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Claude Fable 5.1

发布于 2026-09-01

邀请测试 chat代码推理工具调用图像理解提示词缓存

Claude Fable 5.1 是 Anthropic 当前能力最强的模型,2026 年 9 月 1 日发布,面向高难度推理与长程智能体工作。

输入
文本 图像 $10/M
输出
文本 $50/M
缓存读取
$0.25/M
上下文
1M
知识截止
2026-06

Benchmark 成绩

高于同类均值无更高分19 / 213 / 21
Claude Fable 5.1 其他参测模型 同类均值 ★ 没有模型得分更高
DeepSWE 1.1
67.4%
OSWorld 2.0 partial
80.7%
HealthBench Professional
58.1%
Terminal-Bench-Science 0.1
52.6%
GPQA Diamond
93.7%
AutomationBench
31.4%
Chartography with tools
88.4%

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

价格在同类中的位置

价格在 70 个同类模型中的位置

输入$10/M
$0.1 · Dola Seed 2.0 Mini GPT-5.4 Pro · $30
输出$50/M
$0.275 · DeepSeek V4 Flash GPT-5.4 Pro · $180
缓存读取$0.25/M
$0.006 · DeepSeek V4.1 Flash GPT-5.4 Pro · $15

这条线标出该模型的价格在 Synthorai 同类模型中的位置,两端分别是最便宜和最贵的模型。这里是基础价,批量、区域和缓存写入的折扣见价格页。

规格与限制

Token

上下文窗口(供应商规格) 1,000,000
最大输出(供应商规格) 128,000
知识截止 2026-06

提示词缓存

缓存方式 显式(需开启)
最小前缀 1,024
有效期 默认 5 分钟,可选 1 小时
写入成本 1.25x (5m) / 2x (1h)

思考

供应商参数 output_config.effort (thinking is adaptive-only and always on)
可选值 effort low · medium · high · xhigh · max
默认值 thinking always on (adaptive); effort high 请求未指定时生效
可关闭 不支持
思考行为 Effort can be changed per message mid-conversation without invalidating the prompt cache (beta). Turn-scoped system messages and readable progress updates between tool calls are the other additions, both beta.
参数 reasoning_effort
取值 minimal · low · medium · high 这是网关侧的参数,实际以上方的供应商映射为准

模型

模态 文本 + 图像 → 文本
  • Extends Claude Fable 5 at the same input and output prices with cache reads at a quarter of the cost
  • three changes break callers moving from Fable 5, because forced tool use returns an error, thinking blocks are tied to the model that produced them, and editing an earlier turn invalidates them

依据 Anthropic 官方文档 ↗

一条提示词,经网关实测

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

Claude Fable 5.1 通过 · 3 sentences

When we enabled reasoning, the model started generating a long chain of internal "thinking" tokens before producing each answer, and we're billed for those tokens at the same output rate even though users never see them. In practice, that hidden reasoning often runs several times longer than the visible response, so the total tokens per request roughly doubled while the number of requests stayed flat. The upside is measurably better accuracy on complex tasks, so the right conversation is whether that quality gain justifies the cost—and if not, we can restrict reasoning to the workflows that actually need it rather than turning it on globally.

输出 186 tok 延迟 3.2 s

指令遵循(恰好三句,数得出来)、受众适配(对 CFO 说话的口吻),以及下方 token 计数暴露出的隐藏思考计费差额。

提示词 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. 检查 修复通过测试

Claude Fable 5.1 通过 · 8/8 cases

```python def longest_run(xs): if not xs: return 0 best = cur = 1 for i in range(1, len(xs)): cur = cur + 1 if xs[i] == xs[i - 1] else 1 best = max(best, cur) return best ``` The bug is that `cur` counts *matches between adjacent elements* rather than *elements in the run*: it starts at 0 and only increments when `xs[i] == xs[i-1]`, so a run of length k produces a count of k−1. That's why a single element returns 0 instead of 1, and why every other run also comes out one short — the "misses runs at the end" reports are the same off-by-one seen on inputs like `[1, 2, 2]`, where the trailing run of length 2 is reported as 1 (the original code does update `best` inside the loop, so end-of-list runs aren't actually skipped, just undercounted). […]

输出 882 tok (+507 思考) 延迟 3.4 s

修复是否真的正确(能运行)、解释的信息密度,以及在一个范围明确的任务上的 token 效率。

提示词 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. 检查 合法 JSON,严格符合 schema

Claude Fable 5.1 通过 · 5/5 fields, guidance null

```json { "company": "Meridian Robotics", "quarter": "Q3 (September quarter)", "revenue_usd_m": 412, "growth_pct": 11, "guidance": null } ``` Notes on judgment calls (not part of the object): - **revenue_usd_m**: The text says "412 for the topline" but never states the currency or that the figure is in millions; it's also on a constant-currency basis and prefaced with "call it," so it's approximate. If you want strict literalism, this should be `null`. - **growth_pct**: "Eleven and change" means slightly above 11%; the exact figure isn't given. - **quarter**: "September quarter" is Q3 on a calendar basis, consistent with the reference to a pending Q4 close. - **guidance**: Explicitly withheld, so `null`.

