Is Claude Fable 5.2 better than Claude Opus 5.5?

Claude Fable 5.2 (max) and Claude Opus 5.5 (max) are neck and neck on quality (69.4 vs 68.9, within the ±7.4 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 9 Nov 2026, so check the category scores for your use.

Claude Fable 5.2 vs Claude Opus 5.5: which is cheaper, and will that change?

Claude Opus 5.5 is cheaper today: $8.00 against $16.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.

Is Claude Fable 5.2 or Claude Opus 5.5 better for coding?

They are level in coding (80 vs 80 on the category index). On FrontierCode 2.0 (AA), the top shared coding benchmark, it is 48.8% for Claude Fable 5.2 against 46.4% for Claude Opus 5.5.

Which is faster, Claude Fable 5.2 or Claude Opus 5.5?

Claude Opus 5.5 streams ~1.5× faster (115 vs 72 output tokens per second, Artificial Analysis 7-day median).

Which is better for long documents?

They are level on long-context benchmarks (66 vs 67). Both accept 1,000,000 tokens of context.

Which has lower latency?

Claude Fable 5.2 answers first: 3.0 s against 380.6 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.

When was Claude Fable 5.2 released?

Claude Fable 5.2 was released on 9 Nov 2026.

Claude Fable 5.2 vs Claude Opus 5.5

Full profiles: Claude Fable 5.2 (Anthropic) and Claude Opus 5.5 (Anthropic): every benchmark, price and rank.

Updated 9 Nov 2026 · Data from 12 sources

As of 9 Nov 2026, Claude Fable 5.2 and Claude Opus 5.5 are neck and neck on quality (69.4 vs 68.9 on the BenchLeader Index, inside the ±7.4 margin), and Claude Opus 5.5 is 2.0× cheaper at $8.00 vs $16.00 per 1M tokens blended. Claude Fable 5.2 leads in every category we measure both in. Claude Opus 5.5 streams ~1.5× faster.

Key facts (as of 9 Nov 2026)

Claude Fable 5.2 scores 69.4 on the BenchLeader Index and Claude Opus 5.5 scores 68.9 (BenchLeader, 9 Nov 2026).
Claude Fable 5.2 costs $16.00 per 1M tokens blended (list price, 9 Nov 2026).
Claude Opus 5.5 costs $8.00 per 1M tokens blended (list price, 9 Nov 2026).
Claude Opus 5.5 streams ~1.5× faster than Claude Fable 5.2 (Artificial Analysis, 7-day median, 9 Nov 2026).
Of the 22 benchmarks both models have, Claude Fable 5.2 leads 15 (BenchLeader, 9 Nov 2026).

Claude Fable 5.2 benchmarks max Anthropic

Claude Opus 5.5 benchmarks max Anthropic Add a third model

Which to pick for…

The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.

Use case	Pick	Why	Confidence
Coding	Either	80 vs 80 category score; FrontierCode 2.0 (AA) 48.8% vs 46.4%	Either
Reasoning	Claude Fable 5.2	78 vs 72 category score; HLE-Diamond (AA) 80.2% vs 67.9%	Medium
Knowledge	Claude Fable 5.2	82 vs 74 category score; AA-Omniscience v1.1 66.8 vs 48.1	High
Long documents	Either	66 vs 67 category score; AA-LCR v1.1 83.3% vs 84.7%	Either
Lowest cost	Claude Opus 5.5	$8.00 vs $16.00 per 1M blended; agentic coding session $0.320 vs $0.640	–
Fastest first answer	Claude Fable 5.2	3.0 s (Claude Fable 5.2 (max)) vs 380.6 s (Claude Opus 5.5 (max)) to the first answer token	–
High volume on a budget	Neither flagship	A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs	–

Key differences

Claude Fable 5.2 (max) and Claude Opus 5.5 (max) are neck and neck on quality (69.4 vs 68.9, within the ±7.4 margin).
Claude Fable 5.2 (max) is stronger in knowledge, reasoning.
Claude Opus 5.5 (max) is stronger in coding, long context, agents & tools, maths, multimodal.
Claude Opus 5.5 (max) is 2.0× cheaper ($8.00 vs $16.00 per 1M blended).
Claude Opus 5.5 (max) streams 1.6× faster (115 vs 72 tokens per second).

