Why Compare All Anthropic + OpenAI Models Together
Once you've narrowed a model shortlist on the main TokenRate calculator, the Compare Prices side-by-side view is where you stack them for a decision. Each row shows the provider, the model ID (the one you'd paste into your SDK), per-1M input and output costs, the context window, and the blended quality score. Picking between Anthropic + OpenAI's models — flagship, mid-tier, fast — is usually done by reading the provider's pricing page top-to-bottom, which buries the spread. The Compare Prices grid flips that: you check **every Anthropic + OpenAI model** in one dropdown and the grid lays them out side-by-side. Input cost across the lineup spans $0.150 to $15.00 per 1M tokens — a 100.0× spread you can scan in three seconds. This guide walks through the lineup model-by-model with the framing of "what do you give up to step down a tier." For the underlying math, see tokens-to-dollars conversion; for routing strategy see multi-model routing with quality scores.
The Anthropic + OpenAI Lineup, Top to Bottom
**Claude Opus 4** — $15.00 input / $75.00 output per 1M, 200K context, quality 85, tier **flagship**. flagship tier is for frontier-quality use cases where the per-token price is a rounding error against the value of the output. **Claude Sonnet 4.7** — $3.00 input / $15.00 output per 1M, 200K context, quality 80, tier **balanced**. balanced tier is the production-default zone — quality high enough for customer traffic, price low enough to scale. **Claude Haiku 4.5** — $1.00 input / $5.00 output per 1M, 200K context, quality 65, tier **fast**. fast tier is built for high-volume throughput at the lowest per-token rate the provider offers. **GPT-5** — $1.25 input / $10.00 output per 1M, 200K context, quality 82, tier **flagship**. flagship tier is for frontier-quality use cases where the per-token price is a rounding error against the value of the output. **GPT-5 mini** — $0.300 input / $2.40 output per 1M, 128K context, quality 70, tier **balanced**. balanced tier is the production-default zone — quality high enough for customer traffic, price low enough to scale. **GPT-4o mini** — $0.150 input / $0.600 output per 1M, 128K context, quality 55, tier **fast**. fast tier is built for high-volume throughput at the lowest per-token rate the provider offers. **OpenAI o3** — $10.00 input / $40.00 output per 1M, 200K context, quality 86, tier **reasoning**. reasoning tier uses chain-of-thought and costs more per output token but answers harder questions correctly. **OpenAI o3-mini** — $1.10 input / $4.40 output per 1M, 200K context, quality 72, tier **reasoning**. reasoning tier uses chain-of-thought and costs more per output token but answers harder questions correctly. All five attributes (input, output, context, quality, tier) live in the Compare Prices grid, which makes the cross-tier deltas obvious. Stepping from OpenAI o3 (Q86, $10.00) down to GPT-4o mini (Q55, $0.150) saves 99% on input at a cost of 31 quality points — the right tradeoff if your workload tolerates the quality drop.
Where Each Anthropic + OpenAI Model Earns Its Place
**Claude Opus 4**: best for customer-facing premium experiences, complex writing/code, low-volume high-value queries where the cost is dwarfed by what the answer is worth. **Claude Sonnet 4.7**: best for production routing default — chatbots, RAG answer synthesis, structured output, anything that ships to real users at scale. **Claude Haiku 4.5**: best for high-volume classification, lightweight summarization, embeddings-adjacent tasks, prefilters and triage stages, draft generation. **GPT-5**: best for customer-facing premium experiences, complex writing/code, low-volume high-value queries where the cost is dwarfed by what the answer is worth. **GPT-5 mini**: best for production routing default — chatbots, RAG answer synthesis, structured output, anything that ships to real users at scale. **GPT-4o mini**: best for high-volume classification, lightweight summarization, embeddings-adjacent tasks, prefilters and triage stages, draft generation. **OpenAI o3**: best for multi-step reasoning, math, code that requires planning, and any task where chain-of-thought has been shown to lift accuracy. **OpenAI o3-mini**: best for multi-step reasoning, math, code that requires planning, and any task where chain-of-thought has been shown to lift accuracy. This isn't marketing copy — it's how the tier classification on TokenRate's filter panel actually slots them. If you've already filtered to a tier, the Compare Prices grid is the next step: check the relevant Anthropic + OpenAI models alongside their cross-provider peers (e.g., GPT-4o mini next to Gemini Flash, or OpenAI o3 next to GPT-5 and Grok 4) to confirm you're not paying a provider premium.
Cost Multipliers When Stepping Up a Tier
Within Anthropic + OpenAI's lineup, the step-up multipliers are stark. Input: GPT-4o mini → OpenAI o3 is 66.7×. Output: 66.7×. Quality: +31 points. The question to ask: is +31 quality points worth 66.7× the per-token cost? For agentic or accuracy-critical workloads, yes — quality wins are non-linear in user value. For high-volume classification or templated content, no — the cheaper model clears the bar. Use the API cost estimator to put a dollar figure on the step-up at your workload volume.
Compare-Prices Across Providers, Not Just Within
The most common mistake when picking within Anthropic + OpenAI's lineup is forgetting that cross-provider competitors may dominate the chosen tier. Once you've picked your Anthropic + OpenAI candidates, add 1-2 competitors from a different provider dropdown — for the balanced tier, comparing Anthropic + OpenAI's mid-model against Gemini 2.5 Pro and Claude Sonnet 4.7 is usually instructive. The Compare Prices grid was designed for exactly this multi-provider workflow. Both the price denominator (OpenRouter) and the quality numerator (Arena AI + Artificial Analysis) refresh hourly. So the comparison you screenshot Monday morning is still trustworthy at standup Tuesday morning — but you should re-run it before a quarterly model-routing review. Run the comparison live at /tools/compare-prices, then bookmark the URL for next month's price audit.