Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) Intelligence, Performance & Price Analysis

artificialanalysis.ai · 2026-09-28 · by Long Nguyen ·generic
Analysis of Anthropic's Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) and comparison to other AI models across key metrics including quality, price, performance (tokens per second & time to first token), context window & more.

Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) Intelligence, Performance & Price Analysis

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Anthropic

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Claude Sonnet 5.5max

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Proprietary model

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Released September 2026

Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) Intelligence, Performance & Price Analysis

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Model summary

#### IntelligenceUpdated

#3 / 216

56

Artificial Analysis Intelligence Index

4 out of 4 units for Intelligence.

#### Speed

N/A

Output tokens per second

Unknown out of 4 units for Speed.

#### Cost

#98 / 216

In $2.00Out $10.00Cache Discount 90%

$7.60

Cost per Intelligence Index task

4 out of 4 units for Cost.

#### Verbosity

#102 / 216

410M

Output tokens from Intelligence Index

4 out of 4 units for Verbosity.

Comparison Summary

Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) is amongst the leading models in intelligence and reasonably priced when comparing to other models of similar price. The model supports text and image input, outputs text, and has a 1M tokens context window.

Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) scores 56 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models (median: 26). When evaluating the Intelligence Index, it generated 410M tokens, which is very verbose in comparison to the median of 88M.

Pricing for Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) is $2.00 per 1M input tokens (moderately priced, median: $2.00) and $10.00 per 1M output tokens (moderately priced, median: $10.00). On average, it costs $7.60 per task to evaluate Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) on the Intelligence Index.

Technical specifications

| Reasoning | YesThis page shows the reasoning version of this model.A non-reasoning variant may also exist. | | --------------- | ---------------------------------------------------------------------------------------------- | | Input modality | Supports: text and image | | Output modality | Supports: text | | Context window | 1M\~1500 A4 pages of size 12 Arial font |

216 models in this class

Metrics are compared against models of the same class:

  • Non-reasoning models → compared only with other non-reasoning models
  • Reasoning models → compared across both reasoning and non-reasoning
  • Open weights models → compared only with other open weights models of the same size class:
  • * Tiny: ≤4B parameters * Small: 4B–40B parameters * Medium: 40B–150B parameters * Large: >150B parameters
  • Proprietary models → compared across proprietary and open weights models of the same price range, using a blended 3:1 input/output price ratio:
* <$0.15 per 1M tokens * $0.15–$1 per 1M tokens * \>$1 per 1M tokens

Highlights

Updated

Intelligence

Artificial Analysis Intelligence Index · Higher is better

Speed

Output tokens per second · Higher is better

Cost per Task

Weighted average cost (USD) per Intelligence Index task · Lower is better

Prompt Options

IntelligenceUpdated

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.3.2 incorporates 10 evaluations: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1

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###

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Open Weights / ProprietaryReasoning / Non-ReasoningText Only / Multimodal Inputs

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Artificial Analysis Intelligence Index v4.3.2 incorporates 10 evaluations: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1

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ProprietaryOpen WeightsOpen Weights (Commercial Use Restricted)

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Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

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Open Weights

Indicates whether the model weights are available. Models are labelled as 'Commercial Use Restricted' if commercial use is limited by conditions, and as 'Non-commercial' if the license prohibits commercial use.

Capability Indexes

Measures the performance of models on specific capabilities and industries

Finance & AccountingStrategy & OpsLegalEngineeringEconomics

Artificial Analysis Finance & Accounting Index

Incorporates 7 evaluations: AA-Omniscience, GDPval-AA v2.1, AA-Briefcase v1.1, Humanity's Last Exam, AutomationBench-AA, AA-LCR v1.1, GDP.pdf · Higher is better

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Benchmarks

Intelligence Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better

CodingAgenticTool UsePrivate DatasetUser InteractionFinanceMedicalLegalIntelligence IndexLong ContextMultimodalInstruction FollowingFaithfulnessWritingBusinessSee more

19 of 27 evaluations

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AA-Briefcase v1.1Updated

Agentic knowledge work, (Elo-500)/2000

GDPval-AA v2.1Updated

Agentic real-world work tasks, (Elo-500)/2000

AutomationBench-AAUpdated

Agentic SaaS workflows

Terminal-Bench 4.0New

Agentic coding & terminal use

SciCode

Coding

Humanity's Last Exam

Reasoning & knowledge

GDP.pdfNew

Professional document reasoning, All-pass

CritPtUnder review

Physics reasoning

AA-Omniscience Accuracy

Knowledge

AA-Omniscience Non-Hallucination Rate

1 - hallucination rate

AA-LCR v1.1

Long context reasoning

Harvey LAB-AA

Legal agentic work, criterion pass rate

EnterpriseOps-Gym-AA

Agentic business operations

Terminal-Bench-Science 0.1New

Agentic scientific research workflows in a terminal

AA-AnalystAgent

Quantitative analysis on spreadsheets & documents

𝜏³-Banking

Agentic tool use

ITBench-AA

Kubernetes incident root-cause analysis

MMMU-Pro

Visual reasoning

MLCR-AA

Medical long context reasoning

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Intelligence Evaluation Relevance

While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.