At a glance

Spec	Claude Fable 5.2	Claude Opus 5.5
Developer	Anthropic	Anthropic
Released	9 Nov 2026	22 Sep 2026
Context window (tokens)	1,000,000	1,000,000
Max output (tokens)	–	128,000 (up to 300K on the Message Batches API (beta))
Input types	–	text, image
Reasoning effort settings	–	low, medium, high, xhigh, max
Compared at	Claude Fable 5.2 (max)	Claude Opus 5.5 (max)
Open weights	No	No
Price in / out / cached input per 1M	$8.00 / $40.00 / $0.200	$4.00 / $20.00 / $0.200
API model ID	–	claude-opus-5-5
Where to use it	–	Claude API, Amazon Bedrock, Google Cloud, Microsoft Foundry

Limits, availability and announced prices from the vendors' own pages: platform.claude.com (checked 20 Oct 2026). Everything else is from the day's data.

Category by category

Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.

Category	Claude Fable 5.2 (max)	Claude Opus 5.5 (max)	Leader
Reasoning	78.4	72.3	Claude Fable 5.2
Coding	80.2	80.4	level
Agents & tools	–	62.7	not comparable
Maths	–	74.0	not comparable
Knowledge	81.7	73.7	Claude Fable 5.2
Multimodal	–	70.3	not comparable
Long context	66.4	67.1	level

On one chart

Each domain on the index's own scale, where 50 is an average model. Click a domain to see the benchmarks behind it. Pick up to 5 models from the list.

Not drawn, measured for fewer than two of these models: Agents & tools, Maths, Instruction following, Multimodal, Human preference.

ModelIndex

Where sources disagree

Across the 22 benchmarks both have, Claude Fable 5.2 leads 15, Claude Opus 5.5 leads 5 and 2 are tied. Every overall index that rates both puts Claude Fable 5.2 ahead.

Overall index	Claude Fable 5.2 (max)	Claude Opus 5.5 (max)	Leader
BenchLeader Index	69.4	68.9	neck and neck
AA Intelligence Index v5.0	64.6	59.1	Claude Fable 5.2
Vals Index	71.3†	70.1	Claude Fable 5.2

Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).

Price, speed and latency

List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page. Cost, tokens and time per benchmark task are measured: Artificial Analysis’ averages over its whole Intelligence Index run.

Measure	Claude Fable 5.2 (max)	Claude Opus 5.5 (max)
Blended price per 1M tokens	$16.00	$8.00
Input / output per 1M	$8.00 / $40.00	$4.00 / $20.00
Cached input per 1M	$0.200	$0.200
Price per task: chat reply	$0.015	$0.0076
Price per task: summarize a 30-page report	$0.120	$0.060
Price per task: code edit	$0.108	$0.054
Price per task: agentic coding session	$0.640	$0.320
Price per task: structured extraction	$0.024	$0.012
Agentic coding session, input mostly cached	$0.289	$0.149
Cost per benchmark task (AA Index)	$26.54	$10.04
Output tokens per task (AA Index)	274k	173k
Of which reasoning	193k	120k
Time per task (AA Index)	–	25 min
Output speed	72 tok/s	115 tok/s
Time to first answer	3.0 s	380.6 s
Time to a complete answer	–	771.1 s

Per token is not per task: an average task of Artificial Analysis' Intelligence Index cost $26.54 on Claude Fable 5.2 (max) and $10.04 on Claude Opus 5.5 (max), and Claude Fable 5.2 (max) wrote 1.6× as many output tokens for the same work, which a per-token price hides.

Each model is compared at its best-ranked reasoning-effort setting. Claude Fable 5.2 (max) scores 69.4 and takes 3 s to its first answer token; Claude Fable 5.2 (high) scores 68.9 in 3 s, Claude Fable 5.2 (xhigh) scores 68.7 in 3 s. Claude Opus 5.5 (max) scores 68.9 and takes 381 s to its first answer token; Claude Opus 5.5 (xhigh) scores 65.5 in 84 s, Claude Opus 5.5 (high) scores 65.4 in 28 s. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.

