Claude Opus 4.8 vs GPT-4o
| Spec | Claude Opus 4.8 | GPT-4o |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Input price (per 1M) | $5.00 | $2.50 |
| Output price (per 1M) | $25.00 | $10.00 |
| Context window | 200,000 | 128,000 |
| Tokenizer accuracy | exact (uses official tokenizer) | exact (uses official tokenizer) |
Cost per 1,000 calls across common workloads
| Workload | Claude Opus 4.8 | GPT-4o | Winner |
|---|---|---|---|
| Short chat (200 in / 100 out) |
$3,500.00 | $1,500.00 | GPT-4o 57% cheaper |
| Medium chat (1,000 in / 500 out) |
$17,500.00 | $7,500.00 | GPT-4o 57% cheaper |
| Heavy generation (1,000 in / 2,000 out) |
$55,000.00 | $22,500.00 | GPT-4o 59% cheaper |
| Long context (8,000 in / 500 out) |
$52,500.00 | $25,000.00 | GPT-4o 52% cheaper |
| Code review (3,000 in / 600 out) |
$30,000.00 | $13,500.00 | GPT-4o 55% cheaper |
Costs are per 1,000 API calls. Multiply by 1,000 for per-million-calls.
Verdict
They're priced for different jobs. GPT-4o is the default workhorse for production AI. Claude Opus 4.8 is Anthropic's frontier-reasoning model, meaningfully more capable on hard problems, meaningfully more expensive per call once you account for both the per-token rate AND Opus's larger tokenizer.
If you're choosing between them on cost, GPT-4o usually wins. If you're choosing on capability for hard problems, Opus often does.
Cost example
For a 1,000-token prompt with a 200-token reply:
GPT-4o: 1000 × $2.50/M + 200 × $10/M = $0.0045 per call
Claude Opus: 1000 × $5/M + 200 × $25/M = $0.0100 per callOpus costs ~2.2× more per call at this ratio. For 1,000,000 calls per month: $4,500 vs $10,000, a $5,500 difference.
But there's a wrinkle:
The Opus 4.8 tokenizer surcharge
Anthropic ships Opus 4.8 with a new tokenizer that can produce up to 35% more tokens than the older Claude tokenizer for the same text. So that "1,000-token prompt" measured by GPT-4o's tokenizer might come out to ~1,350 tokens when Opus tokenizes it, pushing your effective Opus call closer to $0.0135, closer to 3× GPT-4o's cost for the same prompt.
The token counter on the home page shows you the actual count from each provider's official tokenizer, so the comparison stays honest. Just don't assume "tokens" mean the same thing across providers.
When the Opus premium is worth it
- Multi-step reasoning where a wrong intermediate step compounds badly.
- Architecture and design decisions in code where the wrong choice costs days.
- Long-form writing where voice, structure, and nuance materially affect outcomes.
- High-stakes single-shot generation, legal drafts, executive summaries, customer-facing content where one mistake is expensive.
When GPT-4o is enough (almost always)
- Routine chat and Q&A.
- RAG over routine documents.
- Code generation on greenfield problems.
- Classification, extraction, summarization.
- High-volume anything.
For most production workloads, GPT-4o is indistinguishable from Opus, and 2-3× cheaper after accounting for the tokenizer change.
The honest comparison: Opus vs Sonnet vs GPT-4o
If you've ruled in Claude for instruction-following nuance, the relevant comparison is Sonnet vs Opus, not Opus vs GPT-4o:
| Model | Input | Output | Use for |
|---|---|---|---|
| GPT-4o | $2.50 | $10 | Most production work |
| Claude Sonnet 4.6 | $3.00 | $15 | When Claude's instruction-following matters |
| Claude Opus 4.8 | $5 | $25 | When Sonnet measurably falls short |
Don't reach for Opus before you've measured Sonnet failing on your task, Sonnet costs ~60% of Opus per token AND uses the older Claude tokenizer (no 35% surcharge).