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Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

AA-Briefcase v1.1Updated

AA-Briefcase EloAA-Briefcase Rubric Score (%)Analytical Quality & Presentation Elo

AA-Briefcase Elo

AA-Briefcase v1.1 is an agentic knowledge work benchmark developed by Artificial Analysis. AA-Briefcase Elo is a combined metric that aggregates rubric pass rate, analytical quality Elo and presentation Elo · Higher is better

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AA-Briefcase Elo

AA-Briefcase Elo is a combined metric that aggregates analytical quality Elo, presentation Elo, and rubric pass rate, with rubric performance converted into Elo via synthetic head-to-head matches. Elo and 95% confidence interval bounds are clamped at 0.

AA-Omniscience

AA-Omniscience IndexAA-Omniscience AccuracyAA-Omniscience Hallucination Rate

AA-Omniscience Index

AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct.

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AA-Omniscience Index

AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct.

Intelligence Index Comparisons

Intelligence Index vs. Cost per TaskIntelligence Index vs. Time per TaskIntelligence Index vs. Output SpeedIntelligence Index vs. End-to-End Response Time

Intelligence Index vs. Cost per Intelligence Index Task

Artificial Analysis Intelligence Index · Weighted average cost (USD) per Artificial Analysis Intelligence Index task

28 of 679 models

Most attractive quadrant

Pareto line

AnthropicXiaomiOpenAISpaceXAIGoogleMetaZ AIDeepSeek

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Cost per Intelligence Index Task

Weighted average cost per Intelligence Index task. Each evaluation’s cost is calculated from input, cache hit, cache write, reasoning, and answer token prices, divided by task count, and weighted by its Intelligence Index weight.

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Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Token Use

Output Tokens per TaskIntelligence Index vs. Output Tokens per TaskIntelligence Index Token UseIntelligence Index vs. Token Use

Output Tokens per Intelligence Index Task

Weighted average number of output tokens used to run one task in the Artificial Analysis Intelligence Index

28 of 679 models

AnswerReasoning

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Output Tokens per Intelligence Index Task

The number of tokens required per Intelligence Index task. This is calculated by multiplying the output tokens per eval by the relative weights of each benchmark in the Intelligence Index, then dividing by task count (excluding repeats).

Cost

Cost per TaskIntelligence Index vs. Cost per TaskEvaluation Breakdown

Cost per Intelligence Index Task

Weighted average cost (USD) per Artificial Analysis Intelligence Index task, segmented by token type. Lower is better

28 of 679 models

AnswerReasoningCache WriteCache HitInput

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Cost per Intelligence Index Task

Weighted average cost per Intelligence Index task. Each evaluation’s cost is calculated from input, cache hit, cache write, reasoning, and answer token prices, divided by task count, and weighted by its Intelligence Index weight.

Intelligence Index Total CostIntelligence Index vs. Total Cost

Cost to Run Artificial Analysis Intelligence Index

Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index

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OutputReasoningCache WriteCache ReadNon-Cache Input

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Cost to Run Artificial Analysis Intelligence Index

The cost to run the evaluations in the Artificial Analysis Intelligence Index, calculated using the model's input, cache hit, cache write, reasoning, and answer token prices and the number of tokens used across evaluations (excluding repeats).

Cache Hit, Input, and Output PricingBlended PriceBlended Price (Stacked)Cache DiscountIntelligence Index vs. PriceIntelligence Index vs. Price (Log, Inverted)Image Input Pricing

Pricing: Cache Hit, Input, and Output

Price (USD per M Tokens)

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Cache HitInputOutput

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Cache Hit

Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail.

4 more notes

Context Window

Context WindowIntelligence Index vs. Context Window

Context Window

Context window: tokens limit · Higher is better

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Context Window for RAG

Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.

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Context Window

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

Frequently Asked Questions

Common questions about Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback)

When was Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) released?

Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) was released on September 28, 2026.

Who created Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback)?

Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) was created by Anthropic.

How intelligent is Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback)?

Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) scores 56 on the Artificial Analysis Intelligence Index, placing it well above average among other reasoning models in a similar price tier (median: 26).

How much does Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) cost?

Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) costs $2.00 per 1M input tokens (better than average, median: $2.00) and $10.00 per 1M output tokens (better than average, median: $10.00), based on Anthropic's API.

What is Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) API pricing?

Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) costs $2.00 per 1M input tokens and $10.00 per 1M output tokens (based on Anthropic's API). For a blended rate (7:2:1 cache hit/input/output ratio), this is $1.54 per 1M tokens. Pricing may vary by provider. Compare provider pricing

How verbose is Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback)?

When evaluated on the Intelligence Index, Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) generated 410M output tokens, which is at the higher end compared to other reasoning models in a similar price tier (median: 88M).

Is Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) a reasoning model?

Yes, Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.

What input modalities does Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) support?

Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) supports text and image input.

What output modalities does Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) support?

Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) supports text output.

Can Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) process images?

Yes, Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) supports image input and can analyze, describe, and answer questions about images.

Is Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) multimodal?

Yes, Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) is multimodal. It can process text and image input and generate text output.

What is the context window of Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback)?

Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) has a context window of 1.0M tokens. This determines how much text and conversation history the model can process in a single request.

Is Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) open source?

No, Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) is proprietary. The model weights are not publicly available.

How many parameters does Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) have?

Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) is a proprietary model and Anthropic has not disclosed the model size or parameter count.

How does Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) perform on benchmarks?

Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) achieves a score of 56 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.

Is Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) available via API?

Yes, Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) is available via API through 1 provider. Compare API providers

Where can I use Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback)?

Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) is available through 1 API provider. Compare providers

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