Every benchmark

135 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.

Metric	Publisher	Claude Fable 5.2 (max)	Claude Opus 5.5 (max)
BenchLeader Index	BenchLeader	69.4	68.9
Coding score	BenchLeader	80.2	80.4
Knowledge score	BenchLeader	81.7	73.7
Long context score	BenchLeader	66.4	67.1
Reasoning score	BenchLeader	78.4	72.3
Agents & tools score	BenchLeader	–	62.7
Maths score	BenchLeader	–	74.0
Multimodal score	BenchLeader	–	70.3
Blended price $/M	BenchLeader	$16.00	$8.00
Output speed	BenchLeader	72 tok/s	115 tok/s
Time to first answer	BenchLeader	3.0 s	380.6 s
Context window	BenchLeader	1,000,000 tokens	1,000,000 tokens
Reasoning
GPQA Diamond	Epoch AI Benchmarking Hub	–	90.6%
Arena Hard Prompts	Arena (LMArena)	–	1530†
LiveBench 2.0 Reasoning	LiveBench	88.8%†	92.2%†
LiveBench 1.0 Reasoning	LiveBench	–	92.2%
Humanity's Last Exam (AA)	Artificial Analysis	74.3%	61.4%
HLE-Diamond (AA)	Artificial Analysis	80.2%	67.9%
ARC-AGI-1	ARC Prize	97.5%	97.5%
ARC-AGI-2	ARC Prize	92.5%	91.7%
ARC-AGI-3	ARC Prize	94.9%	–
CritPt	Artificial Analysis	35.4%	31.7%
CritPt v2 hard subset (AA)	Artificial Analysis	76.5%	68.0%
MysteryMechanism	Vals AI	51.8%†	49.5%†
Chess Puzzles	Epoch AI Benchmarking Hub	–	67.0%
Mystery Game Puzzles	Epoch AI Benchmarking Hub	–	71.0%
LMCA	Epoch AI Benchmarking Hub	–	68.2%
DTBench	Epoch AI Benchmarking Hub	–	98.9%
Coding
SciCode	SciCode	–	66.9%
FrontierCode	Cognition	–	54.6%†
Arena Coding	Arena (LMArena)	–	1546†
Arena WebDev	Arena (LMArena)	–	1818
LiveBench 2.0 Coding	LiveBench	79.2%†	87.1%†
LiveBench 1.0 Coding	LiveBench	–	89.3%
SciCode (AA)	Artificial Analysis	67.7%	66.9%
IOI	Vals AI	–	95.1%†
Code Migration	Vals AI	–	66.7%†

