score
Claude Sonnet 5 (Non-reasoning, High Effort) scores 42 on the Artificial Analysis Intelligence …
vs class avg: 17
Intelligence, Performance & Price Analysis
score
Claude Sonnet 5 (Non-reasoning, High Effort) scores 42 on the Artificial Analysis Intelligence …
vs class avg: 17
/ 1M tokens
Claude Sonnet 5 (Non-reasoning, High Effort) costs $2.00 per 1M input tokens (better than average, …
/ 1M tokens
Claude Sonnet 5 (Non-reasoning, High Effort) costs $2.00 per 1M input tokens (better than average, …
This profile does not provide this metric.
This profile does not provide this metric.
Ethen's intelligence-driven routing assessment for this model
Overall verdict
Frontier research / complex reasoning
Reserve this model for the hardest requests; simpler or repetitive work should stay on cheaper routes.
Routing recommendation
Lower-cost models for repetitive or high-volume work
Cache-backed reuse for repeated prompts
Cost pressure
Premium pricing — $2.00 / M input, $10.00 / M output. Use cheaper routes for repetitive or low-risk work.
Use this model where capability pays for itself; route away where volume, latency, or budget dominate.
| Use case | Fit | Reason | Routing note |
|---|---|---|---|
| Complex reasoning & agentic workflows | Excellent | Intelligence score 42 places this model among top performers. Suitable for multi-step analysis and agentic loops. | Route complex tasks here; reserve simpler queries for cheaper models. |
| Cost-sensitive pipelines | Moderate | Output pricing at $10.00 is premium. Route high-volume simple tasks to cheaper alternatives. | Use only for high-value tasks; route simple queries to budget models. |
Cost pressure
HighPricing is premium — input $2.00, output $10.00. This model is expensive for high-volume or output-heavy workloads.
Key benchmark results at a glance.
Intelligence
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
Claude Sonnet 5 (Non-reasoning, High Effort) scores 42 on the Artificial Analysis Intelligence Index, placing it well above average among other non-reasoning models in a similar price tier (median: 17).
Speed
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Higher throughput supports faster interactive use.
Context, Cost & Pricing
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Pricing is premium — input $2.00, output $10.00. This model is expensive for high-volume or output-heavy workloads.
Benchmark scores and quality indices measuring model capability.
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. · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Output tokens per second and generation throughput.
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Context window size, cost per task, and token pricing.
Context window: tokens limit · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Weighted average cost (USD) per Artificial Analysis Intelligence Index task, segmented by token type. Lower is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Price (USD per M Tokens) · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Further benchmark and comparison data.
Weighted average number of output tokens used to run one task in the Artificial Analysis Intelligence Index · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Claude Sonnet 5 (Non-reasoning, High Effort) scores 42 on the Artificial Analysis Intelligence Index, placing it well above average among other non-reasoning models in a similar price tier (median: 17). Claude Sonnet 5 (Non-reasoning, High Effort) costs $2.00 per 1M input tokens (better than average, median: $1.88) and $10.00 per 1M output tokens (somewhat higher than average, median: $7.75), based on Anthropic's API.
This page is rendered from the normalized profile and page JSON for Claude Sonnet 5 (Non-reasoning).
Benchmark values are preserved as normalized; only layout, disclosure ordering, and typography are adjusted for readability.