate thousands of internal "thinking" tokens behind the scenes to process logic before delivering the final response. Because our vendor bills us for every token generated—including these intermediate processing steps—our billable output volume per query surged significantly. Since output tokens carry a much higher unit cost than input tokens, this jump in processing volume directly doubled our overall spend.

輸出 893 tok (+816 思考) 延遲 4.7 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 Opus 5 通過 · 8/8 cases

## Fixed version ```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 else: cur = 1 if cur > best: best = cur return best ``` ## The bug The counters were tracking the wrong quantity: `cur` counted *matching adjacent pairs* rather than *elements in the current run*, and both counters started at `0` instead of `1`. Since a run of length *n* contains only *n − 1* adjacent equal pairs, every result came back one too small — `[1, 1]` returned 1, `[3, 3, 3]` returned 2 — and a single-element list returned 0 because the loop body never executed and `best` kept its initial value of `0`. […]

輸出 1094 tok 延遲 16.1 s

Gemini 3.6 Flash 通過 · 8/8 cases

Here is the fixed function along with an explanation of the bugs: ```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 else: cur = 1 best = max(best, cur) return best ``` ### Explanation The original function initialized `cur` and `best` to `0` and incremented `cur` on matching adjacent items, which meant it was counting identical adjacent *pairs* rather than the total number of *elements* in a run. This caused single-element inputs to skip the loop and return `0` instead of `1`, and undercounted all run lengths by 1 (for example, a run of two items at the end of the list resulted in `cur = 1`). […]

輸出 2034 tok (+1768 思考) 延遲 10.0 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。

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 Opus 5 通過 · 5/5 fields, guidance "Withheld pending Q4 close"

```json { "company": "Meridian Robotics", "quarter": "Q3", "revenue_usd_m": 412, "growth_pct": 11, "guidance": "Withheld pending Q4 close" } ``` Notes on judgment calls: - **quarter**: "September quarter" is labeled Q3 because the text refers to an upcoming "Q4 close," implying a calendar-aligned fiscal year. No fiscal year is given. - **revenue_usd_m**: 412 is stated as constant-currency and hedged ("call it"), so it's approximate; the currency is not explicitly stated as USD. - **growth_pct**: "up eleven and change" means slightly more than 11, so 11 is a floor rather than an exact figure.

輸出 539 tok 延遲 7.6 s

Gemini 3.6 Flash 通過 · 5/5 fields, guidance "withheld"

```json { "company": "Meridian Robotics", "quarter": "September quarter", "revenue_usd_m": 412, "growth_pct": null, "guidance": "withheld" } ```

輸出 2843 tok (+2783 思考) 延遲 13.1 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 Opus 5 通過 · 123 words, 0 banned, 1 question

**Cross-Provider Prompt Caching** We're introducing Cross-Provider Prompt Caching in the API Gateway. Repeated system prompts, long documents, and few-shot examples are stored once at the gateway layer and reused across OpenAI, Anthropic, Google, and self-hosted models. Instead of paying full input token costs on every request, your application sends a cache reference, and the gateway rehydrates the context before forwarding it downstream. Why does that matter? Teams running high-volume agents and retrieval pipelines typically see input token spend fall 40 to 70 percent, with median latency dropping by several hundred milliseconds. Caches are scoped per project, encrypted at rest, and invalidated automatically when a prompt template changes. Enable it with a single header, and see the docs for TTL tuning and per-route controls.

輸出 1593 tok 延遲 19.1 s

Gemini 3.6 Flash 未通過 · 60 words, 0 banned, 0 questions

72: reducing 73: your 74: monthly 75: token 76: spend. S6 (21): 77: You 78: can 79: easily 80: set 81: custom 82: expiration 83: rules, 84: configure 85: TTL 86: settings, 87: and 88: manage 89: cache 90: invalidation 91: across 92: all 93: vendors 94: from 95: one 96: centralized 97: dashboard. S7 (23): 98: Start 99: optimizing […]

輸出 4092 tok (+3929 思考) 延遲 16.3 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-opus-5",
    # model="gemini-3.6-flash",  # 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 Opus 5 和 Gemini 3.6 Flash 哪個比較便宜?

以「輸入 / 1M tokens」來看,Gemini 3.6 Flash 比較便宜($1.5 對 $5,相差 3.3×)。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 Opus 5 和 Gemini 3.6 Flash 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 Opus 5 與 Gemini 3.6 Flash 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