99MODELS

ক্লড ফেবল 5

নতুন

Mythos-class model for autonomous knowledge work; always reasons.

মুকলিৰ তাৰিখ: 9 জুন 2026

5,280.00

প্ৰতি 10 লাখ আউটপুট Tokens

ইনপুট: প্ৰতি 10 লাখ Tokens-ত ₹1,056.00

প্ৰতি মাৰ্কিন ডলাৰত ₹96 হাৰত ৰূপান্তৰিত, 0% মাৰ্কআপৰ সৈতে প্ৰভাইডাৰৰ নিৰ্ধাৰিত দৰত বিল কৰা হয়।

Specifications

Context window
10,00,000 tokens
সৰ্বাধিক আউটপুট
1,28,000 tokens
গ্ৰহণ কৰে
টেক্সট, ছবি, PDF ফাইল
Reasoning
ডিফল্টভাৱে অন
Effort levels
low, medium, high, xhigh, max
টুলৰ ব্যৱহাৰ
হয়
গঠনবদ্ধ আউটপুট
হয়
ক'ড কাৰ্যকৰীকৰণ
নহয়
বুদ্ধিমত্তাৰ ৰেংক
54 ৰ ভিতৰত #4
ভ্যালু ৰেংক
54 ৰ ভিতৰত #35

মূল্য

মূল্য
প্ৰতি 10 lakh TokensINRUSD
ইনপুট1,056.00$11.00
আউটপুট5,280.00$55.00
কেশ্বড ইনপুট105.60$1.10

Benchmarks

ৰেটিং হিচাপে উল্লেখ নথকালৈকে স্ক’ৰসমূহ শতাংশত দিয়া হৈছে। সকলো Benchmark স্বতন্ত্ৰভাৱে পৰীক্ষা কৰা হৈছে।

  • 92.6%

    GPQA Diamond

    GPQA Diamond - graduate-level science Q&A

  • 55.5%

    HLE

    Humanity's Last Exam

  • 61.0%

    SciCode

    SciCode - scientific code generation

  • 63.5%

    IFBench

    IFBench - precise instruction following

  • 82.3%

    Long Context

    Long Context Reasoning - reasoning over long inputs

  • 62.9%

    Terminal-Bench Hard

    Terminal-Bench Hard - agentic terminal tasks

  • 84.6%

    Terminal-Bench 2

    Terminal-Bench 2.1 - agentic terminal tasks, second edition

  • 53.5%

    FrontierCode

    FrontierCode - long-horizon production coding tasks

  • 89.2%

    ARC-AGI-2

    ARC-AGI-2 - abstract reasoning on novel puzzles

  • 1626

    WebDev Arena

    WebDev Arena - head-to-head web-app builds, Elo rating

ক্লড ফেবল 5-ৰ বিষয়ে

Anthropic's most capable widely released model, built for the most demanding reasoning and long-horizon agentic work. Its capabilities exceed anything Anthropic had previously made generally available, and it is state of the art on nearly all tested benchmarks, with exceptional results in software engineering, knowledge work, vision and scientific research. It can work autonomously for longer than any previous Claude, and it always reasons -- thinking cannot be switched off.

Fable 5 and Claude Mythos 5 are the same underlying model launched twice. Mythos 5 goes to cyber defenders and critical infrastructure providers with safeguards lifted; Fable 5 is that model made safe for general release, and it is the one served here. Because it always reasons, there is no non-thinking mode to fall back to - every call spends reasoning tokens, and the effort ladder from low to max sets how many rather than whether. Anthropic characterises the advantage as one that widens with the job: the harder and more drawn-out the work, the further Fable 5 pulls ahead of the rest of its range.

The safeguards are the defining fact about this model and worth understanding before you rely on it. Classifiers watch for requests about cybersecurity, biology and chemistry, or attempts to distil the model, and hand those to Claude Opus 4.8 instead, telling the user when it happens. Anthropic tuned them deliberately conservatively, so benign requests are sometimes caught; the lab's early data shows fallback in under 5% of sessions, and says that for the other 95% Fable 5 performs effectively as Mythos 5 does. That reads across into the published benchmark table: on the starred rows, which include Humanity's Last Exam, Terminal-Bench 2.1 and the biology and cybersecurity evaluations, Fable 5 scores closer to Opus 4.8 than the headline figure because of those fallbacks.

On software engineering, Anthropic reports the highest score among frontier models on Cognition's FrontierCode evaluation even at medium effort, and cites Stripe compressing a codebase-wide migration across 50 million lines of Ruby into a day of work that would otherwise have taken a team over two months. Vision is where the lab claims a clean state of the art: extracting precise numbers from detailed scientific figures, rebuilding a web app's source code from screenshots alone, and finishing Pokemon FireRed with a vision-only harness where earlier Claude models needed a scaffold of navigation aids and game-state tools.

Long-horizon behaviour is the other theme. Anthropic says Fable 5 holds focus across millions of tokens and improves its own output from notes it wrote earlier; giving it persistent file-based memory in the deck-building game Slay the Spire helped it three times more than the same memory helped Opus 4.8, and it reached the final act three times as often. On knowledge work the lab reports the highest score of any model on Hebbia's Finance Benchmark, with the gains concentrated in document-based reasoning and chart and table interpretation.

Two operational notes come with the capability. Traffic on Mythos-class models carries mandatory 30-day retention on first- and third-party surfaces, which Anthropic says it uses for safety work and jailbreak detection and not for training. And on alignment the lab reports the model's rate of misaligned behaviour as low and similar to Opus 4.8's, measured on Mythos 5 and inherited by Fable 5 because they are the same weights.