Show all 135 benchmarks

Metric	Publisher	Claude Fable 5.2 (max)	Claude Opus 5.5 (max)
Coding
Code Migration v1.1	Vals AI	83.3%†	81.0%†
ProgramBench	Vals AI	19.0%†	18.5%†
SWE-bench Multimodal	Vals AI	62.3%†	70.2%†
Vibe Code Bench 1-100	Vals AI	–	30.4%†
Vibe Code Bench v1.1	Vals AI	93.8%†	90.3%†
MirrorCode	Epoch AI Benchmarking Hub	–	78.9%†
CursorBench	Cursor	–	57.8%
ALE-Bench	Epoch AI Benchmarking Hub	–	2147.4†
FrontierSWE	Epoch AI Benchmarking Hub	–	62.3%
Terminal-Bench 4.0 (AA)	Artificial Analysis	59.6%	59.6%
Startrise Frontend	Startrise	–	71.1%†
GameBench 2 Overall	DuelLab GameBench 2	–	87.6†
GameBench 2 by reasoning setting	DuelLab GameBench 2	–	94.8†
Design Arena Website	Design Arena	–	1325†
FrontierCode 1.1 (AA)	Artificial Analysis	56.2%	52.2%
FrontierCode 2.0 (AA)	Artificial Analysis	48.8%	46.4%
Agents & tools
Terminal-Bench	Terminal-Bench	–	65.8%
Remote Labor Index	Scale AI / CAIS	–	21.3%†
APEX-Agents	Mercor	–	73.5%
Arena Agent	Arena (LMArena)	–	20
LiveBench Long Agentic	LiveBench	82.9%†	72.8%†
LiveBench Browser	LiveBench	86.9%†	88.4%†
LiveBench Agentic Coding	LiveBench	–	71.7%
Terminal-Bench 2.1 (Vals)	Vals AI	–	87.6%†
MCP Atlas	Scale AI SEAL	–	85.4%†
HiL-Bench	Scale AI SEAL	–	59.0%†
GDPval-AA v2.1, normalised score	Artificial Analysis	–	68.3%
GDPval-AA v2.1	Artificial Analysis	1831	1866
ITBench SRE (AA)	Artificial Analysis	–	38.2%
Analyst Agent (AA)	Artificial Analysis	–	56.3%
CUA-bench	Vals AI	–	14.0%
CyberBench	Vals AI	–	55.4%†
Finance Agent v2	Vals AI	–	58.6%†
Finance Agent v2.1	Vals AI	69.5%†	67.8%†
Harvey's Legal Agent Benchmark v1.1	Vals AI	5.0%†	9.2%†
Harvey's Legal Agent Benchmark v1	Vals AI	–	3.8%†
Legal Research Bench	Vals AI	46.1%†	50.5%†
Robo-bench	Vals AI	–	14.6%
SREBench	Vals AI	–	33.6%†
Tax Agent Bench	Vals AI	32.1%†	44.5%†
Terminal-Bench 4.0 (Vals)	Vals AI	65.2%†	65.2%†
Terminal-Bench Science	Vals AI	55.7%†	47.1%†
Time Horizon Index: KSP	Vals AI	–	91.3%†
Arena Search	Arena (LMArena)	–	1214†
Vending-Bench 2	Andon Labs	–	9235.3†
AutomationBench	Artificial Analysis	76.4%	69.5%
GDP.pdf (AA)	Artificial Analysis	24.2%	26.2%
Harvey LAB-AA v1.1	Harvey	7.2%	4.2%
AA-Briefcase v1.1	Artificial Analysis	1785	1800
GDPx	GDPx by SemiAnalysis	–	12.0%
Design Arena Agentic	Design Arena	–	1334†
Terminal-Bench-Science 0.1 (AA)	Artificial Analysis	73.3%	59.0%
CWE-Bench (AA)	Artificial Analysis	–	58.3%
DeepSec-Bench (AA)	Artificial Analysis	–	26.9%
CyberGym end-to-end (AA)	Artificial Analysis	–	0.8%
FACTS Search	Google	–	88.4%†
Maths
FrontierMath Tiers 1–3	Epoch AI Benchmarking Hub	–	91.2%
FrontierMath Tier 4	Epoch AI Benchmarking Hub	–	95.0%
OTIS Mock AIME	Epoch AI Benchmarking Hub	–	100.0%
ProofBench	Vals AI	–	100.0%
LiveBench Mathematics	LiveBench	–	97.1%
Arena Maths	Arena (LMArena)	–	1518†
Knowledge
SimpleQA Verified	Epoch AI Benchmarking Hub	–	72.2%
LiveBench 2.0 Data Analysis	LiveBench	81.5%†	80.3%†
LiveBench Research	LiveBench	94.5%†	88.9%†
LiveBench 1.0 Data Analysis	LiveBench	–	80.3%
AA-Omniscience v1.1	Artificial Analysis	66.8	48.1
PRBench Legal	Scale AI SEAL	–	47.6%†
BioMysteryBench	Vals AI	83.7%†	79.3%†
ClaimBench	Vals AI	–	100.0%†
Excel Modeling Benchmark	Vals AI	–	75.9%†
Excel Modeling Benchmark v1.1	Vals AI	77.4%†	75.8%†
MedCode	Vals AI	–	49.8%†
MedScribe	Vals AI	–	91.4%†
Public Benefits Bench v1.1	Vals AI	–	70.6%†
EBR-bench	Epoch AI Benchmarking Hub	–	71.4%
GDP.pdf	Epoch AI Benchmarking Hub	–	30.6%
AA-Omniscience v1.1: accuracy	Artificial Analysis	79.1%	65.5%
AA-Omniscience v1.1: non-hallucination	Artificial Analysis	40.7%	49.7%
HealthBench Professional (AA)	OpenAI	67.7%	59.9%
Instruction following
LiveBench Language	LiveBench	–	86.3%
LiveBench Instruction Following	LiveBench	–	65.7%
Arena Instruction Following	Arena (LMArena)	–	1519†
Human preference
Arena Text	Arena (LMArena)	–	1506†
EQ-Bench 4	EQ-Bench	–	1340†
Arena Creative Writing	Arena (LMArena)	–	1517†
Arena Multi-turn	Arena (LMArena)	–	1500†
Arena Longer Queries	Arena (LMArena)	–	1520†
Multimodal
Arena Vision	Arena (LMArena)	–	1324†
LiveBench Design	LiveBench	85.1%†	83.3%†
MMMU-Pro	Artificial Analysis	–	87.7%
SAGE	Vals AI	–	91.3%†
Blueprint-Bench 2	Epoch AI Benchmarking Hub	–	51.2%†
Code2Video-AA	Artificial Analysis	–	1536
AA-3D	Artificial Analysis	1271	1202
Long context
AA-LCR v1.1	Artificial Analysis	83.3%	84.7%
MLCR	Artificial Analysis	–	27.8%
Composite
Epoch Capabilities Index	Epoch AI Benchmarking Hub	–	168.4†
LiveBench 2.0	LiveBench	84.9%†	83.4%†
LiveBench 1.0	LiveBench	–	83.2%
AA Intelligence Index v5.0	Artificial Analysis	64.6	59.1
AA Intelligence Index v4.3.2	Artificial Analysis	–	57.6
AA Progress Index v1	Artificial Analysis	–	350
Vals Index	Vals AI	71.3†	70.1†
Vals Finance Index	Vals AI	63.6%†	65.3%†
Vals RSI Index	Vals AI	–	37.3%
Vals Science Index	Vals AI	63.7%†	58.6%†
Vals Router Index	Vals AI	–	64.2%†
AA Cyber Index	Artificial Analysis	–	28.7
Safety & honesty
FORTRESS	Scale AI SEAL	–	5.8%

