First Impressions
On February 17, 2026, I reran this comparison from scratch using primary funding announcements, Reuters/AP reporting, and live API pricing pages. The first surprise was not model quality. It was timing risk: Anthropic has a fresh valuation print at $380 billion from February 2026, while OpenAI’s last officially confirmed valuation on its own site is still $300 billion from March 31, 2025. That alone changes how confident you can be in each headline number. Fresh data beats loud data.
Claim: Anthropic currently has clearer market momentum, while OpenAI has clearer platform breadth.
Evidence: OpenAI announced “$40 billion at a $300 billion post-money valuation” in its March 31, 2025 funding update. Anthropic was reported by Reuters/AP at a $380 billion valuation after a $30 billion round on February 12, 2026, with a stated $14 billion revenue run rate.
Counterpoint: Reuters also reported OpenAI talks around a much higher potential valuation in 2026, but those are talks, not closed official disclosures. If you treat rumor and closed financing as equal, your model is already broken.
Practical recommendation: Use two labels in your spreadsheet: confirmed valuation and reported potential valuation. Decision quality improves immediately, and committee debates get shorter.
What Worked
The most useful part of this comparison was separating “valuation story” from “operating economics.” I tested both vendors’ current API rate cards against two practical workloads: a coding assistant and a support bot.
Claim: OpenAI currently offers a cheaper baseline for many high-volume workloads, while Anthropic gives stronger “premium specialist” signaling in enterprise coding.
Evidence:
For API list pricing (checked February 17, 2026):
- OpenAI GPT-5.2: $1.75 input / $14 output per 1M tokens.
- OpenAI GPT-5 mini: $0.25 input / $2 output per 1M.
- Anthropic Sonnet 4.5: $3 input / $15 output per MTok.
- Anthropic Opus 4.6: $5 input / $25 output per MTok.
- Anthropic Haiku 4.5: $1 input / $5 output per MTok.
In a simple monthly coding workload test (50M input, 10M output):
- OpenAI GPT-5.2 total list cost: about $227.50
- Anthropic Sonnet 4.5 total list cost: about $300.00
In a lightweight support workload (5M input, 2M output):
- OpenAI GPT-5 mini: about $5.25
- Anthropic Haiku 4.5: about $15.00
Counterpoint: Raw token cost is not total value. If one model reduces error-handling loops or review cycles, it can win despite higher per-token pricing. Also, both vendors offer discount paths (batching, caching) that can narrow gaps.
Practical recommendation: Model value as total workflow cost, not token price. Include human review minutes, failed calls, and re-prompt cycles before picking a “winner.”
| Comparison Area | Anthropic | OpenAI | What It Means in Practice |
|---|---|---|---|
| Latest confirmed valuation timing | Feb 2026 print at $380B | Mar 2025 official print at $300B | Anthropic gives a fresher market signal; OpenAI requires more inference between funding events. |
| Revenue disclosure quality | Reuters cites $14B run-rate | OpenAI funding post cites 500M weekly users, less current revenue detail in that post | Anthropic is easier to model on a valuation-to-run-rate basis right now. |
| API price floor | Haiku 4.5 starts at $1/$5 | GPT-5 mini starts at $0.25/$2 | OpenAI is typically easier to deploy for cost-sensitive, high-volume automation. |
| Premium model pricing | Opus 4.6 at $5/$25 | GPT-5.2 at $1.75/$14; GPT-5.2 Pro much higher | Anthropic’s premium tier can be expensive, but may still pencil out for high-value coding workflows. |
What Didn’t
This market still has a reporting asymmetry problem, and it affects anyone trying to compare valuations honestly.
Claim: OpenAI vs Anthropic valuation comparisons are often apples-to-oranges because disclosure cadence and metric style differ.
Evidence: Anthropic’s current financing and run-rate details were reported this week. OpenAI has a strong official funding post, plus SoftBank confirmation of completed investment tranches, but no equally fresh official valuation update on OpenAI’s own site as of February 17, 2026.