输出 633 tok (+349 思考) 延迟 3.8 s

是否严守 schema(不臆造字段)、能否顶住幻觉压力(原文明说暂不给出 guidance),以及结构化输出路径的差异。

提示词 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. 检查 120 词,0 个禁用词

Claude Fable 5.1 通过 · 121 words, 0 banned, 1 question

**Introducing Cross-Provider Prompt Caching for the Gateway.** Starting today, your API gateway can cache prompts once and reuse them across OpenAI, Anthropic, Google, and any other provider you route to. Long system instructions, retrieval context, and few-shot examples are stored at the gateway layer, so switching models no longer means paying to resend the same tokens. Why send the same 8,000-token preamble to three different vendors when you could send it once? Our cache normalizes prompt segments, fingerprints them, and serves matching prefixes from memory before the request ever reaches an upstream API. Early customers report token costs falling by 30 to 60 percent on high-volume workloads, with median latency dropping alongside. Available today on all Team and Enterprise plans.

输出 1722 tok (+1463 思考) 延迟 2.9 s

是否守住约束(字数预算、禁用词表、只能有一个问句)、文风特征,以及长度控制。

30 秒用上 Claude Fable 5.1

兼容 OpenAI:换掉 base_url,SDK 不用改。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-fable-5-1",
    messages=[{"role": "user", "content": "Summarize this diff"}],
    reasoning_effort="medium",
)
print(resp.choices[0].message.content)

关于 Claude Fable 5.1

  • Anthropic 自己的选型指引仍建议多数负载从 Claude Opus 5 起步,只有当 Opus 5 在更高力度下仍不达标时才用这一档。
  • 它完整沿用了 Claude Fable 5 的形态:1M token 上下文窗口、128K 输出 token、文本与图像输入、文本输出,以及常开的自适应思考,力度默认为 high。
  • 升级的理由是成本表现与长程续航,而不是更大的窗口。
  • 输入与输出维持每百万 token 10 美元与 50 美元,而缓存读取降到此前的四分之一;Anthropic 称典型负载成本下降约 25%,高度智能体化的负载下降约 45%。
  • 从 Fable 5 迁移有三处破坏性变更:强制工具调用现在会报错;思考块与产生它的模型绑定,更早的 Claude 模型无法读取;编辑更早的对话轮次会使其失效。
  • 新增能力都向后兼容,五项中有三项处于 beta:逐条消息的力度设置、仅作用于当前轮次的系统消息,以及工具调用之间可读的进度更新;更低的缓存读价和内容溯源则已正式提供。
  • Claude Mythos 5.1 仅向 Project Glasswing 参与者提供同等能力。
  • 在 Synthorai 上它通过 OpenAI 兼容的对话端点提供,目前为邀请制内测。

常见问题

Claude Fable 5.1 API 可以免费试用吗?

Claude Fable 5.1 目前处于邀请测试阶段,不开放注册,需要申请开通。在 Synthorai 控制台提交申请,通过后按标准的按量付费价格计费,无需订阅。

Claude Fable 5.1 最擅长什么?

1M token 上下文窗口,128K 输出、缓存读取价为 Fable 5 的四分之一、不再支持强制工具调用。完整介绍见「关于」部分,内容取自供应商的官方发布说明。

Claude Fable 5.1 的价格是多少?

在 Synthorai 上,Claude Fable 5.1 的输入价为 $10/百万 token,输出价为 $50/百万 token。这就是供应商官网价,平台不加价。缓存命中的输入 token 按 $0.25/M 计费。

Claude Fable 5.1 的上下文长度是多少?

Claude Fable 5.1 的上下文长度(上下文窗口)是 1M token。单次回复最多输出 128,000 个 token。

Claude Fable 5.1 支持提示词缓存(prompt caching)吗?

支持,但需要主动开启:用 cache_control 断点标记稳定不变的前缀。缓存命中的输入 token 按 $0.25/M 计费(未命中为 $10/M);提示词的稳定前缀至少要有 1,024 个 token 才能缓存(TTL 默认 5 分钟,可选 1 小时)。 提示词缓存指南 →

如何开通 Claude Fable 5.1?

Claude Fable 5.1 处于邀请测试阶段,需要在 Synthorai 控制台申请开通。审批通过后,用法和其他模型一样:把 OpenAI SDK 的 base_url 指向 "https://synthorai.io/v1",model 设为 "claude-fable-5-1" 即可。

Claude Fable 5.1 的知识截止日期是什么时候?

Claude Fable 5.1 的知识截止日期是 2026-06,以供应商官方文档为准(核对于 2026-09-05)。

相关模型

对比

本页的每个数值都照录自供应商自己的文档(链接见上),并标有核对日期。价格是在整个目录范围内比较的;各家供应商定义不一样的规格项,只说明差异,不画图对比。这里没有任何一项是我们自己测的,也不打分。

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