TokenAtlasPricing head-to-head
GPT-4o: $2.50 in / $10 out. Claude 3.5 Sonnet: $3 in / $15 out. GPT-3.5: $0.50 in / $1.50 out. Claude Haiku: $0.25 in / $1.25 out. Haiku is the cheapest production-grade model in this matchup.
Capability differences
Claude leads on long-context comprehension and structured output. GPT-4o leads on real-time multimodal and tool-use orchestration. For 80% of business tasks both are interchangeable.
Total cost of ownership
OpenAI's prompt caching (50% off) and Anthropic's caching (90% off) move TCO significantly. On a 100K-token system prompt, Claude with caching is materially cheaper than GPT-4o without it.
Verdict
Pick Claude for document-heavy workflows. Pick GPT-4o for tool-using agents. Use TokenAtlas to confirm with your actual volume — the right answer depends on your traffic shape.
A concrete monthly bill
At 15M input tokens and 6M output tokens a month: GPT-4o = (15M x $2.50) + (6M x $10) = $37.50 + $60 = $97.50. Claude 3.5 Sonnet = (15M x $3) + (6M x $15) = $45 + $90 = $135. Sonnet is $37.50/month higher, about 38%, at this 2.5:1 input:output ratio — before either provider's prompt-caching discount is applied.
How caching changes the break-even point
Say a 100K-token system prompt is reused across 500 calls a month, each returning 500 output tokens. Uncached: GPT-4o = (50M x $2.50) + (0.25M x $10) = $125 + $2.50 = $127.50; Claude = (50M x $3) + (0.25M x $15) = $150 + $3.75 = $153.75. With OpenAI's stated 50% cache discount on the repeated input and Anthropic's stated 90%: GPT-4o becomes (50M x $1.25) + $2.50 = $65; Claude becomes (50M x $0.30) + $3.75 = $18.75. The heavier discount flips the ranking — caching, not list price, decides the winner for repeated-context workloads.
Where picking on list price alone goes wrong
A team that reads only the headline per-token rate and defaults to GPT-4o for a large, repeated-system-prompt workload would overpay once caching is factored in, as shown above. Conversely, a team that assumes Claude is 'always cheaper with caching' without a stable, reused prompt gets none of that 90% discount and pays the higher uncached per-token rate instead.
Running this on your own numbers
You need three inputs per workload: monthly input tokens, monthly output tokens, and how much of your input is an unchanged, cacheable prefix versus unique per-call content. Enter both scenarios (cached and uncached) into TokenAtlas for each provider — the reused-prompt share is usually what moves the answer, not the base rate.
What this pricing comparison can't settle
It doesn't tell you which model follows instructions better on your prompts, handles your tool schema more reliably, or produces fewer factual errors — judge those on your own eval set. Rate limits, data-retention terms, and regional availability also aren't captured in a per-token number and should be checked separately.
Frequently asked questions
- Which has better rate limits?
- OpenAI's Tier 5 limits are higher by default; Anthropic catches up at enterprise tier.
- Which is safer for regulated industries?
- Both offer HIPAA-eligible enterprise tiers. Anthropic's constitutional AI policy stack is preferred by some compliance teams.
- Can I run both?
- Yes — multi-provider routing is a TokenAtlas Pro feature.