Counterpoint: Private market valuation is never purely fundamental anyway. It reflects bargaining power, strategic scarcity, and optionality around future products. Precision beyond one decimal can give a false sense of confidence.
Practical recommendation: Use valuation bands, not single-point targets. For planning, treat OpenAI as confirmed 300B, market chatter materially higher, and Anthropic as confirmed/reported around 380B with recent close.
Another friction point: product-plan pages are increasingly dynamic, and snapshot tools do not always expose every displayed price cleanly. That is not a deal-breaker, but it does raise verification overhead when you need audit-grade comparisons.
Pricing Reality Check
If your valuation thesis ignores unit economics, it will age badly.
Claim: OpenAI currently gives better entry-level API economics, while Anthropic adds premium multipliers you must actively budget for.
Evidence: Anthropic pricing docs list a 1.1x multiplier for US-only inference and premium rates for long-context/fast modes; OpenAI highlights 50% batch savings and lower mini-tier pricing. Both providers now have enough pricing branches that “headline CPM” is usually not your actual bill.
Counterpoint: Discount tools cut both ways. Teams with predictable asynchronous jobs can materially reduce costs on either platform. Teams with spiky, low-latency workloads often pay closer to list.
Practical recommendation: Build three scenarios before committing: list, optimized, and stress. Most teams only calculate one, then act surprised in month two.
| Pricing Item (API) | Anthropic | OpenAI | What It Means in Practice |
|---|---|---|---|
| Main mid-tier model | Sonnet 4.5: $3 in / $15 out per MTok | GPT-5.2: $1.75 in / $14 out per 1M | OpenAI is cheaper on input-heavy tasks; output is closer but still slightly lower. |
| Low-cost tier | Haiku 4.5: $1 in / $5 out | GPT-5 mini: $0.25 in / $2 out | OpenAI has a materially lower floor for high-volume automation. |
| Batch discount | 50% input/output discount | 50% input/output discount | Both reward async batch design; architecture choices matter more than vendor slogans. |
| Extra multipliers | 1.1x for US-only inference on newer models; long-context premiums | Priority tiers and tool-call costs can add up | Your “real” price depends on compliance and latency requirements, not just model sticker rates. |
Pricing sources (checked February 17, 2026):
- OpenAI API pricing: https://openai.com/api/pricing/
- Anthropic API pricing docs: https://docs.anthropic.com/en/docs/about-claude/pricing
- OpenAI ChatGPT plans page: https://openai.com/chatgpt/pricing
- Claude plans page: https://claude.com/pricing
Who Should Pick Which
Claim: Most buyers in 2026 should default to OpenAI for risk-adjusted economics, while specific enterprise teams can justify Anthropic at current valuation levels.
Evidence: OpenAI combines broad distribution, lower entry API pricing, and a still-defensible confirmed valuation baseline. Anthropic shows exceptional momentum, fresher valuation data, and strong enterprise coding traction.
Counterpoint: If OpenAI closes a new round near the highest reported figures, this comparison can change quickly. If Anthropic’s growth normalizes faster than expected, its current multiple will look tighter.
Practical recommendation:
Pick OpenAI now if you need:
- Lower-cost scaling across many mixed workloads
- Broader ecosystem optionality
- A conservative default for most teams
Pick Anthropic now if you need:
- Deep enterprise coding focus and are willing to pay for it
- A thesis tied to recent momentum and faster disclosed growth signals
- Stronger preference for its product direction in regulated enterprise contexts
Decision summary:
Use now: OpenAI for most operators and budget owners; Anthropic for coding-heavy enterprises with clear ROI tracking.
Wait: Anyone making large valuation-driven commitments based on rumored OpenAI 2026 fundraising terms.
Re-check in 30-60 days: official OpenAI valuation updates, Anthropic post-round execution against run-rate claims, and any API pricing adjustments on mini/haiku tiers.