Data as of 2026-11-09. Best configuration of each model; every score links to its source on the model pages.

DuelLab GameBench 2, release gb2-20261103-eaea31df94e6 (https://benchmarks.duellab.org/releases/gb2-20261103-eaea31df94e6/), CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Scores mapped to BenchLeader model names; not endorsed by DuelLab.

What changed

9 Nov 2026 Claude Opus 5.5 (max): 2 score revisions.
8 Nov 2026 Claude Opus 5.5 (max): 1 score revision.
5 Nov 2026 Claude Opus 5.5 (max): 1 score revision.
4 Nov 2026 Claude Opus 5.5 (max): 2 score revisions.
3 Nov 2026 Claude Opus 5.5 (max): 2 score revisions.
31 Oct 2026 Claude Opus 5.5 (max): 1 score revision.
28 Oct 2026 Claude Opus 5.5 (max): 5 new results (AA Intelligence Index v5.0, AA Progress Index v1, HLE-Diamond (AA)…); 3 score revisions; cost per task moved from $5.98/M to $10.04/M (68% up).
25 Oct 2026 Claude Opus 5.5 (max): 1 score revision.
23 Oct 2026 Claude Opus 5.5 (max): 2 new results (Robo-bench, Vals RSI Index).
21 Oct 2026 Claude Opus 5.5 (max): 2 score revisions.

Rankings: Best LLM overall · Best LLM for coding · Best LLM for agents · Best cheap LLMs