মুকলিৰ সময়ত Anthropic-এ যি কৈছিল

Thinking cannot be turned off
Fable 5 always reasons. The effort ladder from low to max decides how much thinking a call buys, never whether it happens, so there is no cheap non-reasoning path on this model.
Software engineering at scale
Anthropic reports the top score among frontier models on Cognition's FrontierCode evaluation even at medium effort, and cites a 50-million-line Ruby migration completed in a day that a team had costed at over two months.
Vision
The lab calls Fable 5 its state of the art for vision: reading precise values off scientific figures, reconstructing a web app from screenshots, and completing a console game from raw frames with no helper tooling.
Long-horizon memory
Anthropic reports Fable 5 staying on task across millions of tokens and gaining three times as much as Opus 4.8 from persistent file-based memory on a long game-playing evaluation.
Knowledge work
On Hebbia's Finance Benchmark for senior-level reasoning the lab reports the highest score of any model, with the largest gains in document-based reasoning and chart and table interpretation.
What it is not for
Cybersecurity, biology and chemistry, and distillation-shaped requests are routed to Claude Opus 4.8 by classifiers Anthropic tuned to over-trigger rather than under-trigger, and the published scores on those rows reflect the fallback rather than the raw model.
Data retention is mandatory
Anthropic requires 30-day retention for all traffic on Mythos-class models, on first- and third-party surfaces alike. It says the data is used for safety and jailbreak detection, never for training.

ভাৰতীয় ভাষাসমূহ

ক্লড ফেবল 5-এ 15 টা ভাৰতীয় ভাষাত উত্তৰ দিয়ে। মেচেজ বক্সৰ কাষৰ ভাষা মেনুৰ পৰা বাছক আৰু সেই ভাষাতে উত্তৰ লাভ কৰক।

Frequently Asked Questions

ক্লড ফেবল 5 সম্পৰ্কে সঘনাই সোধা প্ৰশ্নসমূহ।

ক্লড ফেবল 5 কেতিয়া মুকলি কৰা হৈছিল?

Anthropic-এ ক্লড ফেবল 5 মডেলটো 9 জুন 2026 তাৰিখে মুকলি কৰিছিল।

ক্লড ফেবল 5 কোনে তৈয়াৰ কৰিছে?

ক্লড ফেবল 5-ক AI লেব Anthropic-এ নিৰ্মাণ কৰিছে। 99Models AI-য়ে প্ৰভাইডাৰৰ নিৰ্ধাৰিত দৰতে ইয়াৰ পোনপটীয়া সংযোগ প্ৰদান কৰে।

ক্লড ফেবল 5 কিমান বুদ্ধিমান?

Intelligence তালিকাত 54 টা Chat Model-ৰ ভিতৰত ইয়াৰ স্থান 4, যিটো স্বতন্ত্ৰ Benchmark স্কোৰৰ দ্বাৰা নিৰ্ধাৰিত। ওপৰৰ Benchmarks তালিকাত ইয়াৰ সম্পূৰ্ণ স্কোৰ উপলব্ধ।

ক্লড ফেবল 5-ৰ খৰচ কিমান?

প্ৰতি 10 লাখ Input Tokens-ত ₹1,056.00 আৰু Output Tokens-ত ₹5,280.00, 0% মাৰ্কআপসহ প্ৰভাইডাৰৰ দৰত চাৰ্জ কৰা হয়। কোনো চাবস্ক্ৰিপশ্বন নাই; ব্যৱহাৰ অনুসৰি পেমেন্ট কৰক।

মাৰ্কিন ডলাৰত ক্লড ফেবল 5-ৰ API মূল্য কিমান?

প্ৰভাইডাৰে প্ৰতি 10 লাখ Input Tokens-ত $11.00 আৰু Output Tokens-ত $55.00 চাৰ্জ কৰে। ₹96 ডলাৰ বিনিময় হাৰত টকালৈ ৰূপান্তৰ কৰা হৈছে।

ক্লড ফেবল 5-এ কিমান দীঘলীয়া কথা-বতৰা মনত ৰাখিব পাৰে?

ইয়াৰ Context Window হ'ল 10 lakh Tokens। এটা ৰিকুৱেষ্টত এতিয়ালৈকে হোৱা কথোপকথন আৰু সংলগ্ন ফাইলসমূহ ই একেলগে প্ৰক্ৰিয়াকৰণ কৰিব পাৰে।

মূল্য আৰু পাৰদৰ্শিতাৰ ফালৰ পৰা ক্লড ফেবল 5 কিমান লাভজনক?

Value তালিকাত 54 টা Model-ৰ ভিতৰত ইয়াৰ স্থান 35। এই ৰেংকিং Benchmark বুদ্ধিমত্তা আৰু প্ৰকৃত Tokens খৰচৰ তুলনা কৰি নিৰ্ধাৰণ কৰা হয়।

ক্লড ফেবল 5-এ উত্তৰ দিয়াৰ পূৰ্বে Reasoning কৰেনে?

ডিফল্টভাৱে অন। য'ত Reasoning সমৰ্থিত, তাত আপুনি পোনপটীয়াকৈ মেচেজ কম্পোজাৰত চিন্তাৰ গভীৰতা বাছি ল'ব পাৰিব।

ক্লড ফেবল 5-এ কোন কোন ভাৰতীয় ভাষাত উত্তৰ দিয়ে?

ই 15 টা ভাৰতীয় ভাষাত উত্তৰ দিয়ে। মেচেজ বক্সৰ কাষৰ ভাষা মেনুৰ পৰা বাছি ল'লে সেই ভাষাতে উত্তৰ লাভ কৰিব।

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