OpenAI o-series vs Claude — reasoning models
o-series vs Claude is the reasoning-model matchup: OpenAI’s models that spend extra tokens (or time) thinking versus Anthropic’s frontier Claude rows, some of which also offer extended thinking. You are comparing how much you pay for deliberation, not just “which logo is smarter.”
Reasoning SKUs can look expensive per million tokens and still be cheaper per correct hard problem if they need fewer retries. Compare list prices, then measure tokens actually used on your eval set. The arena’s latency metrics matter here more than on a flash classifier.
Highest quality index right now
Live OpenRouter pricing and Arena quality, cached about an hour. Not a static blog table.
| Model | Provider | Blend $ / 1M | Quality | Context |
|---|---|---|---|---|
| Qwen3.8 Max (0902) | Qwen | 4.00 | 95.1 | 1,000,000 |
| Claude Opus 5 | Anthropic | 15.00 | 93.4 | 1,000,000 |
| Claude Fable 5 | Anthropic | 30.00 | 91.1 | 1,000,000 |
| GLM 5.3 Flash | Z.ai | 0.16 | 89.7 | 1,048,576 |
| Qwen3.8 27B | Qwen | 1.71 | 89.0 | 1,000,000 |
What “reasoning model” means on a bill
Some APIs bill hidden chain-of-thought tokens; some bill more output; some add a request surcharge. OpenRouter’s prompt and completion prices are the numbers we surface. If a vendor hides thinking tokens, your real cost is higher than the blend. Log token usage on a sample of jobs before you pick a default.
Claude extended thinking
Anthropic’s thinking modes are the fair comparison to o-series, not a non-thinking Sonnet against o3. If the catalog lists separate ids, compare those ids. If thinking is a parameter on one id, the leaderboard row is an average — confirm in the provider docs.
When not to use either
Classification, extraction, and “rewrite this email” rarely need a reasoning SKU. Paying frontier reasoning rates for those jobs is how LLM bills explode. Keep o-series/Claude-thinking for math, hard coding, and planning; use flash/haiku/mini for the rest.
Quality index bias
Arena votes include whatever models people paste into chat. Reasoning models may be under- or over-represented. Treat a 3-point quality gap as noise; treat a 15-point gap as a shortlist signal.
Bake-off design
Take 20 hard items you already know the answer to. Run o-series and Claude with thinking on, measure accuracy, tokens, and latency. Pick the cheaper correct model. If they tie on accuracy, pick the faster one for interactive use and the cheaper one for batch.
FAQ
Is o-series better than Claude at reasoning?
- On some math and coding evals, yes; on others, no. Use your items. Public Elo is not a theorem-prover ranking.
Why are reasoning models expensive?
- They generate more tokens (and sometimes hidden tokens) per answer. Cost per correct answer can still be lower if they fail less.
Can I mix o-series and Claude?
- Yes. Route easy traffic to a cheap model and hard traffic to whichever reasoning SKU wins your eval.
Where do I see current prices?
- Model detail pages and the compare table, using live OpenRouter catalog data.
Related guides
Also try: LLM leaderboard, compare tool, live arena.