llmcloud.ai
Model scorecard

Anthropic claude-sonnet-4.5

Composite 69.0/100 across quality, throughput, latency, price efficiency and usable context — measured through the gateway, not vendor-reported.

B+69.0/100anthropic/claude-sonnet-4.5text · vision · 200k context

Capability

eval composite
Quality (blended eval)91

Category: coding

Usable context10

200k advertised window

Serving

gateway measured
Throughput34

118 output tokens/s median

Time to first token63

220ms p50

Economics

at provider cost
Price efficiency64

$3.00 per 1M output tokens

Quality per dollar91
llmcloud adds $0 to these token prices.

Suggested usage

  • Coding agentauto:coding

    Highest diff fidelity per dollar; holds multi-file edits without re-reading the repo.

  • Function calling & agentsauto:tools

    Schema conformance under a wide tool set matters more than raw reasoning score.

  • High-volume product chatauto:cost + cache

    Semantic caching does more for the bill here than any model swap.

→ Full workload matrix